From 9cc1f20ad577bc17250958080fafd12e2830e296 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Wed, 3 Apr 2024 23:26:48 -0400 Subject: [PATCH 001/110] add simplified model manager install API to InvocationContext --- .../app/services/shared/invocation_context.py | 98 ++++++++++++++++++- 1 file changed, 97 insertions(+), 1 deletion(-) diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py index e533baf3bc..20b03bb28c 100644 --- a/invokeai/app/services/shared/invocation_context.py +++ b/invokeai/app/services/shared/invocation_context.py @@ -1,9 +1,10 @@ import threading from dataclasses import dataclass from pathlib import Path -from typing import TYPE_CHECKING, Optional, Union +from typing import TYPE_CHECKING, Any, Dict, Optional, Union from PIL.Image import Image +from pydantic.networks import AnyHttpUrl from torch import Tensor from invokeai.app.invocations.constants import IMAGE_MODES @@ -414,6 +415,101 @@ class ModelsInterface(InvocationContextInterface): model_format=format, ) + def install_model( + self, + source: str, + config: Optional[Dict[str, Any]] = None, + access_token: Optional[str] = None, + inplace: Optional[bool] = False, + timeout: Optional[int] = 0, + ) -> str: + """Install and register a model in the database. + + Args: + source: String source; see below + config: Optional dict. Any fields in this dict + will override corresponding autoassigned probe fields in the + model's config record. + access_token: Optional access token for remote sources. + inplace: If true, installs a local model in place rather than copying + it into the models directory + timeout: How long to wait on install (in seconds). A value of 0 (default) + blocks indefinitely + + The source can be: + 1. A local file path in posix() format (`/foo/bar` or `C:\foo\bar`) + 2. An http or https URL (`https://foo.bar/foo`) + 3. A HuggingFace repo_id (`foo/bar`, `foo/bar:fp16`, `foo/bar:fp16:vae`) + + We extend the HuggingFace repo_id syntax to include the variant and the + subfolder or path. The following are acceptable alternatives: + stabilityai/stable-diffusion-v4 + stabilityai/stable-diffusion-v4:fp16 + stabilityai/stable-diffusion-v4:fp16:vae + stabilityai/stable-diffusion-v4::/checkpoints/sd4.safetensors + stabilityai/stable-diffusion-v4:onnx:vae + + Because a local file path can look like a huggingface repo_id, the logic + first checks whether the path exists on disk, and if not, it is treated as + a parseable huggingface repo. + + Returns: + Key to the newly installed model. + + May Raise: + ValueError -- bad source + UnknownModelException -- remote model not found + InvalidModelException -- what was retrieved from remote is not a model + TimeoutError -- model could not be installed within timeout + Exception -- another error condition + """ + installer = self._services.model_manager.install + job = installer.heuristic_import( + source=source, + config=config, + access_token=access_token, + inplace=inplace, + ) + installer.wait_for_job(job, timeout) + if job.errored: + raise Exception(job.error) + key: str = job.config_out.key + return key + + def download_and_cache_model( + self, + source: Union[str, AnyHttpUrl], + access_token: Optional[str] = None, + timeout: Optional[int] = 0, + ) -> Path: + """Download the model file located at source to the models cache and return its Path. + + This can be used to single-file install models and other resources of arbitrary types + which should not get registered with the database. If the model is already + installed, the cached path will be returned. Otherwise it will be downloaded. + + Args: + source: A URL or a string that can be converted in one. Repo_ids + do not work here. + access_token: Optional access token for restricted resources. + timeout: Wait up to the indicated number of seconds before timing + out long downloads. + + Result: + Path of the downloaded model + + May Raise: + HTTPError + TimeoutError + """ + installer = self._services.model_manager.install + path: Path = installer.download_and_cache( + source=source, + access_token=access_token, + timeout=timeout, + ) + return path + class ConfigInterface(InvocationContextInterface): def get(self) -> InvokeAIAppConfig: From af1b57a01f7e7920c44f21b60d07c33ce2355de6 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Wed, 3 Apr 2024 23:26:48 -0400 Subject: [PATCH 002/110] add simplified model manager install API to InvocationContext --- .../app/services/shared/invocation_context.py | 98 ++++++++++++++++++- 1 file changed, 97 insertions(+), 1 deletion(-) diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py index 9994d663e5..176303b055 100644 --- a/invokeai/app/services/shared/invocation_context.py +++ b/invokeai/app/services/shared/invocation_context.py @@ -1,9 +1,10 @@ import threading from dataclasses import dataclass from pathlib import Path -from typing import TYPE_CHECKING, Optional, Union +from typing import TYPE_CHECKING, Any, Dict, Optional, Union from PIL.Image import Image +from pydantic.networks import AnyHttpUrl from torch import Tensor from invokeai.app.invocations.constants import IMAGE_MODES @@ -426,6 +427,101 @@ class ModelsInterface(InvocationContextInterface): model_format=format, ) + def install_model( + self, + source: str, + config: Optional[Dict[str, Any]] = None, + access_token: Optional[str] = None, + inplace: Optional[bool] = False, + timeout: Optional[int] = 0, + ) -> str: + """Install and register a model in the database. + + Args: + source: String source; see below + config: Optional dict. Any fields in this dict + will override corresponding autoassigned probe fields in the + model's config record. + access_token: Optional access token for remote sources. + inplace: If true, installs a local model in place rather than copying + it into the models directory + timeout: How long to wait on install (in seconds). A value of 0 (default) + blocks indefinitely + + The source can be: + 1. A local file path in posix() format (`/foo/bar` or `C:\foo\bar`) + 2. An http or https URL (`https://foo.bar/foo`) + 3. A HuggingFace repo_id (`foo/bar`, `foo/bar:fp16`, `foo/bar:fp16:vae`) + + We extend the HuggingFace repo_id syntax to include the variant and the + subfolder or path. The following are acceptable alternatives: + stabilityai/stable-diffusion-v4 + stabilityai/stable-diffusion-v4:fp16 + stabilityai/stable-diffusion-v4:fp16:vae + stabilityai/stable-diffusion-v4::/checkpoints/sd4.safetensors + stabilityai/stable-diffusion-v4:onnx:vae + + Because a local file path can look like a huggingface repo_id, the logic + first checks whether the path exists on disk, and if not, it is treated as + a parseable huggingface repo. + + Returns: + Key to the newly installed model. + + May Raise: + ValueError -- bad source + UnknownModelException -- remote model not found + InvalidModelException -- what was retrieved from remote is not a model + TimeoutError -- model could not be installed within timeout + Exception -- another error condition + """ + installer = self._services.model_manager.install + job = installer.heuristic_import( + source=source, + config=config, + access_token=access_token, + inplace=inplace, + ) + installer.wait_for_job(job, timeout) + if job.errored: + raise Exception(job.error) + key: str = job.config_out.key + return key + + def download_and_cache_model( + self, + source: Union[str, AnyHttpUrl], + access_token: Optional[str] = None, + timeout: Optional[int] = 0, + ) -> Path: + """Download the model file located at source to the models cache and return its Path. + + This can be used to single-file install models and other resources of arbitrary types + which should not get registered with the database. If the model is already + installed, the cached path will be returned. Otherwise it will be downloaded. + + Args: + source: A URL or a string that can be converted in one. Repo_ids + do not work here. + access_token: Optional access token for restricted resources. + timeout: Wait up to the indicated number of seconds before timing + out long downloads. + + Result: + Path of the downloaded model + + May Raise: + HTTPError + TimeoutError + """ + installer = self._services.model_manager.install + path: Path = installer.download_and_cache( + source=source, + access_token=access_token, + timeout=timeout, + ) + return path + class ConfigInterface(InvocationContextInterface): def get(self) -> InvokeAIAppConfig: From df5ebdbc4f605f1d078e47a4f235a1e70111c0cd Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Fri, 12 Apr 2024 00:55:21 -0400 Subject: [PATCH 003/110] add invocation_context.load_ckpt_from_url() method --- invokeai/app/invocations/upscale.py | 13 ++-- .../app/services/shared/invocation_context.py | 67 +++++++++++++++++-- .../image_util/realesrgan/realesrgan.py | 6 +- .../backend/model_manager/load/load_base.py | 2 +- .../model_manager/load/load_default.py | 7 +- .../load/model_cache/model_cache_base.py | 1 - .../load/model_cache/model_cache_default.py | 3 +- .../app/services/model_load/test_load_api.py | 57 ++++++++++++++++ 8 files changed, 131 insertions(+), 25 deletions(-) create mode 100644 tests/app/services/model_load/test_load_api.py diff --git a/invokeai/app/invocations/upscale.py b/invokeai/app/invocations/upscale.py index d687384fcb..e09618960e 100644 --- a/invokeai/app/invocations/upscale.py +++ b/invokeai/app/invocations/upscale.py @@ -1,5 +1,4 @@ # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) & the InvokeAI Team -from pathlib import Path from typing import Literal import cv2 @@ -11,7 +10,6 @@ from pydantic import ConfigDict from invokeai.app.invocations.fields import ImageField from invokeai.app.invocations.primitives import ImageOutput from invokeai.app.services.shared.invocation_context import InvocationContext -from invokeai.app.util.download_with_progress import download_with_progress_bar from invokeai.backend.image_util.basicsr.rrdbnet_arch import RRDBNet from invokeai.backend.image_util.realesrgan.realesrgan import RealESRGAN from invokeai.backend.util.devices import choose_torch_device @@ -56,7 +54,6 @@ class ESRGANInvocation(BaseInvocation, WithMetadata, WithBoard): rrdbnet_model = None netscale = None - esrgan_model_path = None if self.model_name in [ "RealESRGAN_x4plus.pth", @@ -99,16 +96,13 @@ class ESRGANInvocation(BaseInvocation, WithMetadata, WithBoard): context.logger.error(msg) raise ValueError(msg) - esrgan_model_path = Path(context.config.get().models_path, f"core/upscaling/realesrgan/{self.model_name}") - - # Downloads the ESRGAN model if it doesn't already exist - download_with_progress_bar( - name=self.model_name, url=ESRGAN_MODEL_URLS[self.model_name], dest_path=esrgan_model_path + loadnet = context.models.load_ckpt_from_url( + source=ESRGAN_MODEL_URLS[self.model_name], ) upscaler = RealESRGAN( scale=netscale, - model_path=esrgan_model_path, + loadnet=loadnet.model, model=rrdbnet_model, half=False, tile=self.tile_size, @@ -118,6 +112,7 @@ class ESRGANInvocation(BaseInvocation, WithMetadata, WithBoard): # TODO: This strips the alpha... is that okay? cv2_image = cv2.cvtColor(np.array(image.convert("RGB")), cv2.COLOR_RGB2BGR) upscaled_image = upscaler.upscale(cv2_image) + pil_image = Image.fromarray(cv2.cvtColor(upscaled_image, cv2.COLOR_BGR2RGB)).convert("RGBA") torch.cuda.empty_cache() diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py index 20b03bb28c..5cfe9c17a1 100644 --- a/invokeai/app/services/shared/invocation_context.py +++ b/invokeai/app/services/shared/invocation_context.py @@ -1,11 +1,14 @@ import threading from dataclasses import dataclass from pathlib import Path -from typing import TYPE_CHECKING, Any, Dict, Optional, Union +from typing import TYPE_CHECKING, Any, Callable, Dict, Optional, Union +from picklescan.scanner import scan_file_path from PIL.Image import Image from pydantic.networks import AnyHttpUrl +from safetensors.torch import load_file as safetensors_load_file from torch import Tensor +from torch import load as torch_load from invokeai.app.invocations.constants import IMAGE_MODES from invokeai.app.invocations.fields import MetadataField, WithBoard, WithMetadata @@ -476,13 +479,14 @@ class ModelsInterface(InvocationContextInterface): key: str = job.config_out.key return key - def download_and_cache_model( + def download_and_cache_ckpt( self, source: Union[str, AnyHttpUrl], access_token: Optional[str] = None, timeout: Optional[int] = 0, ) -> Path: - """Download the model file located at source to the models cache and return its Path. + """ + Download the model file located at source to the models cache and return its Path. This can be used to single-file install models and other resources of arbitrary types which should not get registered with the database. If the model is already @@ -510,10 +514,65 @@ class ModelsInterface(InvocationContextInterface): ) return path + def load_ckpt_from_url( + self, + source: Union[str, AnyHttpUrl], + access_token: Optional[str] = None, + timeout: Optional[int] = 0, + loader: Optional[Callable[[Path], Dict[str | int, Any]]] = None, + ) -> LoadedModel: + """ + Load and cache the model file located at the indicated URL. + + This will check the model download cache for the model designated + by the provided URL and download it if needed using download_and_cache_model(). + It will then load the model into the RAM cache. If the optional loader + argument is provided, the loader will be invoked to load the model into + memory. Otherwise the method will call safetensors.torch.load_file() or + torch.load() as appropriate to the file suffix. + + Be aware that the LoadedModel object will have a `config` attribute of None. + + Args: + source: A URL or a string that can be converted in one. Repo_ids + do not work here. + access_token: Optional access token for restricted resources. + timeout: Wait up to the indicated number of seconds before timing + out long downloads. + loader: A Callable that expects a Path and returns a Dict[str|int, Any] + + Returns: + A LoadedModel object. + """ + ram_cache = self._services.model_manager.load.ram_cache + try: + return LoadedModel(_locker=ram_cache.get(key=str(source))) + except IndexError: + pass + + def torch_load_file(checkpoint: Path) -> Dict[str | int, Any]: + scan_result = scan_file_path(checkpoint) + if scan_result.infected_files != 0: + raise Exception("The model at {checkpoint} is potentially infected by malware. Aborting load.") + return torch_load(path, map_location="cpu") + + path = self.download_and_cache_ckpt(source, access_token, timeout) + if loader is None: + loader = ( + torch_load_file + if path.suffix.endswith((".ckpt", ".pt", ".pth", ".bin")) + else lambda path: safetensors_load_file(path, device="cpu") + ) + + raw_model = loader(path) + ram_cache.put(key=str(source), model=raw_model) + return LoadedModel(_locker=ram_cache.get(key=str(source))) + class ConfigInterface(InvocationContextInterface): def get(self) -> InvokeAIAppConfig: - """Gets the app's config. + """ + Gets the app's config. Returns: The app's config. diff --git a/invokeai/backend/image_util/realesrgan/realesrgan.py b/invokeai/backend/image_util/realesrgan/realesrgan.py index c06504b608..7c4d90f5bd 100644 --- a/invokeai/backend/image_util/realesrgan/realesrgan.py +++ b/invokeai/backend/image_util/realesrgan/realesrgan.py @@ -1,6 +1,5 @@ import math from enum import Enum -from pathlib import Path from typing import Any, Optional import cv2 @@ -11,6 +10,7 @@ from cv2.typing import MatLike from tqdm import tqdm from invokeai.backend.image_util.basicsr.rrdbnet_arch import RRDBNet +from invokeai.backend.model_manager.config import AnyModel from invokeai.backend.util.devices import choose_torch_device """ @@ -52,7 +52,7 @@ class RealESRGAN: def __init__( self, scale: int, - model_path: Path, + loadnet: AnyModel, model: RRDBNet, tile: int = 0, tile_pad: int = 10, @@ -67,8 +67,6 @@ class RealESRGAN: self.half = half self.device = choose_torch_device() - loadnet = torch.load(model_path, map_location=torch.device("cpu")) - # prefer to use params_ema if "params_ema" in loadnet: keyname = "params_ema" diff --git a/invokeai/backend/model_manager/load/load_base.py b/invokeai/backend/model_manager/load/load_base.py index c336926aea..41a36d7b51 100644 --- a/invokeai/backend/model_manager/load/load_base.py +++ b/invokeai/backend/model_manager/load/load_base.py @@ -23,8 +23,8 @@ from invokeai.backend.model_manager.load.model_cache.model_cache_base import Mod class LoadedModel: """Context manager object that mediates transfer from RAM<->VRAM.""" - config: AnyModelConfig _locker: ModelLockerBase + config: Optional[AnyModelConfig] = None def __enter__(self) -> AnyModel: """Context entry.""" diff --git a/invokeai/backend/model_manager/load/load_default.py b/invokeai/backend/model_manager/load/load_default.py index 60cc1f5e6c..8e08f065e1 100644 --- a/invokeai/backend/model_manager/load/load_default.py +++ b/invokeai/backend/model_manager/load/load_default.py @@ -16,7 +16,7 @@ from invokeai.backend.model_manager.config import DiffusersConfigBase, ModelType from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase from invokeai.backend.model_manager.load.load_base import LoadedModel, ModelLoaderBase from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase, ModelLockerBase -from invokeai.backend.model_manager.load.model_util import calc_model_size_by_data, calc_model_size_by_fs +from invokeai.backend.model_manager.load.model_util import calc_model_size_by_fs from invokeai.backend.model_manager.load.optimizations import skip_torch_weight_init from invokeai.backend.util.devices import choose_torch_device, torch_dtype @@ -95,7 +95,6 @@ class ModelLoader(ModelLoaderBase): config.key, submodel_type=submodel_type, model=loaded_model, - size=calc_model_size_by_data(loaded_model), ) return self._ram_cache.get( @@ -126,9 +125,7 @@ class ModelLoader(ModelLoaderBase): if subtype == submodel_type: continue if submodel := getattr(pipeline, subtype.value, None): - self._ram_cache.put( - config.key, submodel_type=subtype, model=submodel, size=calc_model_size_by_data(submodel) - ) + self._ram_cache.put(config.key, submodel_type=subtype, model=submodel) return getattr(pipeline, submodel_type.value) if submodel_type else pipeline def _needs_conversion(self, config: AnyModelConfig, model_path: Path, dest_path: Path) -> bool: diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_base.py b/invokeai/backend/model_manager/load/model_cache/model_cache_base.py index eb82f87cb2..3ffd6714a1 100644 --- a/invokeai/backend/model_manager/load/model_cache/model_cache_base.py +++ b/invokeai/backend/model_manager/load/model_cache/model_cache_base.py @@ -143,7 +143,6 @@ class ModelCacheBase(ABC, Generic[T]): self, key: str, model: T, - size: int, submodel_type: Optional[SubModelType] = None, ) -> None: """Store model under key and optional submodel_type.""" diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py index b8312f619a..b8fe19047c 100644 --- a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py +++ b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py @@ -30,6 +30,7 @@ import torch from invokeai.backend.model_manager import AnyModel, SubModelType from invokeai.backend.model_manager.load.memory_snapshot import MemorySnapshot, get_pretty_snapshot_diff +from invokeai.backend.model_manager.load.model_util import calc_model_size_by_data from invokeai.backend.util.devices import choose_torch_device from invokeai.backend.util.logging import InvokeAILogger @@ -157,13 +158,13 @@ class ModelCache(ModelCacheBase[AnyModel]): self, key: str, model: AnyModel, - size: int, submodel_type: Optional[SubModelType] = None, ) -> None: """Store model under key and optional submodel_type.""" key = self._make_cache_key(key, submodel_type) if key in self._cached_models: return + size = calc_model_size_by_data(model) self.make_room(size) cache_record = CacheRecord(key, model, size) self._cached_models[key] = cache_record diff --git a/tests/app/services/model_load/test_load_api.py b/tests/app/services/model_load/test_load_api.py new file mode 100644 index 0000000000..b99cc7d824 --- /dev/null +++ b/tests/app/services/model_load/test_load_api.py @@ -0,0 +1,57 @@ +from pathlib import Path + +import pytest + +from invokeai.app.services.invocation_services import InvocationServices +from invokeai.app.services.model_manager import ModelManagerServiceBase +from invokeai.app.services.shared.invocation_context import InvocationContext, build_invocation_context +from invokeai.backend.model_manager.load.load_base import LoadedModel +from tests.backend.model_manager.model_manager_fixtures import * # noqa F403 + + +@pytest.fixture() +def mock_context( + mock_services: InvocationServices, + mm2_model_manager: ModelManagerServiceBase, +) -> InvocationContext: + mock_services.model_manager = mm2_model_manager + return build_invocation_context( + services=mock_services, + data=None, # type: ignore + cancel_event=None, # type: ignore + ) + + +def test_download_and_cache(mock_context: InvocationContext, mm2_root_dir: Path): + downloaded_path = mock_context.models.download_and_cache_ckpt( + "https://www.test.foo/download/test_embedding.safetensors" + ) + assert downloaded_path.is_file() + assert downloaded_path.exists() + assert downloaded_path.name == "test_embedding.safetensors" + assert downloaded_path.parent.parent == mm2_root_dir / "models/.cache" + + downloaded_path_2 = mock_context.models.download_and_cache_ckpt( + "https://www.test.foo/download/test_embedding.safetensors" + ) + assert downloaded_path == downloaded_path_2 + + +def test_download_and_load(mock_context: InvocationContext): + loaded_model_1 = mock_context.models.load_ckpt_from_url("https://www.test.foo/download/test_embedding.safetensors") + assert isinstance(loaded_model_1, LoadedModel) + + loaded_model_2 = mock_context.models.load_ckpt_from_url("https://www.test.foo/download/test_embedding.safetensors") + assert isinstance(loaded_model_2, LoadedModel) + + with loaded_model_1 as model_1, loaded_model_2 as model_2: + assert model_1 == model_2 + assert isinstance(model_1, dict) + + +def test_install_model(mock_context: InvocationContext): + key = mock_context.models.install_model("https://www.test.foo/download/test_embedding.safetensors") + assert key is not None + model = mock_context.models.load(key) + assert model is not None + assert model.config.key == key From 41b909cbe3761f59c180430478dcdeb8efba579e Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Fri, 12 Apr 2024 21:05:23 -0400 Subject: [PATCH 004/110] port dw_openpose, depth_anything, and lama processors to new model download scheme --- .../controlnet_image_processors.py | 45 ++++++++++--------- invokeai/app/invocations/infill.py | 18 ++++---- .../app/services/shared/invocation_context.py | 4 +- .../image_util/depth_anything/__init__.py | 37 +++++---------- .../image_util/dw_openpose/__init__.py | 5 ++- .../image_util/dw_openpose/wholebody.py | 29 ++++-------- .../backend/image_util/infill_methods/lama.py | 39 +++++++--------- 7 files changed, 72 insertions(+), 105 deletions(-) diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py index a49c910eeb..12a2ae9c96 100644 --- a/invokeai/app/invocations/controlnet_image_processors.py +++ b/invokeai/app/invocations/controlnet_image_processors.py @@ -137,7 +137,7 @@ class ImageProcessorInvocation(BaseInvocation, WithMetadata, WithBoard): image: ImageField = InputField(description="The image to process") - def run_processor(self, image: Image.Image) -> Image.Image: + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: # superclass just passes through image without processing return image @@ -148,7 +148,7 @@ class ImageProcessorInvocation(BaseInvocation, WithMetadata, WithBoard): def invoke(self, context: InvocationContext) -> ImageOutput: raw_image = self.load_image(context) # image type should be PIL.PngImagePlugin.PngImageFile ? - processed_image = self.run_processor(raw_image) + processed_image = self.run_processor(raw_image, context) # currently can't see processed image in node UI without a showImage node, # so for now setting image_type to RESULT instead of INTERMEDIATE so will get saved in gallery @@ -189,7 +189,7 @@ class CannyImageProcessorInvocation(ImageProcessorInvocation): # Keep alpha channel for Canny processing to detect edges of transparent areas return context.images.get_pil(self.image.image_name, "RGBA") - def run_processor(self, image: Image.Image) -> Image.Image: + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: processed_image = get_canny_edges( image, self.low_threshold, @@ -216,7 +216,7 @@ class HedImageProcessorInvocation(ImageProcessorInvocation): # safe: bool = InputField(default=False, description=FieldDescriptions.safe_mode) scribble: bool = InputField(default=False, description=FieldDescriptions.scribble_mode) - def run_processor(self, image: Image.Image) -> Image.Image: + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: hed_processor = HEDProcessor() processed_image = hed_processor.run( image, @@ -243,7 +243,7 @@ class LineartImageProcessorInvocation(ImageProcessorInvocation): image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res) coarse: bool = InputField(default=False, description="Whether to use coarse mode") - def run_processor(self, image: Image.Image) -> Image.Image: + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: lineart_processor = LineartProcessor() processed_image = lineart_processor.run( image, detect_resolution=self.detect_resolution, image_resolution=self.image_resolution, coarse=self.coarse @@ -264,7 +264,7 @@ class LineartAnimeImageProcessorInvocation(ImageProcessorInvocation): detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res) image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res) - def run_processor(self, image: Image.Image) -> Image.Image: + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: processor = LineartAnimeProcessor() processed_image = processor.run( image, @@ -291,7 +291,8 @@ class MidasDepthImageProcessorInvocation(ImageProcessorInvocation): # depth_and_normal not supported in controlnet_aux v0.0.3 # depth_and_normal: bool = InputField(default=False, description="whether to use depth and normal mode") - def run_processor(self, image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + # TODO: replace from_pretrained() calls with context.models.download_and_cache() (or similar) midas_processor = MidasDetector.from_pretrained("lllyasviel/Annotators") processed_image = midas_processor( image, @@ -318,9 +319,9 @@ class NormalbaeImageProcessorInvocation(ImageProcessorInvocation): detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res) image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res) - def run_processor(self, image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: normalbae_processor = NormalBaeDetector.from_pretrained("lllyasviel/Annotators") - processed_image = normalbae_processor( + processed_image: Image.Image = normalbae_processor( image, detect_resolution=self.detect_resolution, image_resolution=self.image_resolution ) return processed_image @@ -337,7 +338,7 @@ class MlsdImageProcessorInvocation(ImageProcessorInvocation): thr_v: float = InputField(default=0.1, ge=0, description="MLSD parameter `thr_v`") thr_d: float = InputField(default=0.1, ge=0, description="MLSD parameter `thr_d`") - def run_processor(self, image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: mlsd_processor = MLSDdetector.from_pretrained("lllyasviel/Annotators") processed_image = mlsd_processor( image, @@ -360,7 +361,7 @@ class PidiImageProcessorInvocation(ImageProcessorInvocation): safe: bool = InputField(default=False, description=FieldDescriptions.safe_mode) scribble: bool = InputField(default=False, description=FieldDescriptions.scribble_mode) - def run_processor(self, image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: pidi_processor = PidiNetDetector.from_pretrained("lllyasviel/Annotators") processed_image = pidi_processor( image, @@ -388,7 +389,7 @@ class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation): w: int = InputField(default=512, ge=0, description="Content shuffle `w` parameter") f: int = InputField(default=256, ge=0, description="Content shuffle `f` parameter") - def run_processor(self, image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: content_shuffle_processor = ContentShuffleDetector() processed_image = content_shuffle_processor( image, @@ -412,7 +413,7 @@ class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation): class ZoeDepthImageProcessorInvocation(ImageProcessorInvocation): """Applies Zoe depth processing to image""" - def run_processor(self, image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: zoe_depth_processor = ZoeDetector.from_pretrained("lllyasviel/Annotators") processed_image = zoe_depth_processor(image) return processed_image @@ -433,7 +434,7 @@ class MediapipeFaceProcessorInvocation(ImageProcessorInvocation): detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res) image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res) - def run_processor(self, image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: mediapipe_face_processor = MediapipeFaceDetector() processed_image = mediapipe_face_processor( image, @@ -461,7 +462,7 @@ class LeresImageProcessorInvocation(ImageProcessorInvocation): detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res) image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res) - def run_processor(self, image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: leres_processor = LeresDetector.from_pretrained("lllyasviel/Annotators") processed_image = leres_processor( image, @@ -503,7 +504,7 @@ class TileResamplerProcessorInvocation(ImageProcessorInvocation): np_img = cv2.resize(np_img, (W, H), interpolation=cv2.INTER_AREA) return np_img - def run_processor(self, img): + def run_processor(self, img: Image.Image, context: InvocationContext) -> Image.Image: np_img = np.array(img, dtype=np.uint8) processed_np_image = self.tile_resample( np_img, @@ -527,7 +528,7 @@ class SegmentAnythingProcessorInvocation(ImageProcessorInvocation): detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res) image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res) - def run_processor(self, image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: # segment_anything_processor = SamDetector.from_pretrained("ybelkada/segment-anything", subfolder="checkpoints") segment_anything_processor = SamDetectorReproducibleColors.from_pretrained( "ybelkada/segment-anything", subfolder="checkpoints" @@ -573,7 +574,7 @@ class ColorMapImageProcessorInvocation(ImageProcessorInvocation): color_map_tile_size: int = InputField(default=64, ge=0, description=FieldDescriptions.tile_size) - def run_processor(self, image: Image.Image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: np_image = np.array(image, dtype=np.uint8) height, width = np_image.shape[:2] @@ -608,8 +609,8 @@ class DepthAnythingImageProcessorInvocation(ImageProcessorInvocation): ) resolution: int = InputField(default=512, ge=64, multiple_of=64, description=FieldDescriptions.image_res) - def run_processor(self, image: Image.Image): - depth_anything_detector = DepthAnythingDetector() + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + depth_anything_detector = DepthAnythingDetector(context) depth_anything_detector.load_model(model_size=self.model_size) processed_image = depth_anything_detector(image=image, resolution=self.resolution) @@ -631,8 +632,8 @@ class DWOpenposeImageProcessorInvocation(ImageProcessorInvocation): draw_hands: bool = InputField(default=False) image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res) - def run_processor(self, image: Image.Image): - dw_openpose = DWOpenposeDetector() + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + dw_openpose = DWOpenposeDetector(context) processed_image = dw_openpose( image, draw_face=self.draw_face, diff --git a/invokeai/app/invocations/infill.py b/invokeai/app/invocations/infill.py index 418bc62fdc..edee275e72 100644 --- a/invokeai/app/invocations/infill.py +++ b/invokeai/app/invocations/infill.py @@ -38,7 +38,7 @@ class InfillImageProcessorInvocation(BaseInvocation, WithMetadata, WithBoard): image: ImageField = InputField(description="The image to process") @abstractmethod - def infill(self, image: Image.Image) -> Image.Image: + def infill(self, image: Image.Image, context: InvocationContext) -> Image.Image: """Infill the image with the specified method""" pass @@ -57,7 +57,7 @@ class InfillImageProcessorInvocation(BaseInvocation, WithMetadata, WithBoard): return ImageOutput.build(context.images.get_dto(self.image.image_name)) # Perform Infill action - infilled_image = self.infill(input_image) + infilled_image = self.infill(input_image, context) # Create ImageDTO for Infilled Image infilled_image_dto = context.images.save(image=infilled_image) @@ -75,7 +75,7 @@ class InfillColorInvocation(InfillImageProcessorInvocation): description="The color to use to infill", ) - def infill(self, image: Image.Image): + def infill(self, image: Image.Image, context: InvocationContext): solid_bg = Image.new("RGBA", image.size, self.color.tuple()) infilled = Image.alpha_composite(solid_bg, image.convert("RGBA")) infilled.paste(image, (0, 0), image.split()[-1]) @@ -94,7 +94,7 @@ class InfillTileInvocation(InfillImageProcessorInvocation): description="The seed to use for tile generation (omit for random)", ) - def infill(self, image: Image.Image): + def infill(self, image: Image.Image, context: InvocationContext): output = infill_tile(image, seed=self.seed, tile_size=self.tile_size) return output.infilled @@ -108,7 +108,7 @@ class InfillPatchMatchInvocation(InfillImageProcessorInvocation): downscale: float = InputField(default=2.0, gt=0, description="Run patchmatch on downscaled image to speedup infill") resample_mode: PIL_RESAMPLING_MODES = InputField(default="bicubic", description="The resampling mode") - def infill(self, image: Image.Image): + def infill(self, image: Image.Image, context: InvocationContext): resample_mode = PIL_RESAMPLING_MAP[self.resample_mode] width = int(image.width / self.downscale) @@ -132,8 +132,8 @@ class InfillPatchMatchInvocation(InfillImageProcessorInvocation): class LaMaInfillInvocation(InfillImageProcessorInvocation): """Infills transparent areas of an image using the LaMa model""" - def infill(self, image: Image.Image): - lama = LaMA() + def infill(self, image: Image.Image, context: InvocationContext): + lama = LaMA(context) return lama(image) @@ -141,7 +141,7 @@ class LaMaInfillInvocation(InfillImageProcessorInvocation): class CV2InfillInvocation(InfillImageProcessorInvocation): """Infills transparent areas of an image using OpenCV Inpainting""" - def infill(self, image: Image.Image): + def infill(self, image: Image.Image, context: InvocationContext): return cv2_inpaint(image) @@ -163,5 +163,5 @@ class MosaicInfillInvocation(InfillImageProcessorInvocation): description="The max threshold for color", ) - def infill(self, image: Image.Image): + def infill(self, image: Image.Image, context: InvocationContext): return infill_mosaic(image, (self.tile_width, self.tile_height), self.min_color.tuple(), self.max_color.tuple()) diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py index e97d29d308..0d27b2520b 100644 --- a/invokeai/app/services/shared/invocation_context.py +++ b/invokeai/app/services/shared/invocation_context.py @@ -534,10 +534,10 @@ class ModelsInterface(InvocationContextInterface): loader: Optional[Callable[[Path], Dict[str | int, Any]]] = None, ) -> LoadedModel: """ - Load and cache the model file located at the indicated URL. + Download, cache, and Load the model file located at the indicated URL. This will check the model download cache for the model designated - by the provided URL and download it if needed using download_and_cache_model(). + by the provided URL and download it if needed using download_and_cache_ckpt(). It will then load the model into the RAM cache. If the optional loader argument is provided, the loader will be invoked to load the model into memory. Otherwise the method will call safetensors.torch.load_file() or diff --git a/invokeai/backend/image_util/depth_anything/__init__.py b/invokeai/backend/image_util/depth_anything/__init__.py index ccac2ba949..560d977b55 100644 --- a/invokeai/backend/image_util/depth_anything/__init__.py +++ b/invokeai/backend/image_util/depth_anything/__init__.py @@ -1,5 +1,4 @@ -import pathlib -from typing import Literal, Union +from typing import Literal, Optional, Union import cv2 import numpy as np @@ -10,7 +9,7 @@ from PIL import Image from torchvision.transforms import Compose from invokeai.app.services.config.config_default import get_config -from invokeai.app.util.download_with_progress import download_with_progress_bar +from invokeai.app.services.shared.invocation_context import InvocationContext from invokeai.backend.image_util.depth_anything.model.dpt import DPT_DINOv2 from invokeai.backend.image_util.depth_anything.utilities.util import NormalizeImage, PrepareForNet, Resize from invokeai.backend.util.devices import choose_torch_device @@ -20,18 +19,9 @@ config = get_config() logger = InvokeAILogger.get_logger(config=config) DEPTH_ANYTHING_MODELS = { - "large": { - "url": "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vitl14.pth?download=true", - "local": "any/annotators/depth_anything/depth_anything_vitl14.pth", - }, - "base": { - "url": "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vitb14.pth?download=true", - "local": "any/annotators/depth_anything/depth_anything_vitb14.pth", - }, - "small": { - "url": "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vits14.pth?download=true", - "local": "any/annotators/depth_anything/depth_anything_vits14.pth", - }, + "large": "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vitl14.pth?download=true", + "base": "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vitb14.pth?download=true", + "small": "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vits14.pth?download=true", } @@ -53,18 +43,14 @@ transform = Compose( class DepthAnythingDetector: - def __init__(self) -> None: - self.model = None + def __init__(self, context: InvocationContext) -> None: + self.context = context + self.model: Optional[DPT_DINOv2] = None self.model_size: Union[Literal["large", "base", "small"], None] = None self.device = choose_torch_device() - def load_model(self, model_size: Literal["large", "base", "small"] = "small"): - DEPTH_ANYTHING_MODEL_PATH = config.models_path / DEPTH_ANYTHING_MODELS[model_size]["local"] - download_with_progress_bar( - pathlib.Path(DEPTH_ANYTHING_MODELS[model_size]["url"]).name, - DEPTH_ANYTHING_MODELS[model_size]["url"], - DEPTH_ANYTHING_MODEL_PATH, - ) + def load_model(self, model_size: Literal["large", "base", "small"] = "small") -> DPT_DINOv2: + depth_anything_model_path = self.context.models.download_and_cache_ckpt(DEPTH_ANYTHING_MODELS[model_size]) if not self.model or model_size != self.model_size: del self.model @@ -78,7 +64,8 @@ class DepthAnythingDetector: case "large": self.model = DPT_DINOv2(encoder="vitl", features=256, out_channels=[256, 512, 1024, 1024]) - self.model.load_state_dict(torch.load(DEPTH_ANYTHING_MODEL_PATH.as_posix(), map_location="cpu")) + assert self.model is not None + self.model.load_state_dict(torch.load(depth_anything_model_path.as_posix(), map_location="cpu")) self.model.eval() self.model.to(choose_torch_device()) diff --git a/invokeai/backend/image_util/dw_openpose/__init__.py b/invokeai/backend/image_util/dw_openpose/__init__.py index c258ef2c78..17ca0233c8 100644 --- a/invokeai/backend/image_util/dw_openpose/__init__.py +++ b/invokeai/backend/image_util/dw_openpose/__init__.py @@ -3,6 +3,7 @@ import torch from controlnet_aux.util import resize_image from PIL import Image +from invokeai.app.services.shared.invocation_context import InvocationContext from invokeai.backend.image_util.dw_openpose.utils import draw_bodypose, draw_facepose, draw_handpose from invokeai.backend.image_util.dw_openpose.wholebody import Wholebody @@ -39,8 +40,8 @@ class DWOpenposeDetector: Credits: https://github.com/IDEA-Research/DWPose """ - def __init__(self) -> None: - self.pose_estimation = Wholebody() + def __init__(self, context: InvocationContext) -> None: + self.pose_estimation = Wholebody(context) def __call__( self, image: Image.Image, draw_face=False, draw_body=True, draw_hands=False, resolution=512 diff --git a/invokeai/backend/image_util/dw_openpose/wholebody.py b/invokeai/backend/image_util/dw_openpose/wholebody.py index 35d340640d..3628b0abd5 100644 --- a/invokeai/backend/image_util/dw_openpose/wholebody.py +++ b/invokeai/backend/image_util/dw_openpose/wholebody.py @@ -4,44 +4,31 @@ import numpy as np import onnxruntime as ort +import torch from invokeai.app.services.config.config_default import get_config -from invokeai.app.util.download_with_progress import download_with_progress_bar +from invokeai.app.services.shared.invocation_context import InvocationContext from invokeai.backend.util.devices import choose_torch_device from .onnxdet import inference_detector from .onnxpose import inference_pose DWPOSE_MODELS = { - "yolox_l.onnx": { - "local": "any/annotators/dwpose/yolox_l.onnx", - "url": "https://huggingface.co/yzd-v/DWPose/resolve/main/yolox_l.onnx?download=true", - }, - "dw-ll_ucoco_384.onnx": { - "local": "any/annotators/dwpose/dw-ll_ucoco_384.onnx", - "url": "https://huggingface.co/yzd-v/DWPose/resolve/main/dw-ll_ucoco_384.onnx?download=true", - }, + "yolox_l.onnx": "https://huggingface.co/yzd-v/DWPose/resolve/main/yolox_l.onnx?download=true", + "dw-ll_ucoco_384.onnx": "https://huggingface.co/yzd-v/DWPose/resolve/main/dw-ll_ucoco_384.onnx?download=true", } config = get_config() class Wholebody: - def __init__(self): + def __init__(self, context: InvocationContext): device = choose_torch_device() - providers = ["CUDAExecutionProvider"] if device == "cuda" else ["CPUExecutionProvider"] + providers = ["CUDAExecutionProvider"] if device == torch.device("cuda") else ["CPUExecutionProvider"] - DET_MODEL_PATH = config.models_path / DWPOSE_MODELS["yolox_l.onnx"]["local"] - download_with_progress_bar("yolox_l.onnx", DWPOSE_MODELS["yolox_l.onnx"]["url"], DET_MODEL_PATH) - - POSE_MODEL_PATH = config.models_path / DWPOSE_MODELS["dw-ll_ucoco_384.onnx"]["local"] - download_with_progress_bar( - "dw-ll_ucoco_384.onnx", DWPOSE_MODELS["dw-ll_ucoco_384.onnx"]["url"], POSE_MODEL_PATH - ) - - onnx_det = DET_MODEL_PATH - onnx_pose = POSE_MODEL_PATH + onnx_det = context.models.download_and_cache_ckpt(DWPOSE_MODELS["yolox_l.onnx"]) + onnx_pose = context.models.download_and_cache_ckpt(DWPOSE_MODELS["dw-ll_ucoco_384.onnx"]) self.session_det = ort.InferenceSession(path_or_bytes=onnx_det, providers=providers) self.session_pose = ort.InferenceSession(path_or_bytes=onnx_pose, providers=providers) diff --git a/invokeai/backend/image_util/infill_methods/lama.py b/invokeai/backend/image_util/infill_methods/lama.py index fa354aeed1..8c3f33efad 100644 --- a/invokeai/backend/image_util/infill_methods/lama.py +++ b/invokeai/backend/image_util/infill_methods/lama.py @@ -1,4 +1,3 @@ -import gc from typing import Any import numpy as np @@ -6,9 +5,7 @@ import torch from PIL import Image import invokeai.backend.util.logging as logger -from invokeai.app.services.config.config_default import get_config -from invokeai.app.util.download_with_progress import download_with_progress_bar -from invokeai.backend.util.devices import choose_torch_device +from invokeai.app.services.shared.invocation_context import InvocationContext def norm_img(np_img): @@ -28,18 +25,14 @@ def load_jit_model(url_or_path, device): class LaMA: + def __init__(self, context: InvocationContext): + self._context = context + def __call__(self, input_image: Image.Image, *args: Any, **kwds: Any) -> Any: - device = choose_torch_device() - model_location = get_config().models_path / "core/misc/lama/lama.pt" - - if not model_location.exists(): - download_with_progress_bar( - name="LaMa Inpainting Model", - url="https://github.com/Sanster/models/releases/download/add_big_lama/big-lama.pt", - dest_path=model_location, - ) - - model = load_jit_model(model_location, device) + loaded_model = self._context.models.load_ckpt_from_url( + source="https://github.com/Sanster/models/releases/download/add_big_lama/big-lama.pt", + loader=lambda path: load_jit_model(path, "cpu"), + ) image = np.asarray(input_image.convert("RGB")) image = norm_img(image) @@ -48,20 +41,18 @@ class LaMA: mask = np.asarray(mask) mask = np.invert(mask) mask = norm_img(mask) - mask = (mask > 0) * 1 - image = torch.from_numpy(image).unsqueeze(0).to(device) - mask = torch.from_numpy(mask).unsqueeze(0).to(device) - with torch.inference_mode(): - infilled_image = model(image, mask) + with loaded_model as model: + device = next(model.buffers()).device + image = torch.from_numpy(image).unsqueeze(0).to(device) + mask = torch.from_numpy(mask).unsqueeze(0).to(device) + + with torch.inference_mode(): + infilled_image = model(image, mask) infilled_image = infilled_image[0].permute(1, 2, 0).detach().cpu().numpy() infilled_image = np.clip(infilled_image * 255, 0, 255).astype("uint8") infilled_image = Image.fromarray(infilled_image) - del model - gc.collect() - torch.cuda.empty_cache() - return infilled_image From 3ddd7ced49979229d143edc865d32c507332a120 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Sun, 14 Apr 2024 15:54:46 -0400 Subject: [PATCH 005/110] change names of convert and download caches and add migration script --- .../app/services/config/config_default.py | 9 +- .../model_install/model_install_default.py | 17 +++- .../app/services/shared/sqlite/sqlite_util.py | 2 + .../migrations/migration_10.py | 87 +++++++++++++++++++ invokeai/app/util/download_with_progress.py | 51 ----------- .../app/services/model_load/test_load_api.py | 2 +- 6 files changed, 111 insertions(+), 57 deletions(-) create mode 100644 invokeai/app/services/shared/sqlite_migrator/migrations/migration_10.py delete mode 100644 invokeai/app/util/download_with_progress.py diff --git a/invokeai/app/services/config/config_default.py b/invokeai/app/services/config/config_default.py index f453a56584..4b5a2004be 100644 --- a/invokeai/app/services/config/config_default.py +++ b/invokeai/app/services/config/config_default.py @@ -86,6 +86,7 @@ class InvokeAIAppConfig(BaseSettings): patchmatch: Enable patchmatch inpaint code. models_dir: Path to the models directory. convert_cache_dir: Path to the converted models cache directory. When loading a non-diffusers model, it will be converted and store on disk at this location. + download_cache_dir: Path to the directory that contains dynamically downloaded models. legacy_conf_dir: Path to directory of legacy checkpoint config files. db_dir: Path to InvokeAI databases directory. outputs_dir: Path to directory for outputs. @@ -146,7 +147,8 @@ class InvokeAIAppConfig(BaseSettings): # PATHS models_dir: Path = Field(default=Path("models"), description="Path to the models directory.") - convert_cache_dir: Path = Field(default=Path("models/.cache"), description="Path to the converted models cache directory. When loading a non-diffusers model, it will be converted and store on disk at this location.") + convert_cache_dir: Path = Field(default=Path("models/.convert_cache"), description="Path to the converted models cache directory. When loading a non-diffusers model, it will be converted and store on disk at this location.") + download_cache_dir: Path = Field(default=Path("models/.download_cache"), description="Path to the directory that contains dynamically downloaded models.") legacy_conf_dir: Path = Field(default=Path("configs"), description="Path to directory of legacy checkpoint config files.") db_dir: Path = Field(default=Path("databases"), description="Path to InvokeAI databases directory.") outputs_dir: Path = Field(default=Path("outputs"), description="Path to directory for outputs.") @@ -303,6 +305,11 @@ class InvokeAIAppConfig(BaseSettings): """Path to the converted cache models directory, resolved to an absolute path..""" return self._resolve(self.convert_cache_dir) + @property + def download_cache_path(self) -> Path: + """Path to the downloaded models directory, resolved to an absolute path..""" + return self._resolve(self.download_cache_dir) + @property def custom_nodes_path(self) -> Path: """Path to the custom nodes directory, resolved to an absolute path..""" diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py index 20cfc1c4ff..f1fbcdb7ba 100644 --- a/invokeai/app/services/model_install/model_install_default.py +++ b/invokeai/app/services/model_install/model_install_default.py @@ -393,6 +393,11 @@ class ModelInstallService(ModelInstallServiceBase): rmtree(model_path) self.unregister(key) + @classmethod + def _download_cache_path(cls, source: Union[str, AnyHttpUrl], app_config: InvokeAIAppConfig) -> Path: + model_hash = sha256(str(source).encode("utf-8")).hexdigest()[0:32] + return app_config.download_cache_path / model_hash + def download_and_cache( self, source: Union[str, AnyHttpUrl], @@ -400,8 +405,7 @@ class ModelInstallService(ModelInstallServiceBase): timeout: int = 0, ) -> Path: """Download the model file located at source to the models cache and return its Path.""" - model_hash = sha256(str(source).encode("utf-8")).hexdigest()[0:32] - model_path = self._app_config.convert_cache_path / model_hash + model_path = self._download_cache_path(source, self._app_config) # We expect the cache directory to contain one and only one downloaded file. # We don't know the file's name in advance, as it is set by the download @@ -532,8 +536,13 @@ class ModelInstallService(ModelInstallServiceBase): if resolved_path in installed_model_paths: return True # Skip core models entirely - these aren't registered with the model manager. - if str(resolved_path).startswith(str(self.app_config.models_path / "core")): - return False + for special_directory in [ + self.app_config.models_path / "core", + self.app_config.convert_cache_dir, + self.app_config.download_cache_dir, + ]: + if resolved_path.is_relative_to(special_directory): + return False try: model_id = self.register_path(model_path) self._logger.info(f"Registered {model_path.name} with id {model_id}") diff --git a/invokeai/app/services/shared/sqlite/sqlite_util.py b/invokeai/app/services/shared/sqlite/sqlite_util.py index 1eed0b4409..61f35a3b4e 100644 --- a/invokeai/app/services/shared/sqlite/sqlite_util.py +++ b/invokeai/app/services/shared/sqlite/sqlite_util.py @@ -12,6 +12,7 @@ from invokeai.app.services.shared.sqlite_migrator.migrations.migration_6 import from invokeai.app.services.shared.sqlite_migrator.migrations.migration_7 import build_migration_7 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_8 import build_migration_8 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_9 import build_migration_9 +from invokeai.app.services.shared.sqlite_migrator.migrations.migration_10 import build_migration_10 from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_impl import SqliteMigrator @@ -41,6 +42,7 @@ def init_db(config: InvokeAIAppConfig, logger: Logger, image_files: ImageFileSto migrator.register_migration(build_migration_7()) migrator.register_migration(build_migration_8(app_config=config)) migrator.register_migration(build_migration_9()) + migrator.register_migration(build_migration_10(app_config=config, logger=logger)) migrator.run_migrations() return db diff --git a/invokeai/app/services/shared/sqlite_migrator/migrations/migration_10.py b/invokeai/app/services/shared/sqlite_migrator/migrations/migration_10.py new file mode 100644 index 0000000000..df341a6f2e --- /dev/null +++ b/invokeai/app/services/shared/sqlite_migrator/migrations/migration_10.py @@ -0,0 +1,87 @@ +import pathlib +import shutil +import sqlite3 +from logging import Logger + +from invokeai.app.services.config import InvokeAIAppConfig +from invokeai.app.services.model_install.model_install_default import ModelInstallService +from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_common import Migration + +LEGACY_CORE_MODELS = { + # OpenPose + "https://huggingface.co/yzd-v/DWPose/resolve/main/yolox_l.onnx?download=true": "any/annotators/dwpose/yolox_l.onnx", + "https://huggingface.co/yzd-v/DWPose/resolve/main/dw-ll_ucoco_384.onnx?download=true": "any/annotators/dwpose/dw-ll_ucoco_384.onnx", + # DepthAnything + "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vitl14.pth?download=true": "any/annotators/depth_anything/depth_anything_vitl14.pth", + "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vitb14.pth?download=true": "any/annotators/depth_anything/depth_anything_vitb14.pth", + "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vits14.pth?download=true": "any/annotators/depth_anything/depth_anything_vits14.pth", + # Lama inpaint + "https://github.com/Sanster/models/releases/download/add_big_lama/big-lama.pt": "core/misc/lama/lama.pt", + # RealESRGAN upscale + "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth": "core/upscaling/realesrgan/RealESRGAN_x4plus.pth", + "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth": "core/upscaling/realesrgan/RealESRGAN_x4plus_anime_6B.pth", + "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.1/ESRGAN_SRx4_DF2KOST_official-ff704c30.pth": "core/upscaling/realesrgan/ESRGAN_SRx4_DF2KOST_official-ff704c30.pth", + "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth": "core/upscaling/realesrgan/RealESRGAN_x2plus.pth", +} + + +class Migration10Callback: + def __init__(self, app_config: InvokeAIAppConfig, logger: Logger) -> None: + self._app_config = app_config + self._logger = logger + + def __call__(self, cursor: sqlite3.Cursor) -> None: + self._rename_convert_cache() + self._migrate_downloaded_models_cache() + self._remove_unused_core_models() + + def _rename_convert_cache(self) -> None: + """Rename models/.cache to models/.convert_cache.""" + legacy_convert_path = self._app_config.root_path / "models" / ".cache" + configured_convert_dir = self._app_config.convert_cache_dir + configured_convert_path = self._app_config.convert_cache_path + # old convert dir was in use, and current convert dir has not been changed + if legacy_convert_path.exists() and configured_convert_dir == pathlib.Path("models/.convert_cache"): + self._logger.info( + f"Migrating legacy convert cache directory from {str(legacy_convert_path)} to {str(configured_convert_path)}" + ) + shutil.rmtree(configured_convert_path, ignore_errors=True) # shouldn't be needed, but just in case... + shutil.move(legacy_convert_path, configured_convert_path) + + def _migrate_downloaded_models_cache(self) -> None: + """Move used core models to modsl/.download_cache.""" + self._logger.info(f"Migrating legacy core models to {str(self._app_config.download_cache_path)}") + for url, legacy_dest in LEGACY_CORE_MODELS.items(): + legacy_dest_path = self._app_config.models_path / legacy_dest + if not legacy_dest_path.exists(): + continue + # this returns a unique directory path + new_path = ModelInstallService._download_cache_path(url, self._app_config) + new_path.mkdir(parents=True, exist_ok=True) + shutil.move(legacy_dest_path, new_path / legacy_dest_path.name) + + def _remove_unused_core_models(self) -> None: + """Remove unused core models and their directories.""" + self._logger.info("Removing defunct core models.") + for dir in ["face_restoration", "misc", "upscaling"]: + path_to_remove = self._app_config.models_path / "core" / dir + shutil.rmtree(path_to_remove, ignore_errors=True) + shutil.rmtree(self._app_config.models_path / "any" / "annotators", ignore_errors=True) + + +def build_migration_10(app_config: InvokeAIAppConfig, logger: Logger) -> Migration: + """ + Build the migration from database version 9 to 10. + + This migration does the following: + - Moves "core" models previously downloaded with download_with_progress_bar() into new + "models/.download_cache" directory. + - Renames "models/.cache" to "models/.convert_cache". + """ + migration_10 = Migration( + from_version=9, + to_version=10, + callback=Migration10Callback(app_config=app_config, logger=logger), + ) + + return migration_10 diff --git a/invokeai/app/util/download_with_progress.py b/invokeai/app/util/download_with_progress.py deleted file mode 100644 index 97a2abb2f6..0000000000 --- a/invokeai/app/util/download_with_progress.py +++ /dev/null @@ -1,51 +0,0 @@ -from pathlib import Path -from urllib import request - -from tqdm import tqdm - -from invokeai.backend.util.logging import InvokeAILogger - - -class ProgressBar: - """Simple progress bar for urllib.request.urlretrieve using tqdm.""" - - def __init__(self, model_name: str = "file"): - self.pbar = None - self.name = model_name - - def __call__(self, block_num: int, block_size: int, total_size: int): - if not self.pbar: - self.pbar = tqdm( - desc=self.name, - initial=0, - unit="iB", - unit_scale=True, - unit_divisor=1000, - total=total_size, - ) - self.pbar.update(block_size) - - -def download_with_progress_bar(name: str, url: str, dest_path: Path) -> bool: - """Download a file from a URL to a destination path, with a progress bar. - If the file already exists, it will not be downloaded again. - - Exceptions are not caught. - - Args: - name (str): Name of the file being downloaded. - url (str): URL to download the file from. - dest_path (Path): Destination path to save the file to. - - Returns: - bool: True if the file was downloaded, False if it already existed. - """ - if dest_path.exists(): - return False # already downloaded - - InvokeAILogger.get_logger().info(f"Downloading {name}...") - - dest_path.parent.mkdir(parents=True, exist_ok=True) - request.urlretrieve(url, dest_path, ProgressBar(name)) - - return True diff --git a/tests/app/services/model_load/test_load_api.py b/tests/app/services/model_load/test_load_api.py index b99cc7d824..59b207f2ee 100644 --- a/tests/app/services/model_load/test_load_api.py +++ b/tests/app/services/model_load/test_load_api.py @@ -29,7 +29,7 @@ def test_download_and_cache(mock_context: InvocationContext, mm2_root_dir: Path) assert downloaded_path.is_file() assert downloaded_path.exists() assert downloaded_path.name == "test_embedding.safetensors" - assert downloaded_path.parent.parent == mm2_root_dir / "models/.cache" + assert downloaded_path.parent.parent == mm2_root_dir / "models/.download_cache" downloaded_path_2 = mock_context.models.download_and_cache_ckpt( "https://www.test.foo/download/test_embedding.safetensors" From 34438ce1af2da2a0c879a83e6fe2780a9d49911c Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Wed, 3 Apr 2024 23:26:48 -0400 Subject: [PATCH 006/110] add simplified model manager install API to InvocationContext --- .../app/services/shared/invocation_context.py | 98 ++++++++++++++++++- 1 file changed, 97 insertions(+), 1 deletion(-) diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py index 9994d663e5..176303b055 100644 --- a/invokeai/app/services/shared/invocation_context.py +++ b/invokeai/app/services/shared/invocation_context.py @@ -1,9 +1,10 @@ import threading from dataclasses import dataclass from pathlib import Path -from typing import TYPE_CHECKING, Optional, Union +from typing import TYPE_CHECKING, Any, Dict, Optional, Union from PIL.Image import Image +from pydantic.networks import AnyHttpUrl from torch import Tensor from invokeai.app.invocations.constants import IMAGE_MODES @@ -426,6 +427,101 @@ class ModelsInterface(InvocationContextInterface): model_format=format, ) + def install_model( + self, + source: str, + config: Optional[Dict[str, Any]] = None, + access_token: Optional[str] = None, + inplace: Optional[bool] = False, + timeout: Optional[int] = 0, + ) -> str: + """Install and register a model in the database. + + Args: + source: String source; see below + config: Optional dict. Any fields in this dict + will override corresponding autoassigned probe fields in the + model's config record. + access_token: Optional access token for remote sources. + inplace: If true, installs a local model in place rather than copying + it into the models directory + timeout: How long to wait on install (in seconds). A value of 0 (default) + blocks indefinitely + + The source can be: + 1. A local file path in posix() format (`/foo/bar` or `C:\foo\bar`) + 2. An http or https URL (`https://foo.bar/foo`) + 3. A HuggingFace repo_id (`foo/bar`, `foo/bar:fp16`, `foo/bar:fp16:vae`) + + We extend the HuggingFace repo_id syntax to include the variant and the + subfolder or path. The following are acceptable alternatives: + stabilityai/stable-diffusion-v4 + stabilityai/stable-diffusion-v4:fp16 + stabilityai/stable-diffusion-v4:fp16:vae + stabilityai/stable-diffusion-v4::/checkpoints/sd4.safetensors + stabilityai/stable-diffusion-v4:onnx:vae + + Because a local file path can look like a huggingface repo_id, the logic + first checks whether the path exists on disk, and if not, it is treated as + a parseable huggingface repo. + + Returns: + Key to the newly installed model. + + May Raise: + ValueError -- bad source + UnknownModelException -- remote model not found + InvalidModelException -- what was retrieved from remote is not a model + TimeoutError -- model could not be installed within timeout + Exception -- another error condition + """ + installer = self._services.model_manager.install + job = installer.heuristic_import( + source=source, + config=config, + access_token=access_token, + inplace=inplace, + ) + installer.wait_for_job(job, timeout) + if job.errored: + raise Exception(job.error) + key: str = job.config_out.key + return key + + def download_and_cache_model( + self, + source: Union[str, AnyHttpUrl], + access_token: Optional[str] = None, + timeout: Optional[int] = 0, + ) -> Path: + """Download the model file located at source to the models cache and return its Path. + + This can be used to single-file install models and other resources of arbitrary types + which should not get registered with the database. If the model is already + installed, the cached path will be returned. Otherwise it will be downloaded. + + Args: + source: A URL or a string that can be converted in one. Repo_ids + do not work here. + access_token: Optional access token for restricted resources. + timeout: Wait up to the indicated number of seconds before timing + out long downloads. + + Result: + Path of the downloaded model + + May Raise: + HTTPError + TimeoutError + """ + installer = self._services.model_manager.install + path: Path = installer.download_and_cache( + source=source, + access_token=access_token, + timeout=timeout, + ) + return path + class ConfigInterface(InvocationContextInterface): def get(self) -> InvokeAIAppConfig: From c140d3b1df3fb256f2baf789b7968c6f941b4ef0 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Fri, 12 Apr 2024 00:55:21 -0400 Subject: [PATCH 007/110] add invocation_context.load_ckpt_from_url() method --- invokeai/app/invocations/upscale.py | 13 ++-- .../app/services/shared/invocation_context.py | 67 +++++++++++++++++-- .../image_util/realesrgan/realesrgan.py | 6 +- .../backend/model_manager/load/load_base.py | 2 +- .../model_manager/load/load_default.py | 7 +- .../load/model_cache/model_cache_base.py | 1 - .../load/model_cache/model_cache_default.py | 3 +- .../app/services/model_load/test_load_api.py | 57 ++++++++++++++++ 8 files changed, 131 insertions(+), 25 deletions(-) create mode 100644 tests/app/services/model_load/test_load_api.py diff --git a/invokeai/app/invocations/upscale.py b/invokeai/app/invocations/upscale.py index d687384fcb..e09618960e 100644 --- a/invokeai/app/invocations/upscale.py +++ b/invokeai/app/invocations/upscale.py @@ -1,5 +1,4 @@ # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) & the InvokeAI Team -from pathlib import Path from typing import Literal import cv2 @@ -11,7 +10,6 @@ from pydantic import ConfigDict from invokeai.app.invocations.fields import ImageField from invokeai.app.invocations.primitives import ImageOutput from invokeai.app.services.shared.invocation_context import InvocationContext -from invokeai.app.util.download_with_progress import download_with_progress_bar from invokeai.backend.image_util.basicsr.rrdbnet_arch import RRDBNet from invokeai.backend.image_util.realesrgan.realesrgan import RealESRGAN from invokeai.backend.util.devices import choose_torch_device @@ -56,7 +54,6 @@ class ESRGANInvocation(BaseInvocation, WithMetadata, WithBoard): rrdbnet_model = None netscale = None - esrgan_model_path = None if self.model_name in [ "RealESRGAN_x4plus.pth", @@ -99,16 +96,13 @@ class ESRGANInvocation(BaseInvocation, WithMetadata, WithBoard): context.logger.error(msg) raise ValueError(msg) - esrgan_model_path = Path(context.config.get().models_path, f"core/upscaling/realesrgan/{self.model_name}") - - # Downloads the ESRGAN model if it doesn't already exist - download_with_progress_bar( - name=self.model_name, url=ESRGAN_MODEL_URLS[self.model_name], dest_path=esrgan_model_path + loadnet = context.models.load_ckpt_from_url( + source=ESRGAN_MODEL_URLS[self.model_name], ) upscaler = RealESRGAN( scale=netscale, - model_path=esrgan_model_path, + loadnet=loadnet.model, model=rrdbnet_model, half=False, tile=self.tile_size, @@ -118,6 +112,7 @@ class ESRGANInvocation(BaseInvocation, WithMetadata, WithBoard): # TODO: This strips the alpha... is that okay? cv2_image = cv2.cvtColor(np.array(image.convert("RGB")), cv2.COLOR_RGB2BGR) upscaled_image = upscaler.upscale(cv2_image) + pil_image = Image.fromarray(cv2.cvtColor(upscaled_image, cv2.COLOR_BGR2RGB)).convert("RGBA") torch.cuda.empty_cache() diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py index 176303b055..e97d29d308 100644 --- a/invokeai/app/services/shared/invocation_context.py +++ b/invokeai/app/services/shared/invocation_context.py @@ -1,11 +1,14 @@ import threading from dataclasses import dataclass from pathlib import Path -from typing import TYPE_CHECKING, Any, Dict, Optional, Union +from typing import TYPE_CHECKING, Any, Callable, Dict, Optional, Union +from picklescan.scanner import scan_file_path from PIL.Image import Image from pydantic.networks import AnyHttpUrl +from safetensors.torch import load_file as safetensors_load_file from torch import Tensor +from torch import load as torch_load from invokeai.app.invocations.constants import IMAGE_MODES from invokeai.app.invocations.fields import MetadataField, WithBoard, WithMetadata @@ -488,13 +491,14 @@ class ModelsInterface(InvocationContextInterface): key: str = job.config_out.key return key - def download_and_cache_model( + def download_and_cache_ckpt( self, source: Union[str, AnyHttpUrl], access_token: Optional[str] = None, timeout: Optional[int] = 0, ) -> Path: - """Download the model file located at source to the models cache and return its Path. + """ + Download the model file located at source to the models cache and return its Path. This can be used to single-file install models and other resources of arbitrary types which should not get registered with the database. If the model is already @@ -522,10 +526,65 @@ class ModelsInterface(InvocationContextInterface): ) return path + def load_ckpt_from_url( + self, + source: Union[str, AnyHttpUrl], + access_token: Optional[str] = None, + timeout: Optional[int] = 0, + loader: Optional[Callable[[Path], Dict[str | int, Any]]] = None, + ) -> LoadedModel: + """ + Load and cache the model file located at the indicated URL. + + This will check the model download cache for the model designated + by the provided URL and download it if needed using download_and_cache_model(). + It will then load the model into the RAM cache. If the optional loader + argument is provided, the loader will be invoked to load the model into + memory. Otherwise the method will call safetensors.torch.load_file() or + torch.load() as appropriate to the file suffix. + + Be aware that the LoadedModel object will have a `config` attribute of None. + + Args: + source: A URL or a string that can be converted in one. Repo_ids + do not work here. + access_token: Optional access token for restricted resources. + timeout: Wait up to the indicated number of seconds before timing + out long downloads. + loader: A Callable that expects a Path and returns a Dict[str|int, Any] + + Returns: + A LoadedModel object. + """ + ram_cache = self._services.model_manager.load.ram_cache + try: + return LoadedModel(_locker=ram_cache.get(key=str(source))) + except IndexError: + pass + + def torch_load_file(checkpoint: Path) -> Dict[str | int, Any]: + scan_result = scan_file_path(checkpoint) + if scan_result.infected_files != 0: + raise Exception("The model at {checkpoint} is potentially infected by malware. Aborting load.") + return torch_load(path, map_location="cpu") + + path = self.download_and_cache_ckpt(source, access_token, timeout) + if loader is None: + loader = ( + torch_load_file + if path.suffix.endswith((".ckpt", ".pt", ".pth", ".bin")) + else lambda path: safetensors_load_file(path, device="cpu") + ) + + raw_model = loader(path) + ram_cache.put(key=str(source), model=raw_model) + return LoadedModel(_locker=ram_cache.get(key=str(source))) + class ConfigInterface(InvocationContextInterface): def get(self) -> InvokeAIAppConfig: - """Gets the app's config. + """ + Gets the app's config. Returns: The app's config. diff --git a/invokeai/backend/image_util/realesrgan/realesrgan.py b/invokeai/backend/image_util/realesrgan/realesrgan.py index c06504b608..7c4d90f5bd 100644 --- a/invokeai/backend/image_util/realesrgan/realesrgan.py +++ b/invokeai/backend/image_util/realesrgan/realesrgan.py @@ -1,6 +1,5 @@ import math from enum import Enum -from pathlib import Path from typing import Any, Optional import cv2 @@ -11,6 +10,7 @@ from cv2.typing import MatLike from tqdm import tqdm from invokeai.backend.image_util.basicsr.rrdbnet_arch import RRDBNet +from invokeai.backend.model_manager.config import AnyModel from invokeai.backend.util.devices import choose_torch_device """ @@ -52,7 +52,7 @@ class RealESRGAN: def __init__( self, scale: int, - model_path: Path, + loadnet: AnyModel, model: RRDBNet, tile: int = 0, tile_pad: int = 10, @@ -67,8 +67,6 @@ class RealESRGAN: self.half = half self.device = choose_torch_device() - loadnet = torch.load(model_path, map_location=torch.device("cpu")) - # prefer to use params_ema if "params_ema" in loadnet: keyname = "params_ema" diff --git a/invokeai/backend/model_manager/load/load_base.py b/invokeai/backend/model_manager/load/load_base.py index c336926aea..41a36d7b51 100644 --- a/invokeai/backend/model_manager/load/load_base.py +++ b/invokeai/backend/model_manager/load/load_base.py @@ -23,8 +23,8 @@ from invokeai.backend.model_manager.load.model_cache.model_cache_base import Mod class LoadedModel: """Context manager object that mediates transfer from RAM<->VRAM.""" - config: AnyModelConfig _locker: ModelLockerBase + config: Optional[AnyModelConfig] = None def __enter__(self) -> AnyModel: """Context entry.""" diff --git a/invokeai/backend/model_manager/load/load_default.py b/invokeai/backend/model_manager/load/load_default.py index 6774fc2989..451770c0cb 100644 --- a/invokeai/backend/model_manager/load/load_default.py +++ b/invokeai/backend/model_manager/load/load_default.py @@ -16,7 +16,7 @@ from invokeai.backend.model_manager.config import DiffusersConfigBase, ModelType from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase from invokeai.backend.model_manager.load.load_base import LoadedModel, ModelLoaderBase from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase, ModelLockerBase -from invokeai.backend.model_manager.load.model_util import calc_model_size_by_data, calc_model_size_by_fs +from invokeai.backend.model_manager.load.model_util import calc_model_size_by_fs from invokeai.backend.model_manager.load.optimizations import skip_torch_weight_init from invokeai.backend.util.devices import choose_torch_device, torch_dtype @@ -95,7 +95,6 @@ class ModelLoader(ModelLoaderBase): config.key, submodel_type=submodel_type, model=loaded_model, - size=calc_model_size_by_data(loaded_model), ) return self._ram_cache.get( @@ -126,9 +125,7 @@ class ModelLoader(ModelLoaderBase): if subtype == submodel_type: continue if submodel := getattr(pipeline, subtype.value, None): - self._ram_cache.put( - config.key, submodel_type=subtype, model=submodel, size=calc_model_size_by_data(submodel) - ) + self._ram_cache.put(config.key, submodel_type=subtype, model=submodel) return getattr(pipeline, submodel_type.value) if submodel_type else pipeline def _needs_conversion(self, config: AnyModelConfig, model_path: Path, dest_path: Path) -> bool: diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_base.py b/invokeai/backend/model_manager/load/model_cache/model_cache_base.py index a8c2dd3e92..ec77bbe477 100644 --- a/invokeai/backend/model_manager/load/model_cache/model_cache_base.py +++ b/invokeai/backend/model_manager/load/model_cache/model_cache_base.py @@ -143,7 +143,6 @@ class ModelCacheBase(ABC, Generic[T]): self, key: str, model: T, - size: int, submodel_type: Optional[SubModelType] = None, ) -> None: """Store model under key and optional submodel_type.""" diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py index 2ba52d466c..919a7c4396 100644 --- a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py +++ b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py @@ -30,6 +30,7 @@ import torch from invokeai.backend.model_manager import AnyModel, SubModelType from invokeai.backend.model_manager.load.memory_snapshot import MemorySnapshot, get_pretty_snapshot_diff +from invokeai.backend.model_manager.load.model_util import calc_model_size_by_data from invokeai.backend.util.devices import choose_torch_device from invokeai.backend.util.logging import InvokeAILogger @@ -157,13 +158,13 @@ class ModelCache(ModelCacheBase[AnyModel]): self, key: str, model: AnyModel, - size: int, submodel_type: Optional[SubModelType] = None, ) -> None: """Store model under key and optional submodel_type.""" key = self._make_cache_key(key, submodel_type) if key in self._cached_models: return + size = calc_model_size_by_data(model) self.make_room(size) cache_record = CacheRecord(key, model, size) self._cached_models[key] = cache_record diff --git a/tests/app/services/model_load/test_load_api.py b/tests/app/services/model_load/test_load_api.py new file mode 100644 index 0000000000..b99cc7d824 --- /dev/null +++ b/tests/app/services/model_load/test_load_api.py @@ -0,0 +1,57 @@ +from pathlib import Path + +import pytest + +from invokeai.app.services.invocation_services import InvocationServices +from invokeai.app.services.model_manager import ModelManagerServiceBase +from invokeai.app.services.shared.invocation_context import InvocationContext, build_invocation_context +from invokeai.backend.model_manager.load.load_base import LoadedModel +from tests.backend.model_manager.model_manager_fixtures import * # noqa F403 + + +@pytest.fixture() +def mock_context( + mock_services: InvocationServices, + mm2_model_manager: ModelManagerServiceBase, +) -> InvocationContext: + mock_services.model_manager = mm2_model_manager + return build_invocation_context( + services=mock_services, + data=None, # type: ignore + cancel_event=None, # type: ignore + ) + + +def test_download_and_cache(mock_context: InvocationContext, mm2_root_dir: Path): + downloaded_path = mock_context.models.download_and_cache_ckpt( + "https://www.test.foo/download/test_embedding.safetensors" + ) + assert downloaded_path.is_file() + assert downloaded_path.exists() + assert downloaded_path.name == "test_embedding.safetensors" + assert downloaded_path.parent.parent == mm2_root_dir / "models/.cache" + + downloaded_path_2 = mock_context.models.download_and_cache_ckpt( + "https://www.test.foo/download/test_embedding.safetensors" + ) + assert downloaded_path == downloaded_path_2 + + +def test_download_and_load(mock_context: InvocationContext): + loaded_model_1 = mock_context.models.load_ckpt_from_url("https://www.test.foo/download/test_embedding.safetensors") + assert isinstance(loaded_model_1, LoadedModel) + + loaded_model_2 = mock_context.models.load_ckpt_from_url("https://www.test.foo/download/test_embedding.safetensors") + assert isinstance(loaded_model_2, LoadedModel) + + with loaded_model_1 as model_1, loaded_model_2 as model_2: + assert model_1 == model_2 + assert isinstance(model_1, dict) + + +def test_install_model(mock_context: InvocationContext): + key = mock_context.models.install_model("https://www.test.foo/download/test_embedding.safetensors") + assert key is not None + model = mock_context.models.load(key) + assert model is not None + assert model.config.key == key From 3ead827d61fb3c935e3396d43455c12b6b59018f Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Fri, 12 Apr 2024 21:05:23 -0400 Subject: [PATCH 008/110] port dw_openpose, depth_anything, and lama processors to new model download scheme --- .../controlnet_image_processors.py | 45 ++++++++++--------- invokeai/app/invocations/infill.py | 18 ++++---- .../app/services/shared/invocation_context.py | 4 +- .../image_util/depth_anything/__init__.py | 37 +++++---------- .../image_util/dw_openpose/__init__.py | 5 ++- .../image_util/dw_openpose/wholebody.py | 29 ++++-------- .../backend/image_util/infill_methods/lama.py | 39 +++++++--------- 7 files changed, 72 insertions(+), 105 deletions(-) diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py index a49c910eeb..12a2ae9c96 100644 --- a/invokeai/app/invocations/controlnet_image_processors.py +++ b/invokeai/app/invocations/controlnet_image_processors.py @@ -137,7 +137,7 @@ class ImageProcessorInvocation(BaseInvocation, WithMetadata, WithBoard): image: ImageField = InputField(description="The image to process") - def run_processor(self, image: Image.Image) -> Image.Image: + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: # superclass just passes through image without processing return image @@ -148,7 +148,7 @@ class ImageProcessorInvocation(BaseInvocation, WithMetadata, WithBoard): def invoke(self, context: InvocationContext) -> ImageOutput: raw_image = self.load_image(context) # image type should be PIL.PngImagePlugin.PngImageFile ? - processed_image = self.run_processor(raw_image) + processed_image = self.run_processor(raw_image, context) # currently can't see processed image in node UI without a showImage node, # so for now setting image_type to RESULT instead of INTERMEDIATE so will get saved in gallery @@ -189,7 +189,7 @@ class CannyImageProcessorInvocation(ImageProcessorInvocation): # Keep alpha channel for Canny processing to detect edges of transparent areas return context.images.get_pil(self.image.image_name, "RGBA") - def run_processor(self, image: Image.Image) -> Image.Image: + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: processed_image = get_canny_edges( image, self.low_threshold, @@ -216,7 +216,7 @@ class HedImageProcessorInvocation(ImageProcessorInvocation): # safe: bool = InputField(default=False, description=FieldDescriptions.safe_mode) scribble: bool = InputField(default=False, description=FieldDescriptions.scribble_mode) - def run_processor(self, image: Image.Image) -> Image.Image: + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: hed_processor = HEDProcessor() processed_image = hed_processor.run( image, @@ -243,7 +243,7 @@ class LineartImageProcessorInvocation(ImageProcessorInvocation): image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res) coarse: bool = InputField(default=False, description="Whether to use coarse mode") - def run_processor(self, image: Image.Image) -> Image.Image: + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: lineart_processor = LineartProcessor() processed_image = lineart_processor.run( image, detect_resolution=self.detect_resolution, image_resolution=self.image_resolution, coarse=self.coarse @@ -264,7 +264,7 @@ class LineartAnimeImageProcessorInvocation(ImageProcessorInvocation): detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res) image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res) - def run_processor(self, image: Image.Image) -> Image.Image: + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: processor = LineartAnimeProcessor() processed_image = processor.run( image, @@ -291,7 +291,8 @@ class MidasDepthImageProcessorInvocation(ImageProcessorInvocation): # depth_and_normal not supported in controlnet_aux v0.0.3 # depth_and_normal: bool = InputField(default=False, description="whether to use depth and normal mode") - def run_processor(self, image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + # TODO: replace from_pretrained() calls with context.models.download_and_cache() (or similar) midas_processor = MidasDetector.from_pretrained("lllyasviel/Annotators") processed_image = midas_processor( image, @@ -318,9 +319,9 @@ class NormalbaeImageProcessorInvocation(ImageProcessorInvocation): detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res) image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res) - def run_processor(self, image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: normalbae_processor = NormalBaeDetector.from_pretrained("lllyasviel/Annotators") - processed_image = normalbae_processor( + processed_image: Image.Image = normalbae_processor( image, detect_resolution=self.detect_resolution, image_resolution=self.image_resolution ) return processed_image @@ -337,7 +338,7 @@ class MlsdImageProcessorInvocation(ImageProcessorInvocation): thr_v: float = InputField(default=0.1, ge=0, description="MLSD parameter `thr_v`") thr_d: float = InputField(default=0.1, ge=0, description="MLSD parameter `thr_d`") - def run_processor(self, image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: mlsd_processor = MLSDdetector.from_pretrained("lllyasviel/Annotators") processed_image = mlsd_processor( image, @@ -360,7 +361,7 @@ class PidiImageProcessorInvocation(ImageProcessorInvocation): safe: bool = InputField(default=False, description=FieldDescriptions.safe_mode) scribble: bool = InputField(default=False, description=FieldDescriptions.scribble_mode) - def run_processor(self, image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: pidi_processor = PidiNetDetector.from_pretrained("lllyasviel/Annotators") processed_image = pidi_processor( image, @@ -388,7 +389,7 @@ class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation): w: int = InputField(default=512, ge=0, description="Content shuffle `w` parameter") f: int = InputField(default=256, ge=0, description="Content shuffle `f` parameter") - def run_processor(self, image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: content_shuffle_processor = ContentShuffleDetector() processed_image = content_shuffle_processor( image, @@ -412,7 +413,7 @@ class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation): class ZoeDepthImageProcessorInvocation(ImageProcessorInvocation): """Applies Zoe depth processing to image""" - def run_processor(self, image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: zoe_depth_processor = ZoeDetector.from_pretrained("lllyasviel/Annotators") processed_image = zoe_depth_processor(image) return processed_image @@ -433,7 +434,7 @@ class MediapipeFaceProcessorInvocation(ImageProcessorInvocation): detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res) image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res) - def run_processor(self, image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: mediapipe_face_processor = MediapipeFaceDetector() processed_image = mediapipe_face_processor( image, @@ -461,7 +462,7 @@ class LeresImageProcessorInvocation(ImageProcessorInvocation): detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res) image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res) - def run_processor(self, image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: leres_processor = LeresDetector.from_pretrained("lllyasviel/Annotators") processed_image = leres_processor( image, @@ -503,7 +504,7 @@ class TileResamplerProcessorInvocation(ImageProcessorInvocation): np_img = cv2.resize(np_img, (W, H), interpolation=cv2.INTER_AREA) return np_img - def run_processor(self, img): + def run_processor(self, img: Image.Image, context: InvocationContext) -> Image.Image: np_img = np.array(img, dtype=np.uint8) processed_np_image = self.tile_resample( np_img, @@ -527,7 +528,7 @@ class SegmentAnythingProcessorInvocation(ImageProcessorInvocation): detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res) image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res) - def run_processor(self, image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: # segment_anything_processor = SamDetector.from_pretrained("ybelkada/segment-anything", subfolder="checkpoints") segment_anything_processor = SamDetectorReproducibleColors.from_pretrained( "ybelkada/segment-anything", subfolder="checkpoints" @@ -573,7 +574,7 @@ class ColorMapImageProcessorInvocation(ImageProcessorInvocation): color_map_tile_size: int = InputField(default=64, ge=0, description=FieldDescriptions.tile_size) - def run_processor(self, image: Image.Image): + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: np_image = np.array(image, dtype=np.uint8) height, width = np_image.shape[:2] @@ -608,8 +609,8 @@ class DepthAnythingImageProcessorInvocation(ImageProcessorInvocation): ) resolution: int = InputField(default=512, ge=64, multiple_of=64, description=FieldDescriptions.image_res) - def run_processor(self, image: Image.Image): - depth_anything_detector = DepthAnythingDetector() + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + depth_anything_detector = DepthAnythingDetector(context) depth_anything_detector.load_model(model_size=self.model_size) processed_image = depth_anything_detector(image=image, resolution=self.resolution) @@ -631,8 +632,8 @@ class DWOpenposeImageProcessorInvocation(ImageProcessorInvocation): draw_hands: bool = InputField(default=False) image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res) - def run_processor(self, image: Image.Image): - dw_openpose = DWOpenposeDetector() + def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + dw_openpose = DWOpenposeDetector(context) processed_image = dw_openpose( image, draw_face=self.draw_face, diff --git a/invokeai/app/invocations/infill.py b/invokeai/app/invocations/infill.py index 418bc62fdc..edee275e72 100644 --- a/invokeai/app/invocations/infill.py +++ b/invokeai/app/invocations/infill.py @@ -38,7 +38,7 @@ class InfillImageProcessorInvocation(BaseInvocation, WithMetadata, WithBoard): image: ImageField = InputField(description="The image to process") @abstractmethod - def infill(self, image: Image.Image) -> Image.Image: + def infill(self, image: Image.Image, context: InvocationContext) -> Image.Image: """Infill the image with the specified method""" pass @@ -57,7 +57,7 @@ class InfillImageProcessorInvocation(BaseInvocation, WithMetadata, WithBoard): return ImageOutput.build(context.images.get_dto(self.image.image_name)) # Perform Infill action - infilled_image = self.infill(input_image) + infilled_image = self.infill(input_image, context) # Create ImageDTO for Infilled Image infilled_image_dto = context.images.save(image=infilled_image) @@ -75,7 +75,7 @@ class InfillColorInvocation(InfillImageProcessorInvocation): description="The color to use to infill", ) - def infill(self, image: Image.Image): + def infill(self, image: Image.Image, context: InvocationContext): solid_bg = Image.new("RGBA", image.size, self.color.tuple()) infilled = Image.alpha_composite(solid_bg, image.convert("RGBA")) infilled.paste(image, (0, 0), image.split()[-1]) @@ -94,7 +94,7 @@ class InfillTileInvocation(InfillImageProcessorInvocation): description="The seed to use for tile generation (omit for random)", ) - def infill(self, image: Image.Image): + def infill(self, image: Image.Image, context: InvocationContext): output = infill_tile(image, seed=self.seed, tile_size=self.tile_size) return output.infilled @@ -108,7 +108,7 @@ class InfillPatchMatchInvocation(InfillImageProcessorInvocation): downscale: float = InputField(default=2.0, gt=0, description="Run patchmatch on downscaled image to speedup infill") resample_mode: PIL_RESAMPLING_MODES = InputField(default="bicubic", description="The resampling mode") - def infill(self, image: Image.Image): + def infill(self, image: Image.Image, context: InvocationContext): resample_mode = PIL_RESAMPLING_MAP[self.resample_mode] width = int(image.width / self.downscale) @@ -132,8 +132,8 @@ class InfillPatchMatchInvocation(InfillImageProcessorInvocation): class LaMaInfillInvocation(InfillImageProcessorInvocation): """Infills transparent areas of an image using the LaMa model""" - def infill(self, image: Image.Image): - lama = LaMA() + def infill(self, image: Image.Image, context: InvocationContext): + lama = LaMA(context) return lama(image) @@ -141,7 +141,7 @@ class LaMaInfillInvocation(InfillImageProcessorInvocation): class CV2InfillInvocation(InfillImageProcessorInvocation): """Infills transparent areas of an image using OpenCV Inpainting""" - def infill(self, image: Image.Image): + def infill(self, image: Image.Image, context: InvocationContext): return cv2_inpaint(image) @@ -163,5 +163,5 @@ class MosaicInfillInvocation(InfillImageProcessorInvocation): description="The max threshold for color", ) - def infill(self, image: Image.Image): + def infill(self, image: Image.Image, context: InvocationContext): return infill_mosaic(image, (self.tile_width, self.tile_height), self.min_color.tuple(), self.max_color.tuple()) diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py index e97d29d308..0d27b2520b 100644 --- a/invokeai/app/services/shared/invocation_context.py +++ b/invokeai/app/services/shared/invocation_context.py @@ -534,10 +534,10 @@ class ModelsInterface(InvocationContextInterface): loader: Optional[Callable[[Path], Dict[str | int, Any]]] = None, ) -> LoadedModel: """ - Load and cache the model file located at the indicated URL. + Download, cache, and Load the model file located at the indicated URL. This will check the model download cache for the model designated - by the provided URL and download it if needed using download_and_cache_model(). + by the provided URL and download it if needed using download_and_cache_ckpt(). It will then load the model into the RAM cache. If the optional loader argument is provided, the loader will be invoked to load the model into memory. Otherwise the method will call safetensors.torch.load_file() or diff --git a/invokeai/backend/image_util/depth_anything/__init__.py b/invokeai/backend/image_util/depth_anything/__init__.py index ccac2ba949..560d977b55 100644 --- a/invokeai/backend/image_util/depth_anything/__init__.py +++ b/invokeai/backend/image_util/depth_anything/__init__.py @@ -1,5 +1,4 @@ -import pathlib -from typing import Literal, Union +from typing import Literal, Optional, Union import cv2 import numpy as np @@ -10,7 +9,7 @@ from PIL import Image from torchvision.transforms import Compose from invokeai.app.services.config.config_default import get_config -from invokeai.app.util.download_with_progress import download_with_progress_bar +from invokeai.app.services.shared.invocation_context import InvocationContext from invokeai.backend.image_util.depth_anything.model.dpt import DPT_DINOv2 from invokeai.backend.image_util.depth_anything.utilities.util import NormalizeImage, PrepareForNet, Resize from invokeai.backend.util.devices import choose_torch_device @@ -20,18 +19,9 @@ config = get_config() logger = InvokeAILogger.get_logger(config=config) DEPTH_ANYTHING_MODELS = { - "large": { - "url": "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vitl14.pth?download=true", - "local": "any/annotators/depth_anything/depth_anything_vitl14.pth", - }, - "base": { - "url": "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vitb14.pth?download=true", - "local": "any/annotators/depth_anything/depth_anything_vitb14.pth", - }, - "small": { - "url": "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vits14.pth?download=true", - "local": "any/annotators/depth_anything/depth_anything_vits14.pth", - }, + "large": "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vitl14.pth?download=true", + "base": "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vitb14.pth?download=true", + "small": "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vits14.pth?download=true", } @@ -53,18 +43,14 @@ transform = Compose( class DepthAnythingDetector: - def __init__(self) -> None: - self.model = None + def __init__(self, context: InvocationContext) -> None: + self.context = context + self.model: Optional[DPT_DINOv2] = None self.model_size: Union[Literal["large", "base", "small"], None] = None self.device = choose_torch_device() - def load_model(self, model_size: Literal["large", "base", "small"] = "small"): - DEPTH_ANYTHING_MODEL_PATH = config.models_path / DEPTH_ANYTHING_MODELS[model_size]["local"] - download_with_progress_bar( - pathlib.Path(DEPTH_ANYTHING_MODELS[model_size]["url"]).name, - DEPTH_ANYTHING_MODELS[model_size]["url"], - DEPTH_ANYTHING_MODEL_PATH, - ) + def load_model(self, model_size: Literal["large", "base", "small"] = "small") -> DPT_DINOv2: + depth_anything_model_path = self.context.models.download_and_cache_ckpt(DEPTH_ANYTHING_MODELS[model_size]) if not self.model or model_size != self.model_size: del self.model @@ -78,7 +64,8 @@ class DepthAnythingDetector: case "large": self.model = DPT_DINOv2(encoder="vitl", features=256, out_channels=[256, 512, 1024, 1024]) - self.model.load_state_dict(torch.load(DEPTH_ANYTHING_MODEL_PATH.as_posix(), map_location="cpu")) + assert self.model is not None + self.model.load_state_dict(torch.load(depth_anything_model_path.as_posix(), map_location="cpu")) self.model.eval() self.model.to(choose_torch_device()) diff --git a/invokeai/backend/image_util/dw_openpose/__init__.py b/invokeai/backend/image_util/dw_openpose/__init__.py index c258ef2c78..17ca0233c8 100644 --- a/invokeai/backend/image_util/dw_openpose/__init__.py +++ b/invokeai/backend/image_util/dw_openpose/__init__.py @@ -3,6 +3,7 @@ import torch from controlnet_aux.util import resize_image from PIL import Image +from invokeai.app.services.shared.invocation_context import InvocationContext from invokeai.backend.image_util.dw_openpose.utils import draw_bodypose, draw_facepose, draw_handpose from invokeai.backend.image_util.dw_openpose.wholebody import Wholebody @@ -39,8 +40,8 @@ class DWOpenposeDetector: Credits: https://github.com/IDEA-Research/DWPose """ - def __init__(self) -> None: - self.pose_estimation = Wholebody() + def __init__(self, context: InvocationContext) -> None: + self.pose_estimation = Wholebody(context) def __call__( self, image: Image.Image, draw_face=False, draw_body=True, draw_hands=False, resolution=512 diff --git a/invokeai/backend/image_util/dw_openpose/wholebody.py b/invokeai/backend/image_util/dw_openpose/wholebody.py index 35d340640d..3628b0abd5 100644 --- a/invokeai/backend/image_util/dw_openpose/wholebody.py +++ b/invokeai/backend/image_util/dw_openpose/wholebody.py @@ -4,44 +4,31 @@ import numpy as np import onnxruntime as ort +import torch from invokeai.app.services.config.config_default import get_config -from invokeai.app.util.download_with_progress import download_with_progress_bar +from invokeai.app.services.shared.invocation_context import InvocationContext from invokeai.backend.util.devices import choose_torch_device from .onnxdet import inference_detector from .onnxpose import inference_pose DWPOSE_MODELS = { - "yolox_l.onnx": { - "local": "any/annotators/dwpose/yolox_l.onnx", - "url": "https://huggingface.co/yzd-v/DWPose/resolve/main/yolox_l.onnx?download=true", - }, - "dw-ll_ucoco_384.onnx": { - "local": "any/annotators/dwpose/dw-ll_ucoco_384.onnx", - "url": "https://huggingface.co/yzd-v/DWPose/resolve/main/dw-ll_ucoco_384.onnx?download=true", - }, + "yolox_l.onnx": "https://huggingface.co/yzd-v/DWPose/resolve/main/yolox_l.onnx?download=true", + "dw-ll_ucoco_384.onnx": "https://huggingface.co/yzd-v/DWPose/resolve/main/dw-ll_ucoco_384.onnx?download=true", } config = get_config() class Wholebody: - def __init__(self): + def __init__(self, context: InvocationContext): device = choose_torch_device() - providers = ["CUDAExecutionProvider"] if device == "cuda" else ["CPUExecutionProvider"] + providers = ["CUDAExecutionProvider"] if device == torch.device("cuda") else ["CPUExecutionProvider"] - DET_MODEL_PATH = config.models_path / DWPOSE_MODELS["yolox_l.onnx"]["local"] - download_with_progress_bar("yolox_l.onnx", DWPOSE_MODELS["yolox_l.onnx"]["url"], DET_MODEL_PATH) - - POSE_MODEL_PATH = config.models_path / DWPOSE_MODELS["dw-ll_ucoco_384.onnx"]["local"] - download_with_progress_bar( - "dw-ll_ucoco_384.onnx", DWPOSE_MODELS["dw-ll_ucoco_384.onnx"]["url"], POSE_MODEL_PATH - ) - - onnx_det = DET_MODEL_PATH - onnx_pose = POSE_MODEL_PATH + onnx_det = context.models.download_and_cache_ckpt(DWPOSE_MODELS["yolox_l.onnx"]) + onnx_pose = context.models.download_and_cache_ckpt(DWPOSE_MODELS["dw-ll_ucoco_384.onnx"]) self.session_det = ort.InferenceSession(path_or_bytes=onnx_det, providers=providers) self.session_pose = ort.InferenceSession(path_or_bytes=onnx_pose, providers=providers) diff --git a/invokeai/backend/image_util/infill_methods/lama.py b/invokeai/backend/image_util/infill_methods/lama.py index fa354aeed1..8c3f33efad 100644 --- a/invokeai/backend/image_util/infill_methods/lama.py +++ b/invokeai/backend/image_util/infill_methods/lama.py @@ -1,4 +1,3 @@ -import gc from typing import Any import numpy as np @@ -6,9 +5,7 @@ import torch from PIL import Image import invokeai.backend.util.logging as logger -from invokeai.app.services.config.config_default import get_config -from invokeai.app.util.download_with_progress import download_with_progress_bar -from invokeai.backend.util.devices import choose_torch_device +from invokeai.app.services.shared.invocation_context import InvocationContext def norm_img(np_img): @@ -28,18 +25,14 @@ def load_jit_model(url_or_path, device): class LaMA: + def __init__(self, context: InvocationContext): + self._context = context + def __call__(self, input_image: Image.Image, *args: Any, **kwds: Any) -> Any: - device = choose_torch_device() - model_location = get_config().models_path / "core/misc/lama/lama.pt" - - if not model_location.exists(): - download_with_progress_bar( - name="LaMa Inpainting Model", - url="https://github.com/Sanster/models/releases/download/add_big_lama/big-lama.pt", - dest_path=model_location, - ) - - model = load_jit_model(model_location, device) + loaded_model = self._context.models.load_ckpt_from_url( + source="https://github.com/Sanster/models/releases/download/add_big_lama/big-lama.pt", + loader=lambda path: load_jit_model(path, "cpu"), + ) image = np.asarray(input_image.convert("RGB")) image = norm_img(image) @@ -48,20 +41,18 @@ class LaMA: mask = np.asarray(mask) mask = np.invert(mask) mask = norm_img(mask) - mask = (mask > 0) * 1 - image = torch.from_numpy(image).unsqueeze(0).to(device) - mask = torch.from_numpy(mask).unsqueeze(0).to(device) - with torch.inference_mode(): - infilled_image = model(image, mask) + with loaded_model as model: + device = next(model.buffers()).device + image = torch.from_numpy(image).unsqueeze(0).to(device) + mask = torch.from_numpy(mask).unsqueeze(0).to(device) + + with torch.inference_mode(): + infilled_image = model(image, mask) infilled_image = infilled_image[0].permute(1, 2, 0).detach().cpu().numpy() infilled_image = np.clip(infilled_image * 255, 0, 255).astype("uint8") infilled_image = Image.fromarray(infilled_image) - del model - gc.collect() - torch.cuda.empty_cache() - return infilled_image From fa6efac436a40d1ef890467dd338f78589185828 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Sun, 14 Apr 2024 15:54:46 -0400 Subject: [PATCH 009/110] change names of convert and download caches and add migration script --- .../app/services/config/config_default.py | 9 +- .../model_install/model_install_default.py | 17 +++- .../app/services/shared/sqlite/sqlite_util.py | 2 + .../migrations/migration_10.py | 87 +++++++++++++++++++ invokeai/app/util/download_with_progress.py | 51 ----------- .../app/services/model_load/test_load_api.py | 2 +- 6 files changed, 111 insertions(+), 57 deletions(-) create mode 100644 invokeai/app/services/shared/sqlite_migrator/migrations/migration_10.py delete mode 100644 invokeai/app/util/download_with_progress.py diff --git a/invokeai/app/services/config/config_default.py b/invokeai/app/services/config/config_default.py index f453a56584..4b5a2004be 100644 --- a/invokeai/app/services/config/config_default.py +++ b/invokeai/app/services/config/config_default.py @@ -86,6 +86,7 @@ class InvokeAIAppConfig(BaseSettings): patchmatch: Enable patchmatch inpaint code. models_dir: Path to the models directory. convert_cache_dir: Path to the converted models cache directory. When loading a non-diffusers model, it will be converted and store on disk at this location. + download_cache_dir: Path to the directory that contains dynamically downloaded models. legacy_conf_dir: Path to directory of legacy checkpoint config files. db_dir: Path to InvokeAI databases directory. outputs_dir: Path to directory for outputs. @@ -146,7 +147,8 @@ class InvokeAIAppConfig(BaseSettings): # PATHS models_dir: Path = Field(default=Path("models"), description="Path to the models directory.") - convert_cache_dir: Path = Field(default=Path("models/.cache"), description="Path to the converted models cache directory. When loading a non-diffusers model, it will be converted and store on disk at this location.") + convert_cache_dir: Path = Field(default=Path("models/.convert_cache"), description="Path to the converted models cache directory. When loading a non-diffusers model, it will be converted and store on disk at this location.") + download_cache_dir: Path = Field(default=Path("models/.download_cache"), description="Path to the directory that contains dynamically downloaded models.") legacy_conf_dir: Path = Field(default=Path("configs"), description="Path to directory of legacy checkpoint config files.") db_dir: Path = Field(default=Path("databases"), description="Path to InvokeAI databases directory.") outputs_dir: Path = Field(default=Path("outputs"), description="Path to directory for outputs.") @@ -303,6 +305,11 @@ class InvokeAIAppConfig(BaseSettings): """Path to the converted cache models directory, resolved to an absolute path..""" return self._resolve(self.convert_cache_dir) + @property + def download_cache_path(self) -> Path: + """Path to the downloaded models directory, resolved to an absolute path..""" + return self._resolve(self.download_cache_dir) + @property def custom_nodes_path(self) -> Path: """Path to the custom nodes directory, resolved to an absolute path..""" diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py index 20cfc1c4ff..f1fbcdb7ba 100644 --- a/invokeai/app/services/model_install/model_install_default.py +++ b/invokeai/app/services/model_install/model_install_default.py @@ -393,6 +393,11 @@ class ModelInstallService(ModelInstallServiceBase): rmtree(model_path) self.unregister(key) + @classmethod + def _download_cache_path(cls, source: Union[str, AnyHttpUrl], app_config: InvokeAIAppConfig) -> Path: + model_hash = sha256(str(source).encode("utf-8")).hexdigest()[0:32] + return app_config.download_cache_path / model_hash + def download_and_cache( self, source: Union[str, AnyHttpUrl], @@ -400,8 +405,7 @@ class ModelInstallService(ModelInstallServiceBase): timeout: int = 0, ) -> Path: """Download the model file located at source to the models cache and return its Path.""" - model_hash = sha256(str(source).encode("utf-8")).hexdigest()[0:32] - model_path = self._app_config.convert_cache_path / model_hash + model_path = self._download_cache_path(source, self._app_config) # We expect the cache directory to contain one and only one downloaded file. # We don't know the file's name in advance, as it is set by the download @@ -532,8 +536,13 @@ class ModelInstallService(ModelInstallServiceBase): if resolved_path in installed_model_paths: return True # Skip core models entirely - these aren't registered with the model manager. - if str(resolved_path).startswith(str(self.app_config.models_path / "core")): - return False + for special_directory in [ + self.app_config.models_path / "core", + self.app_config.convert_cache_dir, + self.app_config.download_cache_dir, + ]: + if resolved_path.is_relative_to(special_directory): + return False try: model_id = self.register_path(model_path) self._logger.info(f"Registered {model_path.name} with id {model_id}") diff --git a/invokeai/app/services/shared/sqlite/sqlite_util.py b/invokeai/app/services/shared/sqlite/sqlite_util.py index 1eed0b4409..61f35a3b4e 100644 --- a/invokeai/app/services/shared/sqlite/sqlite_util.py +++ b/invokeai/app/services/shared/sqlite/sqlite_util.py @@ -12,6 +12,7 @@ from invokeai.app.services.shared.sqlite_migrator.migrations.migration_6 import from invokeai.app.services.shared.sqlite_migrator.migrations.migration_7 import build_migration_7 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_8 import build_migration_8 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_9 import build_migration_9 +from invokeai.app.services.shared.sqlite_migrator.migrations.migration_10 import build_migration_10 from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_impl import SqliteMigrator @@ -41,6 +42,7 @@ def init_db(config: InvokeAIAppConfig, logger: Logger, image_files: ImageFileSto migrator.register_migration(build_migration_7()) migrator.register_migration(build_migration_8(app_config=config)) migrator.register_migration(build_migration_9()) + migrator.register_migration(build_migration_10(app_config=config, logger=logger)) migrator.run_migrations() return db diff --git a/invokeai/app/services/shared/sqlite_migrator/migrations/migration_10.py b/invokeai/app/services/shared/sqlite_migrator/migrations/migration_10.py new file mode 100644 index 0000000000..df341a6f2e --- /dev/null +++ b/invokeai/app/services/shared/sqlite_migrator/migrations/migration_10.py @@ -0,0 +1,87 @@ +import pathlib +import shutil +import sqlite3 +from logging import Logger + +from invokeai.app.services.config import InvokeAIAppConfig +from invokeai.app.services.model_install.model_install_default import ModelInstallService +from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_common import Migration + +LEGACY_CORE_MODELS = { + # OpenPose + "https://huggingface.co/yzd-v/DWPose/resolve/main/yolox_l.onnx?download=true": "any/annotators/dwpose/yolox_l.onnx", + "https://huggingface.co/yzd-v/DWPose/resolve/main/dw-ll_ucoco_384.onnx?download=true": "any/annotators/dwpose/dw-ll_ucoco_384.onnx", + # DepthAnything + "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vitl14.pth?download=true": "any/annotators/depth_anything/depth_anything_vitl14.pth", + "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vitb14.pth?download=true": "any/annotators/depth_anything/depth_anything_vitb14.pth", + "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vits14.pth?download=true": "any/annotators/depth_anything/depth_anything_vits14.pth", + # Lama inpaint + "https://github.com/Sanster/models/releases/download/add_big_lama/big-lama.pt": "core/misc/lama/lama.pt", + # RealESRGAN upscale + "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth": "core/upscaling/realesrgan/RealESRGAN_x4plus.pth", + "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth": "core/upscaling/realesrgan/RealESRGAN_x4plus_anime_6B.pth", + "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.1/ESRGAN_SRx4_DF2KOST_official-ff704c30.pth": "core/upscaling/realesrgan/ESRGAN_SRx4_DF2KOST_official-ff704c30.pth", + "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth": "core/upscaling/realesrgan/RealESRGAN_x2plus.pth", +} + + +class Migration10Callback: + def __init__(self, app_config: InvokeAIAppConfig, logger: Logger) -> None: + self._app_config = app_config + self._logger = logger + + def __call__(self, cursor: sqlite3.Cursor) -> None: + self._rename_convert_cache() + self._migrate_downloaded_models_cache() + self._remove_unused_core_models() + + def _rename_convert_cache(self) -> None: + """Rename models/.cache to models/.convert_cache.""" + legacy_convert_path = self._app_config.root_path / "models" / ".cache" + configured_convert_dir = self._app_config.convert_cache_dir + configured_convert_path = self._app_config.convert_cache_path + # old convert dir was in use, and current convert dir has not been changed + if legacy_convert_path.exists() and configured_convert_dir == pathlib.Path("models/.convert_cache"): + self._logger.info( + f"Migrating legacy convert cache directory from {str(legacy_convert_path)} to {str(configured_convert_path)}" + ) + shutil.rmtree(configured_convert_path, ignore_errors=True) # shouldn't be needed, but just in case... + shutil.move(legacy_convert_path, configured_convert_path) + + def _migrate_downloaded_models_cache(self) -> None: + """Move used core models to modsl/.download_cache.""" + self._logger.info(f"Migrating legacy core models to {str(self._app_config.download_cache_path)}") + for url, legacy_dest in LEGACY_CORE_MODELS.items(): + legacy_dest_path = self._app_config.models_path / legacy_dest + if not legacy_dest_path.exists(): + continue + # this returns a unique directory path + new_path = ModelInstallService._download_cache_path(url, self._app_config) + new_path.mkdir(parents=True, exist_ok=True) + shutil.move(legacy_dest_path, new_path / legacy_dest_path.name) + + def _remove_unused_core_models(self) -> None: + """Remove unused core models and their directories.""" + self._logger.info("Removing defunct core models.") + for dir in ["face_restoration", "misc", "upscaling"]: + path_to_remove = self._app_config.models_path / "core" / dir + shutil.rmtree(path_to_remove, ignore_errors=True) + shutil.rmtree(self._app_config.models_path / "any" / "annotators", ignore_errors=True) + + +def build_migration_10(app_config: InvokeAIAppConfig, logger: Logger) -> Migration: + """ + Build the migration from database version 9 to 10. + + This migration does the following: + - Moves "core" models previously downloaded with download_with_progress_bar() into new + "models/.download_cache" directory. + - Renames "models/.cache" to "models/.convert_cache". + """ + migration_10 = Migration( + from_version=9, + to_version=10, + callback=Migration10Callback(app_config=app_config, logger=logger), + ) + + return migration_10 diff --git a/invokeai/app/util/download_with_progress.py b/invokeai/app/util/download_with_progress.py deleted file mode 100644 index 97a2abb2f6..0000000000 --- a/invokeai/app/util/download_with_progress.py +++ /dev/null @@ -1,51 +0,0 @@ -from pathlib import Path -from urllib import request - -from tqdm import tqdm - -from invokeai.backend.util.logging import InvokeAILogger - - -class ProgressBar: - """Simple progress bar for urllib.request.urlretrieve using tqdm.""" - - def __init__(self, model_name: str = "file"): - self.pbar = None - self.name = model_name - - def __call__(self, block_num: int, block_size: int, total_size: int): - if not self.pbar: - self.pbar = tqdm( - desc=self.name, - initial=0, - unit="iB", - unit_scale=True, - unit_divisor=1000, - total=total_size, - ) - self.pbar.update(block_size) - - -def download_with_progress_bar(name: str, url: str, dest_path: Path) -> bool: - """Download a file from a URL to a destination path, with a progress bar. - If the file already exists, it will not be downloaded again. - - Exceptions are not caught. - - Args: - name (str): Name of the file being downloaded. - url (str): URL to download the file from. - dest_path (Path): Destination path to save the file to. - - Returns: - bool: True if the file was downloaded, False if it already existed. - """ - if dest_path.exists(): - return False # already downloaded - - InvokeAILogger.get_logger().info(f"Downloading {name}...") - - dest_path.parent.mkdir(parents=True, exist_ok=True) - request.urlretrieve(url, dest_path, ProgressBar(name)) - - return True diff --git a/tests/app/services/model_load/test_load_api.py b/tests/app/services/model_load/test_load_api.py index b99cc7d824..59b207f2ee 100644 --- a/tests/app/services/model_load/test_load_api.py +++ b/tests/app/services/model_load/test_load_api.py @@ -29,7 +29,7 @@ def test_download_and_cache(mock_context: InvocationContext, mm2_root_dir: Path) assert downloaded_path.is_file() assert downloaded_path.exists() assert downloaded_path.name == "test_embedding.safetensors" - assert downloaded_path.parent.parent == mm2_root_dir / "models/.cache" + assert downloaded_path.parent.parent == mm2_root_dir / "models/.download_cache" downloaded_path_2 = mock_context.models.download_and_cache_ckpt( "https://www.test.foo/download/test_embedding.safetensors" From d72f272f1682763170af3627f7089cbe5a4aee64 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Wed, 24 Apr 2024 23:53:30 -0400 Subject: [PATCH 010/110] Address change requests in first round of PR reviews. Pending: - Move model install calls into model manager and create passthrus in invocation_context. - Consider splitting load_model_from_url() into a call to get the path and a call to load the path. --- invokeai/app/invocations/upscale.py | 28 ++++----- .../model_install/model_install_default.py | 6 +- .../app/services/shared/invocation_context.py | 61 ------------------ .../migrations/migration_10.py | 62 ++++++++----------- .../model_manager/load/load_default.py | 3 +- invokeai/backend/util/util.py | 21 +++++++ .../app/services/model_load/test_load_api.py | 6 -- 7 files changed, 64 insertions(+), 123 deletions(-) diff --git a/invokeai/app/invocations/upscale.py b/invokeai/app/invocations/upscale.py index b8acfcb7bf..29cf7819de 100644 --- a/invokeai/app/invocations/upscale.py +++ b/invokeai/app/invocations/upscale.py @@ -11,7 +11,6 @@ from invokeai.app.invocations.primitives import ImageOutput from invokeai.app.services.shared.invocation_context import InvocationContext from invokeai.backend.image_util.basicsr.rrdbnet_arch import RRDBNet from invokeai.backend.image_util.realesrgan.realesrgan import RealESRGAN -from invokeai.backend.util.devices import TorchDevice from .baseinvocation import BaseInvocation, invocation from .fields import InputField, WithBoard, WithMetadata @@ -96,22 +95,21 @@ class ESRGANInvocation(BaseInvocation, WithMetadata, WithBoard): source=ESRGAN_MODEL_URLS[self.model_name], ) - upscaler = RealESRGAN( - scale=netscale, - loadnet=loadnet.model, - model=rrdbnet_model, - half=False, - tile=self.tile_size, - ) + with loadnet as loadnet_model: + upscaler = RealESRGAN( + scale=netscale, + loadnet=loadnet_model, + model=rrdbnet_model, + half=False, + tile=self.tile_size, + ) - # prepare image - Real-ESRGAN uses cv2 internally, and cv2 uses BGR vs RGB for PIL - # TODO: This strips the alpha... is that okay? - cv2_image = cv2.cvtColor(np.array(image.convert("RGB")), cv2.COLOR_RGB2BGR) - upscaled_image = upscaler.upscale(cv2_image) + # prepare image - Real-ESRGAN uses cv2 internally, and cv2 uses BGR vs RGB for PIL + # TODO: This strips the alpha... is that okay? + cv2_image = cv2.cvtColor(np.array(image.convert("RGB")), cv2.COLOR_RGB2BGR) + upscaled_image = upscaler.upscale(cv2_image) - pil_image = Image.fromarray(cv2.cvtColor(upscaled_image, cv2.COLOR_BGR2RGB)).convert("RGBA") - - TorchDevice.empty_cache() + pil_image = Image.fromarray(cv2.cvtColor(upscaled_image, cv2.COLOR_BGR2RGB)).convert("RGBA") image_dto = context.images.save(image=pil_image) diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py index e259cebace..c4127acf7a 100644 --- a/invokeai/app/services/model_install/model_install_default.py +++ b/invokeai/app/services/model_install/model_install_default.py @@ -6,7 +6,6 @@ import re import signal import threading import time -from hashlib import sha256 from pathlib import Path from queue import Empty, Queue from shutil import copyfile, copytree, move, rmtree @@ -44,6 +43,7 @@ from invokeai.backend.model_manager.probe import ModelProbe from invokeai.backend.model_manager.search import ModelSearch from invokeai.backend.util import InvokeAILogger from invokeai.backend.util.devices import TorchDevice +from invokeai.backend.util.util import slugify from .model_install_base import ( MODEL_SOURCE_TO_TYPE_MAP, @@ -396,8 +396,8 @@ class ModelInstallService(ModelInstallServiceBase): @classmethod def _download_cache_path(cls, source: Union[str, AnyHttpUrl], app_config: InvokeAIAppConfig) -> Path: - model_hash = sha256(str(source).encode("utf-8")).hexdigest()[0:32] - return app_config.download_cache_path / model_hash + escaped_source = slugify(str(source)) + return app_config.download_cache_path / escaped_source def download_and_cache( self, diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py index 0d27b2520b..50551efa31 100644 --- a/invokeai/app/services/shared/invocation_context.py +++ b/invokeai/app/services/shared/invocation_context.py @@ -430,67 +430,6 @@ class ModelsInterface(InvocationContextInterface): model_format=format, ) - def install_model( - self, - source: str, - config: Optional[Dict[str, Any]] = None, - access_token: Optional[str] = None, - inplace: Optional[bool] = False, - timeout: Optional[int] = 0, - ) -> str: - """Install and register a model in the database. - - Args: - source: String source; see below - config: Optional dict. Any fields in this dict - will override corresponding autoassigned probe fields in the - model's config record. - access_token: Optional access token for remote sources. - inplace: If true, installs a local model in place rather than copying - it into the models directory - timeout: How long to wait on install (in seconds). A value of 0 (default) - blocks indefinitely - - The source can be: - 1. A local file path in posix() format (`/foo/bar` or `C:\foo\bar`) - 2. An http or https URL (`https://foo.bar/foo`) - 3. A HuggingFace repo_id (`foo/bar`, `foo/bar:fp16`, `foo/bar:fp16:vae`) - - We extend the HuggingFace repo_id syntax to include the variant and the - subfolder or path. The following are acceptable alternatives: - stabilityai/stable-diffusion-v4 - stabilityai/stable-diffusion-v4:fp16 - stabilityai/stable-diffusion-v4:fp16:vae - stabilityai/stable-diffusion-v4::/checkpoints/sd4.safetensors - stabilityai/stable-diffusion-v4:onnx:vae - - Because a local file path can look like a huggingface repo_id, the logic - first checks whether the path exists on disk, and if not, it is treated as - a parseable huggingface repo. - - Returns: - Key to the newly installed model. - - May Raise: - ValueError -- bad source - UnknownModelException -- remote model not found - InvalidModelException -- what was retrieved from remote is not a model - TimeoutError -- model could not be installed within timeout - Exception -- another error condition - """ - installer = self._services.model_manager.install - job = installer.heuristic_import( - source=source, - config=config, - access_token=access_token, - inplace=inplace, - ) - installer.wait_for_job(job, timeout) - if job.errored: - raise Exception(job.error) - key: str = job.config_out.key - return key - def download_and_cache_ckpt( self, source: Union[str, AnyHttpUrl], diff --git a/invokeai/app/services/shared/sqlite_migrator/migrations/migration_10.py b/invokeai/app/services/shared/sqlite_migrator/migrations/migration_10.py index df341a6f2e..4c4f742d4c 100644 --- a/invokeai/app/services/shared/sqlite_migrator/migrations/migration_10.py +++ b/invokeai/app/services/shared/sqlite_migrator/migrations/migration_10.py @@ -1,28 +1,26 @@ -import pathlib import shutil import sqlite3 from logging import Logger from invokeai.app.services.config import InvokeAIAppConfig -from invokeai.app.services.model_install.model_install_default import ModelInstallService from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_common import Migration -LEGACY_CORE_MODELS = { +LEGACY_CORE_MODELS = [ # OpenPose - "https://huggingface.co/yzd-v/DWPose/resolve/main/yolox_l.onnx?download=true": "any/annotators/dwpose/yolox_l.onnx", - "https://huggingface.co/yzd-v/DWPose/resolve/main/dw-ll_ucoco_384.onnx?download=true": "any/annotators/dwpose/dw-ll_ucoco_384.onnx", + "any/annotators/dwpose/yolox_l.onnx", + "any/annotators/dwpose/dw-ll_ucoco_384.onnx", # DepthAnything - "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vitl14.pth?download=true": "any/annotators/depth_anything/depth_anything_vitl14.pth", - "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vitb14.pth?download=true": "any/annotators/depth_anything/depth_anything_vitb14.pth", - "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vits14.pth?download=true": "any/annotators/depth_anything/depth_anything_vits14.pth", + "any/annotators/depth_anything/depth_anything_vitl14.pth", + "any/annotators/depth_anything/depth_anything_vitb14.pth", + "any/annotators/depth_anything/depth_anything_vits14.pth", # Lama inpaint - "https://github.com/Sanster/models/releases/download/add_big_lama/big-lama.pt": "core/misc/lama/lama.pt", + "core/misc/lama/lama.pt", # RealESRGAN upscale - "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth": "core/upscaling/realesrgan/RealESRGAN_x4plus.pth", - "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth": "core/upscaling/realesrgan/RealESRGAN_x4plus_anime_6B.pth", - "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.1/ESRGAN_SRx4_DF2KOST_official-ff704c30.pth": "core/upscaling/realesrgan/ESRGAN_SRx4_DF2KOST_official-ff704c30.pth", - "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.1/RealESRGAN_x2plus.pth": "core/upscaling/realesrgan/RealESRGAN_x2plus.pth", -} + "core/upscaling/realesrgan/RealESRGAN_x4plus.pth", + "core/upscaling/realesrgan/RealESRGAN_x4plus_anime_6B.pth", + "core/upscaling/realesrgan/ESRGAN_SRx4_DF2KOST_official-ff704c30.pth", + "core/upscaling/realesrgan/RealESRGAN_x2plus.pth", +] class Migration10Callback: @@ -31,34 +29,24 @@ class Migration10Callback: self._logger = logger def __call__(self, cursor: sqlite3.Cursor) -> None: - self._rename_convert_cache() - self._migrate_downloaded_models_cache() + self._remove_convert_cache() + self._remove_downloaded_models() self._remove_unused_core_models() - def _rename_convert_cache(self) -> None: + def _remove_convert_cache(self) -> None: """Rename models/.cache to models/.convert_cache.""" + self._logger.info("Removing .cache directory. Converted models will now be cached in .convert_cache.") legacy_convert_path = self._app_config.root_path / "models" / ".cache" - configured_convert_dir = self._app_config.convert_cache_dir - configured_convert_path = self._app_config.convert_cache_path - # old convert dir was in use, and current convert dir has not been changed - if legacy_convert_path.exists() and configured_convert_dir == pathlib.Path("models/.convert_cache"): - self._logger.info( - f"Migrating legacy convert cache directory from {str(legacy_convert_path)} to {str(configured_convert_path)}" - ) - shutil.rmtree(configured_convert_path, ignore_errors=True) # shouldn't be needed, but just in case... - shutil.move(legacy_convert_path, configured_convert_path) + shutil.rmtree(legacy_convert_path, ignore_errors=True) - def _migrate_downloaded_models_cache(self) -> None: - """Move used core models to modsl/.download_cache.""" - self._logger.info(f"Migrating legacy core models to {str(self._app_config.download_cache_path)}") - for url, legacy_dest in LEGACY_CORE_MODELS.items(): - legacy_dest_path = self._app_config.models_path / legacy_dest - if not legacy_dest_path.exists(): - continue - # this returns a unique directory path - new_path = ModelInstallService._download_cache_path(url, self._app_config) - new_path.mkdir(parents=True, exist_ok=True) - shutil.move(legacy_dest_path, new_path / legacy_dest_path.name) + def _remove_downloaded_models(self) -> None: + """Remove models from their old locations; they will re-download when needed.""" + self._logger.info( + "Removing legacy just-in-time models. Downloaded models will now be cached in .download_cache." + ) + for model_path in LEGACY_CORE_MODELS: + legacy_dest_path = self._app_config.models_path / model_path + legacy_dest_path.unlink(missing_ok=True) def _remove_unused_core_models(self) -> None: """Remove unused core models and their directories.""" diff --git a/invokeai/backend/model_manager/load/load_default.py b/invokeai/backend/model_manager/load/load_default.py index 459808b455..16b9e3646e 100644 --- a/invokeai/backend/model_manager/load/load_default.py +++ b/invokeai/backend/model_manager/load/load_default.py @@ -19,6 +19,7 @@ from invokeai.backend.model_manager.load.model_cache.model_cache_base import Mod from invokeai.backend.model_manager.load.model_util import calc_model_size_by_fs from invokeai.backend.model_manager.load.optimizations import skip_torch_weight_init from invokeai.backend.util.devices import TorchDevice +from invokeai.backend.util.util import slugify # TO DO: The loader is not thread safe! @@ -84,7 +85,7 @@ class ModelLoader(ModelLoaderBase): except IndexError: pass - cache_path: Path = self._convert_cache.cache_path(config.key) + cache_path: Path = self._convert_cache.cache_path(slugify(model_path)) if self._needs_conversion(config, model_path, cache_path): loaded_model = self._do_convert(config, model_path, cache_path, submodel_type) else: diff --git a/invokeai/backend/util/util.py b/invokeai/backend/util/util.py index 7d0d9d03f7..2b2bee3458 100644 --- a/invokeai/backend/util/util.py +++ b/invokeai/backend/util/util.py @@ -1,6 +1,8 @@ import base64 import io import os +import re +import unicodedata import warnings from pathlib import Path @@ -12,6 +14,25 @@ from transformers import logging as transformers_logging GIG = 1073741824 +def slugify(value: str, allow_unicode: bool = False) -> str: + """ + Convert to ASCII if 'allow_unicode' is False. Convert spaces or repeated + dashes to single dashes. Remove characters that aren't alphanumerics, + underscores, or hyphens. Convert to lowercase. Also strip leading and + trailing whitespace, dashes, and underscores. + + Adapted from Django: https://github.com/django/django/blob/main/django/utils/text.py + """ + value = str(value) + if allow_unicode: + value = unicodedata.normalize("NFKC", value) + else: + value = unicodedata.normalize("NFKD", value).encode("ascii", "ignore").decode("ascii") + value = re.sub(r"[/]", "_", value.lower()) + value = re.sub(r"[^\w\s-]", "", value.lower()) + return re.sub(r"[-\s]+", "-", value).strip("-_") + + def directory_size(directory: Path) -> int: """ Return the aggregate size of all files in a directory (bytes). diff --git a/tests/app/services/model_load/test_load_api.py b/tests/app/services/model_load/test_load_api.py index 59b207f2ee..463be86c68 100644 --- a/tests/app/services/model_load/test_load_api.py +++ b/tests/app/services/model_load/test_load_api.py @@ -49,9 +49,3 @@ def test_download_and_load(mock_context: InvocationContext): assert isinstance(model_1, dict) -def test_install_model(mock_context: InvocationContext): - key = mock_context.models.install_model("https://www.test.foo/download/test_embedding.safetensors") - assert key is not None - model = mock_context.models.load(key) - assert model is not None - assert model.config.key == key From 70903ef05760e82a5814c432e6a0b48475eba467 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Sun, 28 Apr 2024 11:33:23 -0400 Subject: [PATCH 011/110] refactor load_ckpt_from_url() --- invokeai/app/invocations/infill.py | 4 +- .../model_install/model_install_base.py | 7 +- .../model_install/model_install_default.py | 4 +- .../services/model_load/model_load_base.py | 27 +++- .../services/model_load/model_load_default.py | 53 +++++++- .../model_manager/model_manager_base.py | 36 ++++++ .../model_manager/model_manager_default.py | 39 +++++- .../app/services/shared/invocation_context.py | 117 ++++++++++-------- .../backend/image_util/infill_methods/lama.py | 16 +-- invokeai/backend/model_manager/config.py | 2 +- .../app/services/model_load/test_load_api.py | 2 - 11 files changed, 235 insertions(+), 72 deletions(-) diff --git a/invokeai/app/invocations/infill.py b/invokeai/app/invocations/infill.py index edee275e72..50fec22994 100644 --- a/invokeai/app/invocations/infill.py +++ b/invokeai/app/invocations/infill.py @@ -133,7 +133,9 @@ class LaMaInfillInvocation(InfillImageProcessorInvocation): """Infills transparent areas of an image using the LaMa model""" def infill(self, image: Image.Image, context: InvocationContext): - lama = LaMA(context) + # Note that this accesses a protected attribute to get to the model manager service. + # Is there a better way? + lama = LaMA(context._services.model_manager) return lama(image) diff --git a/invokeai/app/services/model_install/model_install_base.py b/invokeai/app/services/model_install/model_install_base.py index 0ea901fb46..388f4a5ba2 100644 --- a/invokeai/app/services/model_install/model_install_base.py +++ b/invokeai/app/services/model_install/model_install_base.py @@ -468,7 +468,12 @@ class ModelInstallServiceBase(ABC): """ @abstractmethod - def download_and_cache(self, source: Union[str, AnyHttpUrl], access_token: Optional[str] = None) -> Path: + def download_and_cache_ckpt( + self, + source: str | AnyHttpUrl, + access_token: Optional[str] = None, + timeout: int = 0, + ) -> Path: """ Download the model file located at source to the models cache and return its Path. diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py index c4127acf7a..32c86ad3a3 100644 --- a/invokeai/app/services/model_install/model_install_default.py +++ b/invokeai/app/services/model_install/model_install_default.py @@ -399,9 +399,9 @@ class ModelInstallService(ModelInstallServiceBase): escaped_source = slugify(str(source)) return app_config.download_cache_path / escaped_source - def download_and_cache( + def download_and_cache_ckpt( self, - source: Union[str, AnyHttpUrl], + source: str | AnyHttpUrl, access_token: Optional[str] = None, timeout: int = 0, ) -> Path: diff --git a/invokeai/app/services/model_load/model_load_base.py b/invokeai/app/services/model_load/model_load_base.py index cc80333e93..d59f7a370d 100644 --- a/invokeai/app/services/model_load/model_load_base.py +++ b/invokeai/app/services/model_load/model_load_base.py @@ -2,7 +2,10 @@ """Base class for model loader.""" from abc import ABC, abstractmethod -from typing import Optional +from pathlib import Path +from typing import Callable, Dict, Optional + +from torch import Tensor from invokeai.app.services.shared.invocation_context import InvocationContextData from invokeai.backend.model_manager import AnyModel, AnyModelConfig, SubModelType @@ -38,3 +41,25 @@ class ModelLoadServiceBase(ABC): @abstractmethod def convert_cache(self) -> ModelConvertCacheBase: """Return the checkpoint convert cache used by this loader.""" + + @abstractmethod + def load_ckpt_from_path( + self, model_path: Path, loader: Optional[Callable[[Path], Dict[str, Tensor]]] = None + ) -> LoadedModel: + """ + Load the checkpoint-format model file located at the indicated Path. + + This will load an arbitrary model file into the RAM cache. If the optional loader + argument is provided, the loader will be invoked to load the model into + memory. Otherwise the method will call safetensors.torch.load_file() or + torch.load() as appropriate to the file suffix. + + Be aware that the LoadedModel object will have a `config` attribute of None. + + Args: + model_path: A pathlib.Path to a checkpoint-style models file + loader: A Callable that expects a Path and returns a Dict[str|int, Any] + + Returns: + A LoadedModel object. + """ diff --git a/invokeai/app/services/model_load/model_load_default.py b/invokeai/app/services/model_load/model_load_default.py index 21d3c56f36..a87b6123ce 100644 --- a/invokeai/app/services/model_load/model_load_default.py +++ b/invokeai/app/services/model_load/model_load_default.py @@ -1,7 +1,13 @@ # Copyright (c) 2024 Lincoln D. Stein and the InvokeAI Team """Implementation of model loader service.""" -from typing import Optional, Type +from pathlib import Path +from typing import Callable, Dict, Optional, Type + +from picklescan.scanner import scan_file_path +from safetensors.torch import load_file as safetensors_load_file +from torch import Tensor +from torch import load as torch_load from invokeai.app.services.config import InvokeAIAppConfig from invokeai.app.services.invoker import Invoker @@ -88,6 +94,51 @@ class ModelLoadService(ModelLoadServiceBase): ) return loaded_model + def load_ckpt_from_path( + self, model_path: Path, loader: Optional[Callable[[Path], Dict[str, Tensor]]] = None + ) -> LoadedModel: + """ + Load the checkpoint-format model file located at the indicated Path. + + This will load an arbitrary model file into the RAM cache. If the optional loader + argument is provided, the loader will be invoked to load the model into + memory. Otherwise the method will call safetensors.torch.load_file() or + torch.load() as appropriate to the file suffix. + + Be aware that the LoadedModel object will have a `config` attribute of None. + + Args: + model_path: A pathlib.Path to a checkpoint-style models file + loader: A Callable that expects a Path and returns a Dict[str|int, Any] + + Returns: + A LoadedModel object. + """ + cache_key = str(model_path) + ram_cache = self.ram_cache + try: + return LoadedModel(_locker=ram_cache.get(key=cache_key)) + except IndexError: + pass + + def torch_load_file(checkpoint: Path) -> Dict[str, Tensor]: + scan_result = scan_file_path(checkpoint) + if scan_result.infected_files != 0: + raise Exception("The model at {checkpoint} is potentially infected by malware. Aborting load.") + result: Dict[str, Tensor] = torch_load(checkpoint, map_location="cpu") + return result + + if loader is None: + loader = ( + torch_load_file + if model_path.suffix.endswith((".ckpt", ".pt", ".pth", ".bin")) + else lambda path: safetensors_load_file(path, device="cpu") + ) + + raw_model = loader(model_path) + ram_cache.put(key=cache_key, model=raw_model) + return LoadedModel(_locker=ram_cache.get(key=cache_key)) + def _emit_load_event( self, context_data: InvocationContextData, diff --git a/invokeai/app/services/model_manager/model_manager_base.py b/invokeai/app/services/model_manager/model_manager_base.py index af1b68e1ec..7a5f433aca 100644 --- a/invokeai/app/services/model_manager/model_manager_base.py +++ b/invokeai/app/services/model_manager/model_manager_base.py @@ -1,11 +1,15 @@ # Copyright (c) 2023 Lincoln D. Stein and the InvokeAI Team from abc import ABC, abstractmethod +from pathlib import Path +from typing import Callable, Dict, Optional import torch +from pydantic.networks import AnyHttpUrl from typing_extensions import Self from invokeai.app.services.invoker import Invoker +from invokeai.backend.model_manager.load import LoadedModel from ..config import InvokeAIAppConfig from ..download import DownloadQueueServiceBase @@ -66,3 +70,35 @@ class ModelManagerServiceBase(ABC): @abstractmethod def stop(self, invoker: Invoker) -> None: pass + + @abstractmethod + def load_ckpt_from_url( + self, + source: str | AnyHttpUrl, + access_token: Optional[str] = None, + timeout: Optional[int] = 0, + loader: Optional[Callable[[Path], Dict[str, torch.Tensor]]] = None, + ) -> LoadedModel: + """ + Download, cache, and Load the model file located at the indicated URL. + + This will check the model download cache for the model designated + by the provided URL and download it if needed using download_and_cache_ckpt(). + It will then load the model into the RAM cache. If the optional loader + argument is provided, the loader will be invoked to load the model into + memory. Otherwise the method will call safetensors.torch.load_file() or + torch.load() as appropriate to the file suffix. + + Be aware that the LoadedModel object will have a `config` attribute of None. + + Args: + source: A URL or a string that can be converted in one. Repo_ids + do not work here. + access_token: Optional access token for restricted resources. + timeout: Wait up to the indicated number of seconds before timing + out long downloads. + loader: A Callable that expects a Path and returns a Dict[str|int, Any] + + Returns: + A LoadedModel object. + """ diff --git a/invokeai/app/services/model_manager/model_manager_default.py b/invokeai/app/services/model_manager/model_manager_default.py index 1a2b9a3402..57c409c066 100644 --- a/invokeai/app/services/model_manager/model_manager_default.py +++ b/invokeai/app/services/model_manager/model_manager_default.py @@ -1,13 +1,15 @@ # Copyright (c) 2023 Lincoln D. Stein and the InvokeAI Team """Implementation of ModelManagerServiceBase.""" -from typing import Optional +from pathlib import Path +from typing import Callable, Dict, Optional import torch +from pydantic.networks import AnyHttpUrl from typing_extensions import Self from invokeai.app.services.invoker import Invoker -from invokeai.backend.model_manager.load import ModelCache, ModelConvertCache, ModelLoaderRegistry +from invokeai.backend.model_manager.load import LoadedModel, ModelCache, ModelConvertCache, ModelLoaderRegistry from invokeai.backend.util.devices import TorchDevice from invokeai.backend.util.logging import InvokeAILogger @@ -100,3 +102,36 @@ class ModelManagerService(ModelManagerServiceBase): event_bus=events, ) return cls(store=model_record_service, install=installer, load=loader) + + def load_ckpt_from_url( + self, + source: str | AnyHttpUrl, + access_token: Optional[str] = None, + timeout: Optional[int] = 0, + loader: Optional[Callable[[Path], Dict[str, torch.Tensor]]] = None, + ) -> LoadedModel: + """ + Download, cache, and Load the model file located at the indicated URL. + + This will check the model download cache for the model designated + by the provided URL and download it if needed using download_and_cache_ckpt(). + It will then load the model into the RAM cache. If the optional loader + argument is provided, the loader will be invoked to load the model into + memory. Otherwise the method will call safetensors.torch.load_file() or + torch.load() as appropriate to the file suffix. + + Be aware that the LoadedModel object will have a `config` attribute of None. + + Args: + source: A URL or a string that can be converted in one. Repo_ids + do not work here. + access_token: Optional access token for restricted resources. + timeout: Wait up to the indicated number of seconds before timing + out long downloads. + loader: A Callable that expects a Path and returns a Dict[str|int, Any] + + Returns: + A LoadedModel object. + """ + model_path = self.install.download_and_cache_ckpt(source=source, access_token=access_token, timeout=timeout) + return self.load.load_ckpt_from_path(model_path=model_path, loader=loader) diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py index 50551efa31..485be2ba91 100644 --- a/invokeai/app/services/shared/invocation_context.py +++ b/invokeai/app/services/shared/invocation_context.py @@ -1,14 +1,11 @@ import threading from dataclasses import dataclass from pathlib import Path -from typing import TYPE_CHECKING, Any, Callable, Dict, Optional, Union +from typing import TYPE_CHECKING, Callable, Dict, Optional, Union -from picklescan.scanner import scan_file_path +import torch from PIL.Image import Image from pydantic.networks import AnyHttpUrl -from safetensors.torch import load_file as safetensors_load_file -from torch import Tensor -from torch import load as torch_load from invokeai.app.invocations.constants import IMAGE_MODES from invokeai.app.invocations.fields import MetadataField, WithBoard, WithMetadata @@ -263,7 +260,7 @@ class ImagesInterface(InvocationContextInterface): class TensorsInterface(InvocationContextInterface): - def save(self, tensor: Tensor) -> str: + def save(self, tensor: torch.Tensor) -> str: """Saves a tensor, returning its name. Args: @@ -276,7 +273,7 @@ class TensorsInterface(InvocationContextInterface): name = self._services.tensors.save(obj=tensor) return name - def load(self, name: str) -> Tensor: + def load(self, name: str) -> torch.Tensor: """Loads a tensor by name. Args: @@ -316,8 +313,10 @@ class ConditioningInterface(InvocationContextInterface): class ModelsInterface(InvocationContextInterface): + """Common API for loading, downloading and managing models.""" + def exists(self, identifier: Union[str, "ModelIdentifierField"]) -> bool: - """Checks if a model exists. + """Check if a model exists. Args: identifier: The key or ModelField representing the model. @@ -326,14 +325,18 @@ class ModelsInterface(InvocationContextInterface): True if the model exists, False if not. """ if isinstance(identifier, str): - return self._services.model_manager.store.exists(identifier) - - return self._services.model_manager.store.exists(identifier.key) + # For some reason, Mypy is not getting the type annotations for many of + # the model manager service calls and raises a "returning Any in typed + # context" error. Hence the extra typing hints here and below. + result: bool = self._services.model_manager.store.exists(identifier) + else: + result = self._services.model_manager.store.exists(identifier.key) + return result def load( self, identifier: Union[str, "ModelIdentifierField"], submodel_type: Optional[SubModelType] = None ) -> LoadedModel: - """Loads a model. + """Load a model. Args: identifier: The key or ModelField representing the model. @@ -342,22 +345,22 @@ class ModelsInterface(InvocationContextInterface): Returns: An object representing the loaded model. """ - # The model manager emits events as it loads the model. It needs the context data to build # the event payloads. if isinstance(identifier, str): model = self._services.model_manager.store.get_model(identifier) - return self._services.model_manager.load.load_model(model, submodel_type, self._data) + result: LoadedModel = self._services.model_manager.load.load_model(model, submodel_type, self._data) else: _submodel_type = submodel_type or identifier.submodel_type model = self._services.model_manager.store.get_model(identifier.key) - return self._services.model_manager.load.load_model(model, _submodel_type, self._data) + result = self._services.model_manager.load.load_model(model, _submodel_type, self._data) + return result def load_by_attrs( self, name: str, base: BaseModelType, type: ModelType, submodel_type: Optional[SubModelType] = None ) -> LoadedModel: - """Loads a model by its attributes. + """Load a model by its attributes. Args: name: Name of the model. @@ -369,7 +372,6 @@ class ModelsInterface(InvocationContextInterface): Returns: An object representing the loaded model. """ - configs = self._services.model_manager.store.search_by_attr(model_name=name, base_model=base, model_type=type) if len(configs) == 0: raise UnknownModelException(f"No model found with name {name}, base {base}, and type {type}") @@ -377,10 +379,11 @@ class ModelsInterface(InvocationContextInterface): if len(configs) > 1: raise ValueError(f"More than one model found with name {name}, base {base}, and type {type}") - return self._services.model_manager.load.load_model(configs[0], submodel_type, self._data) + result: LoadedModel = self._services.model_manager.load.load_model(configs[0], submodel_type, self._data) + return result def get_config(self, identifier: Union[str, "ModelIdentifierField"]) -> AnyModelConfig: - """Gets a model's config. + """Get a model's config. Args: identifier: The key or ModelField representing the model. @@ -389,12 +392,13 @@ class ModelsInterface(InvocationContextInterface): The model's config. """ if isinstance(identifier, str): - return self._services.model_manager.store.get_model(identifier) - - return self._services.model_manager.store.get_model(identifier.key) + result: AnyModelConfig = self._services.model_manager.store.get_model(identifier) + else: + result = self._services.model_manager.store.get_model(identifier.key) + return result def search_by_path(self, path: Path) -> list[AnyModelConfig]: - """Searches for models by path. + """Search for models by path. Args: path: The path to search for. @@ -402,7 +406,8 @@ class ModelsInterface(InvocationContextInterface): Returns: A list of models that match the path. """ - return self._services.model_manager.store.search_by_path(path) + result: list[AnyModelConfig] = self._services.model_manager.store.search_by_path(path) + return result def search_by_attrs( self, @@ -411,7 +416,7 @@ class ModelsInterface(InvocationContextInterface): type: Optional[ModelType] = None, format: Optional[ModelFormat] = None, ) -> list[AnyModelConfig]: - """Searches for models by attributes. + """Search for models by attributes. Args: name: The name to search for (exact match). @@ -422,13 +427,13 @@ class ModelsInterface(InvocationContextInterface): Returns: A list of models that match the attributes. """ - - return self._services.model_manager.store.search_by_attr( + result: list[AnyModelConfig] = self._services.model_manager.store.search_by_attr( model_name=name, base_model=base, model_type=type, model_format=format, ) + return result def download_and_cache_ckpt( self, @@ -451,26 +456,49 @@ class ModelsInterface(InvocationContextInterface): out long downloads. Result: - Path of the downloaded model + Path to the downloaded model May Raise: HTTPError TimeoutError """ installer = self._services.model_manager.install - path: Path = installer.download_and_cache( + path: Path = installer.download_and_cache_ckpt( source=source, access_token=access_token, timeout=timeout, ) return path + def load_ckpt_from_path( + self, model_path: Path, loader: Optional[Callable[[Path], Dict[str, torch.Tensor]]] = None + ) -> LoadedModel: + """ + Load the checkpoint-format model file located at the indicated Path. + + This will load an arbitrary model file into the RAM cache. If the optional loader + argument is provided, the loader will be invoked to load the model into + memory. Otherwise the method will call safetensors.torch.load_file() or + torch.load() as appropriate to the file suffix. + + Be aware that the LoadedModel object will have a `config` attribute of None. + + Args: + model_path: A pathlib.Path to a checkpoint-style models file + loader: A Callable that expects a Path and returns a Dict[str|int, Any] + + Returns: + A LoadedModel object. + """ + result: LoadedModel = self._services.model_manager.load.load_ckpt_from_path(model_path, loader=loader) + return result + def load_ckpt_from_url( self, - source: Union[str, AnyHttpUrl], + source: str | AnyHttpUrl, access_token: Optional[str] = None, timeout: Optional[int] = 0, - loader: Optional[Callable[[Path], Dict[str | int, Any]]] = None, + loader: Optional[Callable[[Path], Dict[str, torch.Tensor]]] = None, ) -> LoadedModel: """ Download, cache, and Load the model file located at the indicated URL. @@ -495,29 +523,10 @@ class ModelsInterface(InvocationContextInterface): Returns: A LoadedModel object. """ - ram_cache = self._services.model_manager.load.ram_cache - try: - return LoadedModel(_locker=ram_cache.get(key=str(source))) - except IndexError: - pass - - def torch_load_file(checkpoint: Path) -> Dict[str | int, Any]: - scan_result = scan_file_path(checkpoint) - if scan_result.infected_files != 0: - raise Exception("The model at {checkpoint} is potentially infected by malware. Aborting load.") - return torch_load(path, map_location="cpu") - - path = self.download_and_cache_ckpt(source, access_token, timeout) - if loader is None: - loader = ( - torch_load_file - if path.suffix.endswith((".ckpt", ".pt", ".pth", ".bin")) - else lambda path: safetensors_load_file(path, device="cpu") - ) - - raw_model = loader(path) - ram_cache.put(key=str(source), model=raw_model) - return LoadedModel(_locker=ram_cache.get(key=str(source))) + result: LoadedModel = self._services.model_manager.load_ckpt_from_url( + source=source, access_token=access_token, timeout=timeout, loader=loader + ) + return result class ConfigInterface(InvocationContextInterface): diff --git a/invokeai/backend/image_util/infill_methods/lama.py b/invokeai/backend/image_util/infill_methods/lama.py index 8c3f33efad..c7fea497ca 100644 --- a/invokeai/backend/image_util/infill_methods/lama.py +++ b/invokeai/backend/image_util/infill_methods/lama.py @@ -1,11 +1,13 @@ -from typing import Any +from typing import TYPE_CHECKING, Any import numpy as np import torch from PIL import Image import invokeai.backend.util.logging as logger -from invokeai.app.services.shared.invocation_context import InvocationContext + +if TYPE_CHECKING: + from invokeai.app.services.model_manager import ModelManagerServiceBase def norm_img(np_img): @@ -16,20 +18,20 @@ def norm_img(np_img): return np_img -def load_jit_model(url_or_path, device): +def load_jit_model(url_or_path, device) -> torch.nn.Module: model_path = url_or_path logger.info(f"Loading model from: {model_path}") - model = torch.jit.load(model_path, map_location="cpu").to(device) + model: torch.nn.Module = torch.jit.load(model_path, map_location="cpu").to(device) # type: ignore model.eval() return model class LaMA: - def __init__(self, context: InvocationContext): - self._context = context + def __init__(self, model_manager: "ModelManagerServiceBase"): + self._model_manager = model_manager def __call__(self, input_image: Image.Image, *args: Any, **kwds: Any) -> Any: - loaded_model = self._context.models.load_ckpt_from_url( + loaded_model = self._model_manager.load_ckpt_from_url( source="https://github.com/Sanster/models/releases/download/add_big_lama/big-lama.pt", loader=lambda path: load_jit_model(path, "cpu"), ) diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py index 82f88c0e81..1a5d95b7d8 100644 --- a/invokeai/backend/model_manager/config.py +++ b/invokeai/backend/model_manager/config.py @@ -36,7 +36,7 @@ from ..raw_model import RawModel # ModelMixin is the base class for all diffusers and transformers models # RawModel is the InvokeAI wrapper class for ip_adapters, loras, textual_inversion and onnx runtime -AnyModel = Union[ModelMixin, RawModel, torch.nn.Module] +AnyModel = Union[ModelMixin, RawModel, torch.nn.Module, Dict[str, torch.Tensor]] class InvalidModelConfigException(Exception): diff --git a/tests/app/services/model_load/test_load_api.py b/tests/app/services/model_load/test_load_api.py index 463be86c68..167c2a09df 100644 --- a/tests/app/services/model_load/test_load_api.py +++ b/tests/app/services/model_load/test_load_api.py @@ -47,5 +47,3 @@ def test_download_and_load(mock_context: InvocationContext): with loaded_model_1 as model_1, loaded_model_2 as model_2: assert model_1 == model_2 assert isinstance(model_1, dict) - - From a26667d3ca9110d07507a8466fdc6339f72a36e3 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Sun, 28 Apr 2024 12:24:36 -0400 Subject: [PATCH 012/110] make download and convert cache keys safe for filename length --- .../convert_cache/convert_cache_default.py | 2 ++ .../model_manager/load/load_default.py | 3 +- invokeai/backend/util/util.py | 12 ++++++-- .../app/services/model_load/test_load_api.py | 29 +++++++++++++++---- 4 files changed, 36 insertions(+), 10 deletions(-) diff --git a/invokeai/backend/model_manager/load/convert_cache/convert_cache_default.py b/invokeai/backend/model_manager/load/convert_cache/convert_cache_default.py index 8dc2aff74b..cf6448c056 100644 --- a/invokeai/backend/model_manager/load/convert_cache/convert_cache_default.py +++ b/invokeai/backend/model_manager/load/convert_cache/convert_cache_default.py @@ -7,6 +7,7 @@ from pathlib import Path from invokeai.backend.util import GIG, directory_size from invokeai.backend.util.logging import InvokeAILogger +from invokeai.backend.util.util import safe_filename from .convert_cache_base import ModelConvertCacheBase @@ -35,6 +36,7 @@ class ModelConvertCache(ModelConvertCacheBase): def cache_path(self, key: str) -> Path: """Return the path for a model with the indicated key.""" + key = safe_filename(self._cache_path, key) return self._cache_path / key def make_room(self, size: float) -> None: diff --git a/invokeai/backend/model_manager/load/load_default.py b/invokeai/backend/model_manager/load/load_default.py index 16b9e3646e..a63cc66a86 100644 --- a/invokeai/backend/model_manager/load/load_default.py +++ b/invokeai/backend/model_manager/load/load_default.py @@ -19,7 +19,6 @@ from invokeai.backend.model_manager.load.model_cache.model_cache_base import Mod from invokeai.backend.model_manager.load.model_util import calc_model_size_by_fs from invokeai.backend.model_manager.load.optimizations import skip_torch_weight_init from invokeai.backend.util.devices import TorchDevice -from invokeai.backend.util.util import slugify # TO DO: The loader is not thread safe! @@ -85,7 +84,7 @@ class ModelLoader(ModelLoaderBase): except IndexError: pass - cache_path: Path = self._convert_cache.cache_path(slugify(model_path)) + cache_path: Path = self._convert_cache.cache_path(str(model_path)) if self._needs_conversion(config, model_path, cache_path): loaded_model = self._do_convert(config, model_path, cache_path, submodel_type) else: diff --git a/invokeai/backend/util/util.py b/invokeai/backend/util/util.py index 2b2bee3458..8ffa1ee7df 100644 --- a/invokeai/backend/util/util.py +++ b/invokeai/backend/util/util.py @@ -18,7 +18,8 @@ def slugify(value: str, allow_unicode: bool = False) -> str: """ Convert to ASCII if 'allow_unicode' is False. Convert spaces or repeated dashes to single dashes. Remove characters that aren't alphanumerics, - underscores, or hyphens. Convert to lowercase. Also strip leading and + underscores, or hyphens. Replace slashes with underscores. + Convert to lowercase. Also strip leading and trailing whitespace, dashes, and underscores. Adapted from Django: https://github.com/django/django/blob/main/django/utils/text.py @@ -29,10 +30,17 @@ def slugify(value: str, allow_unicode: bool = False) -> str: else: value = unicodedata.normalize("NFKD", value).encode("ascii", "ignore").decode("ascii") value = re.sub(r"[/]", "_", value.lower()) - value = re.sub(r"[^\w\s-]", "", value.lower()) + value = re.sub(r"[^.\w\s-]", "", value.lower()) return re.sub(r"[-\s]+", "-", value).strip("-_") +def safe_filename(directory: Path, value: str) -> str: + """Make a string safe to use as a filename.""" + escaped_string = slugify(value) + max_name_length = os.pathconf(directory, "PC_NAME_MAX") + return escaped_string[len(escaped_string) - max_name_length :] + + def directory_size(directory: Path) -> int: """ Return the aggregate size of all files in a directory (bytes). diff --git a/tests/app/services/model_load/test_load_api.py b/tests/app/services/model_load/test_load_api.py index 167c2a09df..7eb09fb375 100644 --- a/tests/app/services/model_load/test_load_api.py +++ b/tests/app/services/model_load/test_load_api.py @@ -1,6 +1,7 @@ from pathlib import Path import pytest +import torch from invokeai.app.services.invocation_services import InvocationServices from invokeai.app.services.model_manager import ModelManagerServiceBase @@ -22,7 +23,7 @@ def mock_context( ) -def test_download_and_cache(mock_context: InvocationContext, mm2_root_dir: Path): +def test_download_and_cache(mock_context: InvocationContext, mm2_root_dir: Path) -> None: downloaded_path = mock_context.models.download_and_cache_ckpt( "https://www.test.foo/download/test_embedding.safetensors" ) @@ -37,13 +38,29 @@ def test_download_and_cache(mock_context: InvocationContext, mm2_root_dir: Path) assert downloaded_path == downloaded_path_2 -def test_download_and_load(mock_context: InvocationContext): +def test_load_from_path(mock_context: InvocationContext, embedding_file: Path) -> None: + downloaded_path = mock_context.models.download_and_cache_ckpt( + "https://www.test.foo/download/test_embedding.safetensors" + ) + loaded_model_1 = mock_context.models.load_ckpt_from_path(downloaded_path) + assert isinstance(loaded_model_1, LoadedModel) + + loaded_model_2 = mock_context.models.load_ckpt_from_path(downloaded_path) + assert isinstance(loaded_model_2, LoadedModel) + assert loaded_model_1.model is loaded_model_2.model + + loaded_model_3 = mock_context.models.load_ckpt_from_path(embedding_file) + assert isinstance(loaded_model_3, LoadedModel) + assert loaded_model_1.model is not loaded_model_3.model + assert isinstance(loaded_model_1.model, dict) + assert isinstance(loaded_model_3.model, dict) + assert torch.equal(loaded_model_1.model["emb_params"], loaded_model_3.model["emb_params"]) + + +def test_download_and_load(mock_context: InvocationContext) -> None: loaded_model_1 = mock_context.models.load_ckpt_from_url("https://www.test.foo/download/test_embedding.safetensors") assert isinstance(loaded_model_1, LoadedModel) loaded_model_2 = mock_context.models.load_ckpt_from_url("https://www.test.foo/download/test_embedding.safetensors") assert isinstance(loaded_model_2, LoadedModel) - - with loaded_model_1 as model_1, loaded_model_2 as model_2: - assert model_1 == model_2 - assert isinstance(model_1, dict) + assert loaded_model_1.model is loaded_model_2.model # should be cached copy From 7c39929758a8df48b8bc9973766a5d47a3ee2b1c Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Sun, 28 Apr 2024 13:41:06 -0400 Subject: [PATCH 013/110] support VRAM caching of dict models that lack `to()` --- .../app/services/model_load/model_load_base.py | 2 +- .../services/model_load/model_load_default.py | 2 +- .../app/services/shared/invocation_context.py | 4 ++-- .../load/model_cache/model_cache_default.py | 17 ++++++++--------- .../load/model_cache/model_locker.py | 7 ------- 5 files changed, 12 insertions(+), 20 deletions(-) diff --git a/invokeai/app/services/model_load/model_load_base.py b/invokeai/app/services/model_load/model_load_base.py index d59f7a370d..32fc62fa5b 100644 --- a/invokeai/app/services/model_load/model_load_base.py +++ b/invokeai/app/services/model_load/model_load_base.py @@ -58,7 +58,7 @@ class ModelLoadServiceBase(ABC): Args: model_path: A pathlib.Path to a checkpoint-style models file - loader: A Callable that expects a Path and returns a Dict[str|int, Any] + loader: A Callable that expects a Path and returns a Dict[str, Tensor] Returns: A LoadedModel object. diff --git a/invokeai/app/services/model_load/model_load_default.py b/invokeai/app/services/model_load/model_load_default.py index a87b6123ce..af211c260e 100644 --- a/invokeai/app/services/model_load/model_load_default.py +++ b/invokeai/app/services/model_load/model_load_default.py @@ -109,7 +109,7 @@ class ModelLoadService(ModelLoadServiceBase): Args: model_path: A pathlib.Path to a checkpoint-style models file - loader: A Callable that expects a Path and returns a Dict[str|int, Any] + loader: A Callable that expects a Path and returns a Dict[str, Tensor] Returns: A LoadedModel object. diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py index 485be2ba91..bfdbf1e025 100644 --- a/invokeai/app/services/shared/invocation_context.py +++ b/invokeai/app/services/shared/invocation_context.py @@ -437,7 +437,7 @@ class ModelsInterface(InvocationContextInterface): def download_and_cache_ckpt( self, - source: Union[str, AnyHttpUrl], + source: str | AnyHttpUrl, access_token: Optional[str] = None, timeout: Optional[int] = 0, ) -> Path: @@ -501,7 +501,7 @@ class ModelsInterface(InvocationContextInterface): loader: Optional[Callable[[Path], Dict[str, torch.Tensor]]] = None, ) -> LoadedModel: """ - Download, cache, and Load the model file located at the indicated URL. + Download, cache, and load the model file located at the indicated URL. This will check the model download cache for the model designated by the provided URL and download it if needed using download_and_cache_ckpt(). diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py index 62bb766cd6..bd7b2ffc7a 100644 --- a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py +++ b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py @@ -252,23 +252,22 @@ class ModelCache(ModelCacheBase[AnyModel]): May raise a torch.cuda.OutOfMemoryError """ - # These attributes are not in the base ModelMixin class but in various derived classes. - # Some models don't have these attributes, in which case they run in RAM/CPU. self.logger.debug(f"Called to move {cache_entry.key} to {target_device}") - if not (hasattr(cache_entry.model, "device") and hasattr(cache_entry.model, "to")): - return + model = cache_entry.model - source_device = cache_entry.model.device - - # Note: We compare device types only so that 'cuda' == 'cuda:0'. - # This would need to be revised to support multi-GPU. + source_device = model.device if hasattr(model, "device") else self.storage_device if torch.device(source_device).type == torch.device(target_device).type: return start_model_to_time = time.time() snapshot_before = self._capture_memory_snapshot() try: - cache_entry.model.to(target_device) + if hasattr(model, "to"): + model.to(target_device) + elif isinstance(model, dict): + for _, v in model.items(): + if hasattr(v, "to"): + v.to(target_device) except Exception as e: # blow away cache entry self._delete_cache_entry(cache_entry) raise e diff --git a/invokeai/backend/model_manager/load/model_cache/model_locker.py b/invokeai/backend/model_manager/load/model_cache/model_locker.py index a275987773..e3cb7c8fff 100644 --- a/invokeai/backend/model_manager/load/model_cache/model_locker.py +++ b/invokeai/backend/model_manager/load/model_cache/model_locker.py @@ -29,10 +29,6 @@ class ModelLocker(ModelLockerBase): def lock(self) -> AnyModel: """Move the model into the execution device (GPU) and lock it.""" - if not hasattr(self.model, "to"): - return self.model - - # NOTE that the model has to have the to() method in order for this code to move it into GPU! self._cache_entry.lock() try: if self._cache.lazy_offloading: @@ -55,9 +51,6 @@ class ModelLocker(ModelLockerBase): def unlock(self) -> None: """Call upon exit from context.""" - if not hasattr(self.model, "to"): - return - self._cache_entry.unlock() if not self._cache.lazy_offloading: self._cache.offload_unlocked_models(self._cache_entry.size) From 57c831442e4b41521b6d096d5805c3718a3fd764 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Sun, 28 Apr 2024 14:42:40 -0400 Subject: [PATCH 014/110] fix safe_filename() on windows --- invokeai/backend/util/util.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/invokeai/backend/util/util.py b/invokeai/backend/util/util.py index 8ffa1ee7df..1ee89dcc66 100644 --- a/invokeai/backend/util/util.py +++ b/invokeai/backend/util/util.py @@ -37,7 +37,7 @@ def slugify(value: str, allow_unicode: bool = False) -> str: def safe_filename(directory: Path, value: str) -> str: """Make a string safe to use as a filename.""" escaped_string = slugify(value) - max_name_length = os.pathconf(directory, "PC_NAME_MAX") + max_name_length = os.pathconf(directory, "PC_NAME_MAX") if hasattr(os, "pathconf") else 256 return escaped_string[len(escaped_string) - max_name_length :] From fcb071f30caa5de52ab6e951e39dfbf6bf80e458 Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 29 Apr 2024 08:12:51 +1000 Subject: [PATCH 015/110] feat(backend): lift managed model loading out of lama class --- invokeai/app/invocations/infill.py | 10 +++-- .../backend/image_util/infill_methods/lama.py | 43 ++++++++----------- 2 files changed, 24 insertions(+), 29 deletions(-) diff --git a/invokeai/app/invocations/infill.py b/invokeai/app/invocations/infill.py index 50fec22994..f8358d1df5 100644 --- a/invokeai/app/invocations/infill.py +++ b/invokeai/app/invocations/infill.py @@ -133,10 +133,12 @@ class LaMaInfillInvocation(InfillImageProcessorInvocation): """Infills transparent areas of an image using the LaMa model""" def infill(self, image: Image.Image, context: InvocationContext): - # Note that this accesses a protected attribute to get to the model manager service. - # Is there a better way? - lama = LaMA(context._services.model_manager) - return lama(image) + with context.models.load_ckpt_from_url( + source="https://github.com/Sanster/models/releases/download/add_big_lama/big-lama.pt", + loader=LaMA.load_jit_model, + ) as model: + lama = LaMA(model) + return lama(image) @invocation("infill_cv2", title="CV2 Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.2") diff --git a/invokeai/backend/image_util/infill_methods/lama.py b/invokeai/backend/image_util/infill_methods/lama.py index c7fea497ca..cd5838d1f2 100644 --- a/invokeai/backend/image_util/infill_methods/lama.py +++ b/invokeai/backend/image_util/infill_methods/lama.py @@ -1,13 +1,12 @@ -from typing import TYPE_CHECKING, Any +from pathlib import Path +from typing import Any import numpy as np import torch from PIL import Image import invokeai.backend.util.logging as logger - -if TYPE_CHECKING: - from invokeai.app.services.model_manager import ModelManagerServiceBase +from invokeai.backend.model_manager.config import AnyModel def norm_img(np_img): @@ -18,24 +17,11 @@ def norm_img(np_img): return np_img -def load_jit_model(url_or_path, device) -> torch.nn.Module: - model_path = url_or_path - logger.info(f"Loading model from: {model_path}") - model: torch.nn.Module = torch.jit.load(model_path, map_location="cpu").to(device) # type: ignore - model.eval() - return model - - class LaMA: - def __init__(self, model_manager: "ModelManagerServiceBase"): - self._model_manager = model_manager + def __init__(self, model: AnyModel): + self._model = model def __call__(self, input_image: Image.Image, *args: Any, **kwds: Any) -> Any: - loaded_model = self._model_manager.load_ckpt_from_url( - source="https://github.com/Sanster/models/releases/download/add_big_lama/big-lama.pt", - loader=lambda path: load_jit_model(path, "cpu"), - ) - image = np.asarray(input_image.convert("RGB")) image = norm_img(image) @@ -45,16 +31,23 @@ class LaMA: mask = norm_img(mask) mask = (mask > 0) * 1 - with loaded_model as model: - device = next(model.buffers()).device - image = torch.from_numpy(image).unsqueeze(0).to(device) - mask = torch.from_numpy(mask).unsqueeze(0).to(device) + device = next(self._model.buffers()).device + image = torch.from_numpy(image).unsqueeze(0).to(device) + mask = torch.from_numpy(mask).unsqueeze(0).to(device) - with torch.inference_mode(): - infilled_image = model(image, mask) + with torch.inference_mode(): + infilled_image = self._model(image, mask) infilled_image = infilled_image[0].permute(1, 2, 0).detach().cpu().numpy() infilled_image = np.clip(infilled_image * 255, 0, 255).astype("uint8") infilled_image = Image.fromarray(infilled_image) return infilled_image + + @staticmethod + def load_jit_model(url_or_path: str | Path, device: torch.device | str = "cpu") -> torch.nn.Module: + model_path = url_or_path + logger.info(f"Loading model from: {model_path}") + model: torch.nn.Module = torch.jit.load(model_path, map_location="cpu").to(device) # type: ignore + model.eval() + return model From 1fe90c357cb3f216bd4f2789180911c3520c6505 Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 29 Apr 2024 08:56:00 +1000 Subject: [PATCH 016/110] feat(backend): lift managed model loading out of depthanything class --- .../controlnet_image_processors.py | 16 +++++-- .../image_util/depth_anything/__init__.py | 47 ++++++++----------- 2 files changed, 31 insertions(+), 32 deletions(-) diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py index fd34f18e76..6c647c7ed1 100644 --- a/invokeai/app/invocations/controlnet_image_processors.py +++ b/invokeai/app/invocations/controlnet_image_processors.py @@ -2,6 +2,7 @@ # initial implementation by Gregg Helt, 2023 # heavily leverages controlnet_aux package: https://github.com/patrickvonplaten/controlnet_aux from builtins import bool, float +from pathlib import Path from typing import Dict, List, Literal, Union import cv2 @@ -37,11 +38,12 @@ from invokeai.app.invocations.util import validate_begin_end_step, validate_weig from invokeai.app.services.shared.invocation_context import InvocationContext from invokeai.app.util.controlnet_utils import CONTROLNET_MODE_VALUES, CONTROLNET_RESIZE_VALUES from invokeai.backend.image_util.canny import get_canny_edges -from invokeai.backend.image_util.depth_anything import DepthAnythingDetector +from invokeai.backend.image_util.depth_anything import DEPTH_ANYTHING_MODELS, DepthAnythingDetector from invokeai.backend.image_util.dw_openpose import DWOpenposeDetector from invokeai.backend.image_util.hed import HEDProcessor from invokeai.backend.image_util.lineart import LineartProcessor from invokeai.backend.image_util.lineart_anime import LineartAnimeProcessor +from invokeai.backend.util.devices import TorchDevice from .baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output @@ -603,11 +605,15 @@ class DepthAnythingImageProcessorInvocation(ImageProcessorInvocation): resolution: int = InputField(default=512, ge=64, multiple_of=64, description=FieldDescriptions.image_res) def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: - depth_anything_detector = DepthAnythingDetector(context) - depth_anything_detector.load_model(model_size=self.model_size) + def loader(model_path: Path): + return DepthAnythingDetector.load_model( + model_path, model_size=self.model_size, device=TorchDevice.choose_torch_device() + ) - processed_image = depth_anything_detector(image=image, resolution=self.resolution) - return processed_image + with context.models.load_ckpt_from_url(source=DEPTH_ANYTHING_MODELS[self.model_size], loader=loader) as model: + depth_anything_detector = DepthAnythingDetector(model, TorchDevice.choose_torch_device()) + processed_image = depth_anything_detector(image=image, resolution=self.resolution) + return processed_image @invocation( diff --git a/invokeai/backend/image_util/depth_anything/__init__.py b/invokeai/backend/image_util/depth_anything/__init__.py index 2d88c45485..1adcc6b202 100644 --- a/invokeai/backend/image_util/depth_anything/__init__.py +++ b/invokeai/backend/image_util/depth_anything/__init__.py @@ -1,4 +1,5 @@ -from typing import Literal, Optional, Union +from pathlib import Path +from typing import Literal import cv2 import numpy as np @@ -9,10 +10,8 @@ from PIL import Image from torchvision.transforms import Compose from invokeai.app.services.config.config_default import get_config -from invokeai.app.services.shared.invocation_context import InvocationContext from invokeai.backend.image_util.depth_anything.model.dpt import DPT_DINOv2 from invokeai.backend.image_util.depth_anything.utilities.util import NormalizeImage, PrepareForNet, Resize -from invokeai.backend.util.devices import TorchDevice from invokeai.backend.util.logging import InvokeAILogger config = get_config() @@ -43,33 +42,27 @@ transform = Compose( class DepthAnythingDetector: - def __init__(self, context: InvocationContext) -> None: - self.context = context - self.model: Optional[DPT_DINOv2] = None - self.model_size: Union[Literal["large", "base", "small"], None] = None - self.device = TorchDevice.choose_torch_device() + def __init__(self, model: DPT_DINOv2, device: torch.device) -> None: + self.model = model + self.device = device - def load_model(self, model_size: Literal["large", "base", "small"] = "small") -> DPT_DINOv2: - depth_anything_model_path = self.context.models.download_and_cache_ckpt(DEPTH_ANYTHING_MODELS[model_size]) + @staticmethod + def load_model( + model_path: Path, device: torch.device, model_size: Literal["large", "base", "small"] = "small" + ) -> DPT_DINOv2: + match model_size: + case "small": + model = DPT_DINOv2(encoder="vits", features=64, out_channels=[48, 96, 192, 384]) + case "base": + model = DPT_DINOv2(encoder="vitb", features=128, out_channels=[96, 192, 384, 768]) + case "large": + model = DPT_DINOv2(encoder="vitl", features=256, out_channels=[256, 512, 1024, 1024]) - if not self.model or model_size != self.model_size: - del self.model - self.model_size = model_size + model.load_state_dict(torch.load(model_path.as_posix(), map_location="cpu")) + model.eval() - match self.model_size: - case "small": - self.model = DPT_DINOv2(encoder="vits", features=64, out_channels=[48, 96, 192, 384]) - case "base": - self.model = DPT_DINOv2(encoder="vitb", features=128, out_channels=[96, 192, 384, 768]) - case "large": - self.model = DPT_DINOv2(encoder="vitl", features=256, out_channels=[256, 512, 1024, 1024]) - - assert self.model is not None - self.model.load_state_dict(torch.load(depth_anything_model_path.as_posix(), map_location="cpu")) - self.model.eval() - - self.model.to(self.device) - return self.model + model.to(device) + return model def __call__(self, image: Image.Image, resolution: int = 512) -> Image.Image: if not self.model: From 38df6f37028a8d6cc81055aa35e4ee3e5a716cf7 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Thu, 2 May 2024 21:22:33 -0400 Subject: [PATCH 017/110] fix ruff error --- invokeai/app/invocations/controlnet_image_processors.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py index e9793b9424..267f72ec2b 100644 --- a/invokeai/app/invocations/controlnet_image_processors.py +++ b/invokeai/app/invocations/controlnet_image_processors.py @@ -43,8 +43,8 @@ from invokeai.backend.image_util.dw_openpose import DWOpenposeDetector from invokeai.backend.image_util.hed import HEDProcessor from invokeai.backend.image_util.lineart import LineartProcessor from invokeai.backend.image_util.lineart_anime import LineartAnimeProcessor -from invokeai.backend.util.devices import TorchDevice from invokeai.backend.image_util.util import np_to_pil, pil_to_np +from invokeai.backend.util.devices import TorchDevice from .baseinvocation import BaseInvocation, BaseInvocationOutput, Classification, invocation, invocation_output From e9a20051bd52860298a1b10fac2b40672f855a79 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Fri, 3 May 2024 18:08:53 -0400 Subject: [PATCH 018/110] refactor DWOpenPose and add type hints --- .../controlnet_image_processors.py | 8 +++- .../image_util/dw_openpose/__init__.py | 46 +++++++++++++++---- .../backend/image_util/dw_openpose/utils.py | 8 ++-- .../image_util/dw_openpose/wholebody.py | 13 ++---- 4 files changed, 52 insertions(+), 23 deletions(-) diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py index 267f72ec2b..971179ac93 100644 --- a/invokeai/app/invocations/controlnet_image_processors.py +++ b/invokeai/app/invocations/controlnet_image_processors.py @@ -39,7 +39,7 @@ from invokeai.app.services.shared.invocation_context import InvocationContext from invokeai.app.util.controlnet_utils import CONTROLNET_MODE_VALUES, CONTROLNET_RESIZE_VALUES, heuristic_resize from invokeai.backend.image_util.canny import get_canny_edges from invokeai.backend.image_util.depth_anything import DEPTH_ANYTHING_MODELS, DepthAnythingDetector -from invokeai.backend.image_util.dw_openpose import DWOpenposeDetector +from invokeai.backend.image_util.dw_openpose import DWPOSE_MODELS, DWOpenposeDetector from invokeai.backend.image_util.hed import HEDProcessor from invokeai.backend.image_util.lineart import LineartProcessor from invokeai.backend.image_util.lineart_anime import LineartAnimeProcessor @@ -633,7 +633,11 @@ class DWOpenposeImageProcessorInvocation(ImageProcessorInvocation): image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res) def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: - dw_openpose = DWOpenposeDetector(context) + mm = context.models + onnx_det = mm.download_and_cache_ckpt(DWPOSE_MODELS["yolox_l.onnx"]) + onnx_pose = mm.download_and_cache_ckpt(DWPOSE_MODELS["dw-ll_ucoco_384.onnx"]) + + dw_openpose = DWOpenposeDetector(onnx_det=onnx_det, onnx_pose=onnx_pose) processed_image = dw_openpose( image, draw_face=self.draw_face, diff --git a/invokeai/backend/image_util/dw_openpose/__init__.py b/invokeai/backend/image_util/dw_openpose/__init__.py index 17ca0233c8..cfd3ea4b0d 100644 --- a/invokeai/backend/image_util/dw_openpose/__init__.py +++ b/invokeai/backend/image_util/dw_openpose/__init__.py @@ -1,31 +1,53 @@ +from pathlib import Path +from typing import Dict + import numpy as np import torch from controlnet_aux.util import resize_image from PIL import Image -from invokeai.app.services.shared.invocation_context import InvocationContext -from invokeai.backend.image_util.dw_openpose.utils import draw_bodypose, draw_facepose, draw_handpose +from invokeai.backend.image_util.dw_openpose.utils import NDArrayInt, draw_bodypose, draw_facepose, draw_handpose from invokeai.backend.image_util.dw_openpose.wholebody import Wholebody +DWPOSE_MODELS = { + "yolox_l.onnx": "https://huggingface.co/yzd-v/DWPose/resolve/main/yolox_l.onnx?download=true", + "dw-ll_ucoco_384.onnx": "https://huggingface.co/yzd-v/DWPose/resolve/main/dw-ll_ucoco_384.onnx?download=true", +} -def draw_pose(pose, H, W, draw_face=True, draw_body=True, draw_hands=True, resolution=512): + +def draw_pose( + pose: Dict[str, NDArrayInt | Dict[str, NDArrayInt]], + H: int, + W: int, + draw_face: bool = True, + draw_body: bool = True, + draw_hands: bool = True, + resolution: int = 512, +) -> Image.Image: bodies = pose["bodies"] faces = pose["faces"] hands = pose["hands"] + + assert isinstance(bodies, dict) candidate = bodies["candidate"] + + assert isinstance(bodies, dict) subset = bodies["subset"] + canvas = np.zeros(shape=(H, W, 3), dtype=np.uint8) if draw_body: canvas = draw_bodypose(canvas, candidate, subset) if draw_hands: + assert isinstance(hands, np.ndarray) canvas = draw_handpose(canvas, hands) if draw_face: - canvas = draw_facepose(canvas, faces) + assert isinstance(hands, np.ndarray) + canvas = draw_facepose(canvas, faces) # type: ignore - dwpose_image = resize_image( + dwpose_image: Image.Image = resize_image( canvas, resolution, ) @@ -40,11 +62,16 @@ class DWOpenposeDetector: Credits: https://github.com/IDEA-Research/DWPose """ - def __init__(self, context: InvocationContext) -> None: - self.pose_estimation = Wholebody(context) + def __init__(self, onnx_det: Path, onnx_pose: Path) -> None: + self.pose_estimation = Wholebody(onnx_det=onnx_det, onnx_pose=onnx_pose) def __call__( - self, image: Image.Image, draw_face=False, draw_body=True, draw_hands=False, resolution=512 + self, + image: Image.Image, + draw_face: bool = False, + draw_body: bool = True, + draw_hands: bool = False, + resolution: int = 512, ) -> Image.Image: np_image = np.array(image) H, W, C = np_image.shape @@ -80,3 +107,6 @@ class DWOpenposeDetector: return draw_pose( pose, H, W, draw_face=draw_face, draw_hands=draw_hands, draw_body=draw_body, resolution=resolution ) + + +__all__ = ["DWPOSE_MODELS", "DWOpenposeDetector"] diff --git a/invokeai/backend/image_util/dw_openpose/utils.py b/invokeai/backend/image_util/dw_openpose/utils.py index 428672ab31..dc142dfa71 100644 --- a/invokeai/backend/image_util/dw_openpose/utils.py +++ b/invokeai/backend/image_util/dw_openpose/utils.py @@ -5,11 +5,13 @@ import math import cv2 import matplotlib import numpy as np +import numpy.typing as npt eps = 0.01 +NDArrayInt = npt.NDArray[np.uint8] -def draw_bodypose(canvas, candidate, subset): +def draw_bodypose(canvas: NDArrayInt, candidate: NDArrayInt, subset: NDArrayInt) -> NDArrayInt: H, W, C = canvas.shape candidate = np.array(candidate) subset = np.array(subset) @@ -88,7 +90,7 @@ def draw_bodypose(canvas, candidate, subset): return canvas -def draw_handpose(canvas, all_hand_peaks): +def draw_handpose(canvas: NDArrayInt, all_hand_peaks: NDArrayInt) -> NDArrayInt: H, W, C = canvas.shape edges = [ @@ -142,7 +144,7 @@ def draw_handpose(canvas, all_hand_peaks): return canvas -def draw_facepose(canvas, all_lmks): +def draw_facepose(canvas: NDArrayInt, all_lmks: NDArrayInt) -> NDArrayInt: H, W, C = canvas.shape for lmks in all_lmks: lmks = np.array(lmks) diff --git a/invokeai/backend/image_util/dw_openpose/wholebody.py b/invokeai/backend/image_util/dw_openpose/wholebody.py index 0f66af2c77..3f77f20b9c 100644 --- a/invokeai/backend/image_util/dw_openpose/wholebody.py +++ b/invokeai/backend/image_util/dw_openpose/wholebody.py @@ -2,33 +2,26 @@ # Modified pathing to suit Invoke +from pathlib import Path + import numpy as np import onnxruntime as ort from invokeai.app.services.config.config_default import get_config -from invokeai.app.services.shared.invocation_context import InvocationContext from invokeai.backend.util.devices import TorchDevice from .onnxdet import inference_detector from .onnxpose import inference_pose -DWPOSE_MODELS = { - "yolox_l.onnx": "https://huggingface.co/yzd-v/DWPose/resolve/main/yolox_l.onnx?download=true", - "dw-ll_ucoco_384.onnx": "https://huggingface.co/yzd-v/DWPose/resolve/main/dw-ll_ucoco_384.onnx?download=true", -} - config = get_config() class Wholebody: - def __init__(self, context: InvocationContext): + def __init__(self, onnx_det: Path, onnx_pose: Path): device = TorchDevice.choose_torch_device() providers = ["CUDAExecutionProvider"] if device.type == "cuda" else ["CPUExecutionProvider"] - onnx_det = context.models.download_and_cache_ckpt(DWPOSE_MODELS["yolox_l.onnx"]) - onnx_pose = context.models.download_and_cache_ckpt(DWPOSE_MODELS["dw-ll_ucoco_384.onnx"]) - self.session_det = ort.InferenceSession(path_or_bytes=onnx_det, providers=providers) self.session_pose = ort.InferenceSession(path_or_bytes=onnx_pose, providers=providers) From f211c95dbcd08770e388356cdcd5a0988dadf4fc Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Sun, 5 May 2024 21:00:31 -0400 Subject: [PATCH 019/110] move access token regex matching into download queue --- invokeai/app/api/dependencies.py | 2 +- .../app/services/download/download_default.py | 16 +++++- .../model_install/model_install_default.py | 9 +--- .../model_manager/model_manager_base.py | 5 -- .../model_manager/model_manager_default.py | 7 +-- .../app/services/shared/invocation_context.py | 9 +--- .../services/download/test_download_queue.py | 50 +++++++++++++++++++ 7 files changed, 69 insertions(+), 29 deletions(-) diff --git a/invokeai/app/api/dependencies.py b/invokeai/app/api/dependencies.py index 9a6c7416f6..0cfcf2f3b7 100644 --- a/invokeai/app/api/dependencies.py +++ b/invokeai/app/api/dependencies.py @@ -93,7 +93,7 @@ class ApiDependencies: conditioning = ObjectSerializerForwardCache( ObjectSerializerDisk[ConditioningFieldData](output_folder / "conditioning", ephemeral=True) ) - download_queue_service = DownloadQueueService(event_bus=events) + download_queue_service = DownloadQueueService(app_config=configuration, event_bus=events) model_images_service = ModelImageFileStorageDisk(model_images_folder / "model_images") model_manager = ModelManagerService.build_model_manager( app_config=configuration, diff --git a/invokeai/app/services/download/download_default.py b/invokeai/app/services/download/download_default.py index 7d8229fba1..d9ab2c7f35 100644 --- a/invokeai/app/services/download/download_default.py +++ b/invokeai/app/services/download/download_default.py @@ -15,6 +15,7 @@ from pydantic.networks import AnyHttpUrl from requests import HTTPError from tqdm import tqdm +from invokeai.app.services.config import InvokeAIAppConfig, get_config from invokeai.app.services.events.events_base import EventServiceBase from invokeai.app.util.misc import get_iso_timestamp from invokeai.backend.util.logging import InvokeAILogger @@ -40,15 +41,18 @@ class DownloadQueueService(DownloadQueueServiceBase): def __init__( self, max_parallel_dl: int = 5, + app_config: Optional[InvokeAIAppConfig] = None, event_bus: Optional[EventServiceBase] = None, requests_session: Optional[requests.sessions.Session] = None, ): """ Initialize DownloadQueue. + :param app_config: InvokeAIAppConfig object :param max_parallel_dl: Number of simultaneous downloads allowed [5]. :param requests_session: Optional requests.sessions.Session object, for unit tests. """ + self._app_config = app_config or get_config() self._jobs: Dict[int, DownloadJob] = {} self._next_job_id = 0 self._queue: PriorityQueue[DownloadJob] = PriorityQueue() @@ -139,7 +143,7 @@ class DownloadQueueService(DownloadQueueServiceBase): source=source, dest=dest, priority=priority, - access_token=access_token, + access_token=access_token or self._lookup_access_token(source), ) self.submit_download_job( job, @@ -333,6 +337,16 @@ class DownloadQueueService(DownloadQueueServiceBase): def _in_progress_path(self, path: Path) -> Path: return path.with_name(path.name + ".downloading") + def _lookup_access_token(self, source: AnyHttpUrl) -> Optional[str]: + # Pull the token from config if it exists and matches the URL + print(self._app_config) + token = None + for pair in self._app_config.remote_api_tokens or []: + if re.search(pair.url_regex, str(source)): + token = pair.token + break + return token + def _signal_job_started(self, job: DownloadJob) -> None: job.status = DownloadJobStatus.RUNNING if job.on_start: diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py index 92512baec9..1a08624f8e 100644 --- a/invokeai/app/services/model_install/model_install_default.py +++ b/invokeai/app/services/model_install/model_install_default.py @@ -222,16 +222,9 @@ class ModelInstallService(ModelInstallServiceBase): access_token=access_token, ) elif re.match(r"^https?://[^/]+", source): - # Pull the token from config if it exists and matches the URL - _token = access_token - if _token is None: - for pair in self.app_config.remote_api_tokens or []: - if re.search(pair.url_regex, source): - _token = pair.token - break source_obj = URLModelSource( url=AnyHttpUrl(source), - access_token=_token, + access_token=access_token, ) else: raise ValueError(f"Unsupported model source: '{source}'") diff --git a/invokeai/app/services/model_manager/model_manager_base.py b/invokeai/app/services/model_manager/model_manager_base.py index 7a5f433aca..d16c00302e 100644 --- a/invokeai/app/services/model_manager/model_manager_base.py +++ b/invokeai/app/services/model_manager/model_manager_base.py @@ -75,8 +75,6 @@ class ModelManagerServiceBase(ABC): def load_ckpt_from_url( self, source: str | AnyHttpUrl, - access_token: Optional[str] = None, - timeout: Optional[int] = 0, loader: Optional[Callable[[Path], Dict[str, torch.Tensor]]] = None, ) -> LoadedModel: """ @@ -94,9 +92,6 @@ class ModelManagerServiceBase(ABC): Args: source: A URL or a string that can be converted in one. Repo_ids do not work here. - access_token: Optional access token for restricted resources. - timeout: Wait up to the indicated number of seconds before timing - out long downloads. loader: A Callable that expects a Path and returns a Dict[str|int, Any] Returns: diff --git a/invokeai/app/services/model_manager/model_manager_default.py b/invokeai/app/services/model_manager/model_manager_default.py index 57c409c066..ed274266f3 100644 --- a/invokeai/app/services/model_manager/model_manager_default.py +++ b/invokeai/app/services/model_manager/model_manager_default.py @@ -106,8 +106,6 @@ class ModelManagerService(ModelManagerServiceBase): def load_ckpt_from_url( self, source: str | AnyHttpUrl, - access_token: Optional[str] = None, - timeout: Optional[int] = 0, loader: Optional[Callable[[Path], Dict[str, torch.Tensor]]] = None, ) -> LoadedModel: """ @@ -125,13 +123,10 @@ class ModelManagerService(ModelManagerServiceBase): Args: source: A URL or a string that can be converted in one. Repo_ids do not work here. - access_token: Optional access token for restricted resources. - timeout: Wait up to the indicated number of seconds before timing - out long downloads. loader: A Callable that expects a Path and returns a Dict[str|int, Any] Returns: A LoadedModel object. """ - model_path = self.install.download_and_cache_ckpt(source=source, access_token=access_token, timeout=timeout) + model_path = self.install.download_and_cache_ckpt(source=source) return self.load.load_ckpt_from_path(model_path=model_path, loader=loader) diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py index bfdbf1e025..c7602760f7 100644 --- a/invokeai/app/services/shared/invocation_context.py +++ b/invokeai/app/services/shared/invocation_context.py @@ -496,8 +496,6 @@ class ModelsInterface(InvocationContextInterface): def load_ckpt_from_url( self, source: str | AnyHttpUrl, - access_token: Optional[str] = None, - timeout: Optional[int] = 0, loader: Optional[Callable[[Path], Dict[str, torch.Tensor]]] = None, ) -> LoadedModel: """ @@ -515,17 +513,12 @@ class ModelsInterface(InvocationContextInterface): Args: source: A URL or a string that can be converted in one. Repo_ids do not work here. - access_token: Optional access token for restricted resources. - timeout: Wait up to the indicated number of seconds before timing - out long downloads. loader: A Callable that expects a Path and returns a Dict[str|int, Any] Returns: A LoadedModel object. """ - result: LoadedModel = self._services.model_manager.load_ckpt_from_url( - source=source, access_token=access_token, timeout=timeout, loader=loader - ) + result: LoadedModel = self._services.model_manager.load_ckpt_from_url(source=source, loader=loader) return result diff --git a/tests/app/services/download/test_download_queue.py b/tests/app/services/download/test_download_queue.py index 307238fd61..07c473b183 100644 --- a/tests/app/services/download/test_download_queue.py +++ b/tests/app/services/download/test_download_queue.py @@ -2,14 +2,19 @@ import re import time +from contextlib import contextmanager from pathlib import Path +from typing import Generator import pytest from pydantic.networks import AnyHttpUrl from requests.sessions import Session from requests_testadapter import TestAdapter, TestSession +from invokeai.app.services.config import get_config +from invokeai.app.services.config.config_default import URLRegexTokenPair from invokeai.app.services.download import DownloadJob, DownloadJobStatus, DownloadQueueService +from tests.backend.model_manager.model_manager_fixtures import * # noqa F403 from tests.test_nodes import TestEventService # Prevent pytest deprecation warnings @@ -34,6 +39,17 @@ def session() -> Session: ), ) + sess.mount( + "http://www.huggingface.co/foo.txt", + TestAdapter( + content, + headers={ + "Content-Length": len(content), + "Content-Disposition": 'filename="foo.safetensors"', + }, + ), + ) + # here are some malformed URLs to test # missing the content length sess.mount( @@ -205,3 +221,37 @@ def test_cancel(tmp_path: Path, session: Session) -> None: assert events[-1].event_name == "download_cancelled" assert events[-1].payload["source"] == "http://www.civitai.com/models/12345" queue.stop() + + +@contextmanager +def clear_config() -> Generator[None, None, None]: + try: + yield None + finally: + get_config.cache_clear() + + +def test_tokens(tmp_path: Path, session: Session): + with clear_config(): + config = get_config() + config.remote_api_tokens = [URLRegexTokenPair(url_regex="civitai", token="cv_12345")] + queue = DownloadQueueService(requests_session=session) + queue.start() + # this one has an access token assigned + job1 = queue.download( + source=AnyHttpUrl("http://www.civitai.com/models/12345"), + dest=tmp_path, + ) + # this one doesn't + job2 = queue.download( + source=AnyHttpUrl( + "http://www.huggingface.co/foo.txt", + ), + dest=tmp_path, + ) + queue.join() + # this token is defined in the temporary root invokeai.yaml + # see tests/backend/model_manager/data/invokeai_root/invokeai.yaml + assert job1.access_token == "cv_12345" + assert job2.access_token is None + queue.stop() From b48d4a049deedf0103f47f6d50a3ef0ebe94d165 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Wed, 8 May 2024 21:21:01 -0700 Subject: [PATCH 020/110] bad implementation of diffusers folder download --- .../model_install/model_install_base.py | 16 +++++++++ .../model_install/model_install_default.py | 33 ++++++++++++++----- invokeai/backend/model_manager/config.py | 2 +- .../metadata/fetch/huggingface.py | 2 +- .../model_install/test_model_install.py | 24 ++++++++++++-- 5 files changed, 64 insertions(+), 13 deletions(-) diff --git a/invokeai/app/services/model_install/model_install_base.py b/invokeai/app/services/model_install/model_install_base.py index 388f4a5ba2..ccb8e3772e 100644 --- a/invokeai/app/services/model_install/model_install_base.py +++ b/invokeai/app/services/model_install/model_install_base.py @@ -177,6 +177,7 @@ class ModelInstallJob(BaseModel): ) # internal flags and transitory settings _install_tmpdir: Optional[Path] = PrivateAttr(default=None) + _do_install: Optional[bool] = PrivateAttr(default=True) _exception: Optional[Exception] = PrivateAttr(default=None) def set_error(self, e: Exception) -> None: @@ -407,6 +408,21 @@ class ModelInstallServiceBase(ABC): """ + @abstractmethod + def download_diffusers_model( + self, + source: HFModelSource, + download_to: Path, + ) -> ModelInstallJob: + """ + Download, but do not install, a diffusers model. + + :param source: An HFModelSource object containing a repo_id + :param download_to: Path to directory that will contain the downloaded model. + + Returns: a ModelInstallJob + """ + @abstractmethod def get_job_by_source(self, source: ModelSource) -> List[ModelInstallJob]: """Return the ModelInstallJob(s) corresponding to the provided source.""" diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py index 1a08624f8e..fe932649c4 100644 --- a/invokeai/app/services/model_install/model_install_default.py +++ b/invokeai/app/services/model_install/model_install_default.py @@ -249,6 +249,9 @@ class ModelInstallService(ModelInstallServiceBase): self._install_jobs.append(install_job) return install_job + def download_diffusers_model(self, source: HFModelSource, download_to: Path) -> ModelInstallJob: + return self._import_from_hf(source, download_path=download_to) + def list_jobs(self) -> List[ModelInstallJob]: # noqa D102 return self._install_jobs @@ -641,7 +644,12 @@ class ModelInstallService(ModelInstallServiceBase): inplace=source.inplace or False, ) - def _import_from_hf(self, source: HFModelSource, config: Optional[Dict[str, Any]]) -> ModelInstallJob: + def _import_from_hf( + self, + source: HFModelSource, + config: Optional[Dict[str, Any]] = None, + download_path: Optional[Path] = None, + ) -> ModelInstallJob: # Add user's cached access token to HuggingFace requests source.access_token = source.access_token or HfFolder.get_token() if not source.access_token: @@ -660,9 +668,14 @@ class ModelInstallService(ModelInstallServiceBase): config=config, remote_files=remote_files, metadata=metadata, + download_path=download_path, ) - def _import_from_url(self, source: URLModelSource, config: Optional[Dict[str, Any]]) -> ModelInstallJob: + def _import_from_url( + self, + source: URLModelSource, + config: Optional[Dict[str, Any]], + ) -> ModelInstallJob: # URLs from HuggingFace will be handled specially metadata = None fetcher = None @@ -676,6 +689,7 @@ class ModelInstallService(ModelInstallServiceBase): self._logger.debug(f"metadata={metadata}") if metadata and isinstance(metadata, ModelMetadataWithFiles): remote_files = metadata.download_urls(session=self._session) + print(remote_files) else: remote_files = [RemoteModelFile(url=source.url, path=Path("."), size=0)] return self._import_remote_model( @@ -691,13 +705,14 @@ class ModelInstallService(ModelInstallServiceBase): remote_files: List[RemoteModelFile], metadata: Optional[AnyModelRepoMetadata], config: Optional[Dict[str, Any]], + download_path: Optional[Path] = None, # if defined, download only - don't install! ) -> ModelInstallJob: # TODO: Replace with tempfile.tmpdir() when multithreading is cleaned up. # Currently the tmpdir isn't automatically removed at exit because it is # being held in a daemon thread. if len(remote_files) == 0: raise ValueError(f"{source}: No downloadable files found") - tmpdir = Path( + destdir = download_path or Path( mkdtemp( dir=self._app_config.models_path, prefix=TMPDIR_PREFIX, @@ -708,7 +723,7 @@ class ModelInstallService(ModelInstallServiceBase): source=source, config_in=config or {}, source_metadata=metadata, - local_path=tmpdir, # local path may change once the download has started due to content-disposition handling + local_path=destdir, # local path may change once the download has started due to content-disposition handling bytes=0, total_bytes=0, ) @@ -722,9 +737,10 @@ class ModelInstallService(ModelInstallServiceBase): root = Path(".") subfolder = Path(".") - # we remember the path up to the top of the tmpdir so that it may be + # we remember the path up to the top of the destdir so that it may be # removed safely at the end of the install process. - install_job._install_tmpdir = tmpdir + install_job._install_tmpdir = destdir + install_job._do_install = download_path is None assert install_job.total_bytes is not None # to avoid type checking complaints in the loop below files_string = "file" if len(remote_files) == 1 else "file" @@ -736,7 +752,7 @@ class ModelInstallService(ModelInstallServiceBase): self._logger.debug(f"Downloading {url} => {path}") install_job.total_bytes += model_file.size assert hasattr(source, "access_token") - dest = tmpdir / path.parent + dest = destdir / path.parent dest.mkdir(parents=True, exist_ok=True) download_job = DownloadJob( source=url, @@ -805,7 +821,8 @@ class ModelInstallService(ModelInstallServiceBase): # are there any more active jobs left in this task? if install_job.downloading and all(x.complete for x in install_job.download_parts): self._signal_job_downloads_done(install_job) - self._put_in_queue(install_job) + if install_job._do_install: + self._put_in_queue(install_job) # Let other threads know that the number of downloads has changed self._download_cache.pop(download_job.source, None) diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py index 9e30d96016..e3c99c5644 100644 --- a/invokeai/backend/model_manager/config.py +++ b/invokeai/backend/model_manager/config.py @@ -115,7 +115,7 @@ class SchedulerPredictionType(str, Enum): class ModelRepoVariant(str, Enum): """Various hugging face variants on the diffusers format.""" - Default = "" # model files without "fp16" or other qualifier - empty str + Default = "" # model files without "fp16" or other qualifier FP16 = "fp16" FP32 = "fp32" ONNX = "onnx" diff --git a/invokeai/backend/model_manager/metadata/fetch/huggingface.py b/invokeai/backend/model_manager/metadata/fetch/huggingface.py index 4e3625fdbe..ab78b3e064 100644 --- a/invokeai/backend/model_manager/metadata/fetch/huggingface.py +++ b/invokeai/backend/model_manager/metadata/fetch/huggingface.py @@ -83,7 +83,7 @@ class HuggingFaceMetadataFetch(ModelMetadataFetchBase): assert s.size is not None files.append( RemoteModelFile( - url=hf_hub_url(id, s.rfilename, revision=variant), + url=hf_hub_url(id, s.rfilename, revision=variant or "main"), path=Path(name, s.rfilename), size=s.size, sha256=s.lfs.get("sha256") if s.lfs else None, diff --git a/tests/app/services/model_install/test_model_install.py b/tests/app/services/model_install/test_model_install.py index c755d3c491..ba84455240 100644 --- a/tests/app/services/model_install/test_model_install.py +++ b/tests/app/services/model_install/test_model_install.py @@ -14,6 +14,7 @@ from pydantic_core import Url from invokeai.app.services.config import InvokeAIAppConfig from invokeai.app.services.events.events_base import EventServiceBase from invokeai.app.services.model_install import ( + HFModelSource, InstallStatus, LocalModelSource, ModelInstallJob, @@ -21,7 +22,13 @@ from invokeai.app.services.model_install import ( URLModelSource, ) from invokeai.app.services.model_records import ModelRecordChanges, UnknownModelException -from invokeai.backend.model_manager.config import BaseModelType, InvalidModelConfigException, ModelFormat, ModelType +from invokeai.backend.model_manager.config import ( + BaseModelType, + InvalidModelConfigException, + ModelFormat, + ModelRepoVariant, + ModelType, +) from tests.backend.model_manager.model_manager_fixtures import * # noqa F403 OS = platform.uname().system @@ -247,7 +254,7 @@ def test_simple_download(mm2_installer: ModelInstallServiceBase, mm2_app_config: @pytest.mark.timeout(timeout=20, method="thread") -def test_huggingface_download(mm2_installer: ModelInstallServiceBase, mm2_app_config: InvokeAIAppConfig) -> None: +def test_huggingface_install(mm2_installer: ModelInstallServiceBase, mm2_app_config: InvokeAIAppConfig) -> None: source = URLModelSource(url=Url("https://huggingface.co/stabilityai/sdxl-turbo")) bus = mm2_installer.event_bus @@ -278,6 +285,17 @@ def test_huggingface_download(mm2_installer: ModelInstallServiceBase, mm2_app_co } +@pytest.mark.timeout(timeout=20, method="thread") +def test_huggingface_download(mm2_installer: ModelInstallServiceBase, tmp_path: Path) -> None: + source = HFModelSource(repo_id="stabilityai/sdxl-turbo", variant=ModelRepoVariant.Default) + job = mm2_installer.download_diffusers_model(source, tmp_path) + mm2_installer.wait_for_installs(timeout=5) + print(job.local_path) + assert job.status == InstallStatus.DOWNLOADS_DONE + assert (tmp_path / "sdxl-turbo").exists() + assert (tmp_path / "sdxl-turbo" / "model_index.json").exists() + + def test_404_download(mm2_installer: ModelInstallServiceBase, mm2_app_config: InvokeAIAppConfig) -> None: source = URLModelSource(url=Url("https://test.com/missing_model.safetensors")) job = mm2_installer.import_model(source) @@ -327,7 +345,7 @@ def test_other_error_during_install( }, ], ) -@pytest.mark.timeout(timeout=40, method="thread") +@pytest.mark.timeout(timeout=20, method="thread") def test_heuristic_import_with_type(mm2_installer: ModelInstallServiceBase, model_params: Dict[str, str]): """Test whether or not type is respected on configs when passed to heuristic import.""" assert "name" in model_params and "type" in model_params From 0bf14c2830c915f635dd624bc6816d1f963dcd88 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Sun, 12 May 2024 20:14:00 -0600 Subject: [PATCH 021/110] add multifile_download() method to download service --- invokeai/app/services/download/__init__.py | 9 +- .../app/services/download/download_base.py | 108 +++++++--- .../app/services/download/download_default.py | 201 ++++++++++++++---- .../model_install/model_install_default.py | 1 - .../model_manager/metadata/metadata_base.py | 2 +- .../services/download/test_download_queue.py | 112 +++++++++- 6 files changed, 350 insertions(+), 83 deletions(-) diff --git a/invokeai/app/services/download/__init__.py b/invokeai/app/services/download/__init__.py index 371c531387..33b0025809 100644 --- a/invokeai/app/services/download/__init__.py +++ b/invokeai/app/services/download/__init__.py @@ -1,10 +1,17 @@ """Init file for download queue.""" -from .download_base import DownloadJob, DownloadJobStatus, DownloadQueueServiceBase, UnknownJobIDException +from .download_base import ( + DownloadJob, + DownloadJobStatus, + DownloadQueueServiceBase, + MultiFileDownloadJob, + UnknownJobIDException, +) from .download_default import DownloadQueueService, TqdmProgress __all__ = [ "DownloadJob", + "MultiFileDownloadJob", "DownloadQueueServiceBase", "DownloadQueueService", "TqdmProgress", diff --git a/invokeai/app/services/download/download_base.py b/invokeai/app/services/download/download_base.py index 2ac13b825f..9bb2300eb6 100644 --- a/invokeai/app/services/download/download_base.py +++ b/invokeai/app/services/download/download_base.py @@ -5,11 +5,13 @@ from abc import ABC, abstractmethod from enum import Enum from functools import total_ordering from pathlib import Path -from typing import Any, Callable, List, Optional +from typing import Any, Callable, List, Optional, Set from pydantic import BaseModel, Field, PrivateAttr from pydantic.networks import AnyHttpUrl +from invokeai.backend.model_manager.metadata import RemoteModelFile + class DownloadJobStatus(str, Enum): """State of a download job.""" @@ -33,30 +35,19 @@ class ServiceInactiveException(Exception): """This exception is raised when user attempts to initiate a download before the service is started.""" -DownloadEventHandler = Callable[["DownloadJob"], None] -DownloadExceptionHandler = Callable[["DownloadJob", Optional[Exception]], None] +DownloadEventHandler = Callable[["DownloadJobBase"], None] +DownloadExceptionHandler = Callable[["DownloadJobBase", Optional[Exception]], None] + +MultiFileDownloadEventHandler = Callable[["MultiFileDownloadJob"], None] +MultiFileDownloadExceptionHandler = Callable[["MultiFileDownloadJob", Optional[Exception]], None] -@total_ordering -class DownloadJob(BaseModel): - """Class to monitor and control a model download request.""" +class DownloadJobBase(BaseModel): + """Base of classes to monitor and control downloads.""" - # required variables to be passed in on creation - source: AnyHttpUrl = Field(description="Where to download from. Specific types specified in child classes.") - dest: Path = Field(description="Destination of downloaded model on local disk; a directory or file path") - access_token: Optional[str] = Field(default=None, description="authorization token for protected resources") - # automatically assigned on creation - id: int = Field(description="Numeric ID of this job", default=-1) # default id is a sentinel - priority: int = Field(default=10, description="Queue priority; lower values are higher priority") - - # set internally during download process + dest: Path = Field(description="Initial destination of downloaded model on local disk; a directory or file path") + download_path: Optional[Path] = Field(default=None, description="Final location of downloaded file or directory") status: DownloadJobStatus = Field(default=DownloadJobStatus.WAITING, description="Status of the download") - download_path: Optional[Path] = Field(default=None, description="Final location of downloaded file") - job_started: Optional[str] = Field(default=None, description="Timestamp for when the download job started") - job_ended: Optional[str] = Field( - default=None, description="Timestamp for when the download job ende1d (completed or errored)" - ) - content_type: Optional[str] = Field(default=None, description="Content type of downloaded file") bytes: int = Field(default=0, description="Bytes downloaded so far") total_bytes: int = Field(default=0, description="Total file size (bytes)") @@ -74,14 +65,6 @@ class DownloadJob(BaseModel): _on_cancelled: Optional[DownloadEventHandler] = PrivateAttr(default=None) _on_error: Optional[DownloadExceptionHandler] = PrivateAttr(default=None) - def __hash__(self) -> int: - """Return hash of the string representation of this object, for indexing.""" - return hash(str(self)) - - def __le__(self, other: "DownloadJob") -> bool: - """Return True if this job's priority is less than another's.""" - return self.priority <= other.priority - def cancel(self) -> None: """Call to cancel the job.""" self._cancelled = True @@ -98,6 +81,11 @@ class DownloadJob(BaseModel): """Return true if job completed without errors.""" return self.status == DownloadJobStatus.COMPLETED + @property + def waiting(self) -> bool: + """Return true if the job is waiting to run.""" + return self.status == DownloadJobStatus.WAITING + @property def running(self) -> bool: """Return true if the job is running.""" @@ -154,6 +142,39 @@ class DownloadJob(BaseModel): self._on_cancelled = on_cancelled +@total_ordering +class DownloadJob(DownloadJobBase): + """Class to monitor and control a model download request.""" + + # required variables to be passed in on creation + source: AnyHttpUrl = Field(description="Where to download from. Specific types specified in child classes.") + access_token: Optional[str] = Field(default=None, description="authorization token for protected resources") + # automatically assigned on creation + id: int = Field(description="Numeric ID of this job", default=-1) # default id is a sentinel + priority: int = Field(default=10, description="Queue priority; lower values are higher priority") + + # set internally during download process + job_started: Optional[str] = Field(default=None, description="Timestamp for when the download job started") + job_ended: Optional[str] = Field( + default=None, description="Timestamp for when the download job ende1d (completed or errored)" + ) + content_type: Optional[str] = Field(default=None, description="Content type of downloaded file") + + def __hash__(self) -> int: + """Return hash of the string representation of this object, for indexing.""" + return hash(str(self)) + + def __le__(self, other: "DownloadJob") -> bool: + """Return True if this job's priority is less than another's.""" + return self.priority <= other.priority + + +class MultiFileDownloadJob(DownloadJobBase): + """Class to monitor and control multifile downloads.""" + + download_parts: Set[DownloadJob] = Field(default_factory=set, description="List of download parts.") + + class DownloadQueueServiceBase(ABC): """Multithreaded queue for downloading models via URL.""" @@ -201,6 +222,33 @@ class DownloadQueueServiceBase(ABC): """ pass + @abstractmethod + def multifile_download( + self, + parts: Set[RemoteModelFile], + dest: Path, + access_token: Optional[str] = None, + on_start: Optional[DownloadEventHandler] = None, + on_progress: Optional[DownloadEventHandler] = None, + on_complete: Optional[DownloadEventHandler] = None, + on_cancelled: Optional[DownloadEventHandler] = None, + on_error: Optional[DownloadExceptionHandler] = None, + ) -> MultiFileDownloadJob: + """ + Create and enqueue a multifile download job. + + :param parts: Set of URL / filename pairs + :param dest: Path to download to. See below. + :param on_start, on_progress, on_complete, on_error: Callbacks for the indicated + events. + :returns: A MultiFileDownloadJob object for monitoring the state of the download. + + The `dest` argument is a Path object pointing to a directory. All downloads + with be placed inside this directory. The callbacks will receive the + MultiFileDownloadJob. + """ + pass + @abstractmethod def submit_download_job( self, @@ -262,7 +310,7 @@ class DownloadQueueServiceBase(ABC): pass @abstractmethod - def wait_for_job(self, job: DownloadJob, timeout: int = 0) -> DownloadJob: + def wait_for_job(self, job: DownloadJob | MultiFileDownloadJob, timeout: int = 0) -> DownloadJob: """Wait until the indicated download job has reached a terminal state. This will block until the indicated install job has completed, diff --git a/invokeai/app/services/download/download_default.py b/invokeai/app/services/download/download_default.py index d9ab2c7f35..9ab452c1ef 100644 --- a/invokeai/app/services/download/download_default.py +++ b/invokeai/app/services/download/download_default.py @@ -18,6 +18,7 @@ from tqdm import tqdm from invokeai.app.services.config import InvokeAIAppConfig, get_config from invokeai.app.services.events.events_base import EventServiceBase from invokeai.app.util.misc import get_iso_timestamp +from invokeai.backend.model_manager.metadata import RemoteModelFile from invokeai.backend.util.logging import InvokeAILogger from .download_base import ( @@ -27,6 +28,9 @@ from .download_base import ( DownloadJobCancelledException, DownloadJobStatus, DownloadQueueServiceBase, + MultiFileDownloadEventHandler, + MultiFileDownloadExceptionHandler, + MultiFileDownloadJob, ServiceInactiveException, UnknownJobIDException, ) @@ -54,10 +58,11 @@ class DownloadQueueService(DownloadQueueServiceBase): """ self._app_config = app_config or get_config() self._jobs: Dict[int, DownloadJob] = {} + self._download_part2parent: Dict[AnyHttpUrl, MultiFileDownloadJob] = {} self._next_job_id = 0 self._queue: PriorityQueue[DownloadJob] = PriorityQueue() self._stop_event = threading.Event() - self._job_completed_event = threading.Event() + self._job_terminated_event = threading.Event() self._worker_pool: Set[threading.Thread] = set() self._lock = threading.Lock() self._logger = InvokeAILogger.get_logger("DownloadQueueService") @@ -155,6 +160,49 @@ class DownloadQueueService(DownloadQueueServiceBase): ) return job + def multifile_download( + self, + parts: Set[RemoteModelFile], + dest: Path, + access_token: Optional[str] = None, + on_start: Optional[MultiFileDownloadEventHandler] = None, + on_progress: Optional[MultiFileDownloadEventHandler] = None, + on_complete: Optional[MultiFileDownloadEventHandler] = None, + on_cancelled: Optional[MultiFileDownloadEventHandler] = None, + on_error: Optional[MultiFileDownloadExceptionHandler] = None, + ) -> MultiFileDownloadJob: + mfdj = MultiFileDownloadJob(dest=dest) + mfdj.set_callbacks( + on_start=on_start, + on_progress=on_progress, + on_complete=on_complete, + on_cancelled=on_cancelled, + on_error=on_error, + ) + + for part in parts: + url = part.url + path = dest / part.path + assert path.is_relative_to(dest), "only relative download paths accepted" + job = DownloadJob( + source=url, + dest=path, + access_token=access_token, + ) + mfdj.download_parts.add(job) + self._download_part2parent[job.source] = mfdj + + for download_job in mfdj.download_parts: + self.submit_download_job( + download_job, + on_start=self._mfd_started, + on_progress=self._mfd_progress, + on_complete=self._mfd_complete, + on_cancelled=self._mfd_cancelled, + on_error=self._mfd_error, + ) + return mfdj + def join(self) -> None: """Wait for all jobs to complete.""" self._queue.join() @@ -187,7 +235,7 @@ class DownloadQueueService(DownloadQueueServiceBase): If it is running it will be stopped. job.status will be set to DownloadJobStatus.CANCELLED """ - with self._lock: + if job.status in [DownloadJobStatus.WAITING, DownloadJobStatus.RUNNING]: job.cancel() def cancel_all_jobs(self) -> None: @@ -196,12 +244,12 @@ class DownloadQueueService(DownloadQueueServiceBase): if not job.in_terminal_state: self.cancel_job(job) - def wait_for_job(self, job: DownloadJob, timeout: int = 0) -> DownloadJob: + def wait_for_job(self, job: DownloadJob | MultiFileDownloadJob, timeout: int = 0) -> DownloadJob: """Block until the indicated job has reached terminal state, or when timeout limit reached.""" start = time.time() while not job.in_terminal_state: - if self._job_completed_event.wait(timeout=0.25): # in case we miss an event - self._job_completed_event.clear() + if self._job_terminated_event.wait(timeout=0.25): # in case we miss an event + self._job_terminated_event.clear() if timeout > 0 and time.time() - start > timeout: raise TimeoutError("Timeout exceeded") return job @@ -230,22 +278,25 @@ class DownloadQueueService(DownloadQueueServiceBase): job.job_started = get_iso_timestamp() self._do_download(job) self._signal_job_complete(job) - except (OSError, HTTPError) as excp: - job.error_type = excp.__class__.__name__ + f"({str(excp)})" - job.error = traceback.format_exc() - self._signal_job_error(job, excp) except DownloadJobCancelledException: self._signal_job_cancelled(job) self._cleanup_cancelled_job(job) - + except Exception as excp: + job.error_type = excp.__class__.__name__ + f"({str(excp)})" + job.error = traceback.format_exc() + self._signal_job_error(job, excp) finally: job.job_ended = get_iso_timestamp() - self._job_completed_event.set() # signal a change to terminal state + self._job_terminated_event.set() # signal a change to terminal state + self._download_part2parent.pop(job.source, None) # if this is a subpart of a multipart job, remove it + self._job_terminated_event.set() self._queue.task_done() + self._logger.debug(f"Download queue worker thread {threading.current_thread().name} exiting.") def _do_download(self, job: DownloadJob) -> None: """Do the actual download.""" + url = job.source header = {"Authorization": f"Bearer {job.access_token}"} if job.access_token else {} open_mode = "wb" @@ -339,7 +390,6 @@ class DownloadQueueService(DownloadQueueServiceBase): def _lookup_access_token(self, source: AnyHttpUrl) -> Optional[str]: # Pull the token from config if it exists and matches the URL - print(self._app_config) token = None for pair in self._app_config.remote_api_tokens or []: if re.search(pair.url_regex, str(source)): @@ -349,25 +399,13 @@ class DownloadQueueService(DownloadQueueServiceBase): def _signal_job_started(self, job: DownloadJob) -> None: job.status = DownloadJobStatus.RUNNING - if job.on_start: - try: - job.on_start(job) - except Exception as e: - self._logger.error( - f"An error occurred while processing the on_start callback: {traceback.format_exception(e)}" - ) + self._execute_cb(job, "on_start") if self._event_bus: assert job.download_path self._event_bus.emit_download_started(str(job.source), job.download_path.as_posix()) def _signal_job_progress(self, job: DownloadJob) -> None: - if job.on_progress: - try: - job.on_progress(job) - except Exception as e: - self._logger.error( - f"An error occurred while processing the on_progress callback: {traceback.format_exception(e)}" - ) + self._execute_cb(job, "on_progress") if self._event_bus: assert job.download_path self._event_bus.emit_download_progress( @@ -379,13 +417,7 @@ class DownloadQueueService(DownloadQueueServiceBase): def _signal_job_complete(self, job: DownloadJob) -> None: job.status = DownloadJobStatus.COMPLETED - if job.on_complete: - try: - job.on_complete(job) - except Exception as e: - self._logger.error( - f"An error occurred while processing the on_complete callback: {traceback.format_exception(e)}" - ) + self._execute_cb(job, "on_complete") if self._event_bus: assert job.download_path self._event_bus.emit_download_complete( @@ -396,26 +428,21 @@ class DownloadQueueService(DownloadQueueServiceBase): if job.status not in [DownloadJobStatus.RUNNING, DownloadJobStatus.WAITING]: return job.status = DownloadJobStatus.CANCELLED - if job.on_cancelled: - try: - job.on_cancelled(job) - except Exception as e: - self._logger.error( - f"An error occurred while processing the on_cancelled callback: {traceback.format_exception(e)}" - ) + self._execute_cb(job, "on_cancelled") if self._event_bus: self._event_bus.emit_download_cancelled(str(job.source)) + # if multifile download, then signal the parent + if parent_job := self._download_part2parent.get(job.source, None): + if not parent_job.in_terminal_state: + parent_job.status = DownloadJobStatus.CANCELLED + self._execute_cb(parent_job, "on_cancelled") + def _signal_job_error(self, job: DownloadJob, excp: Optional[Exception] = None) -> None: job.status = DownloadJobStatus.ERROR self._logger.error(f"{str(job.source)}: {traceback.format_exception(excp)}") - if job.on_error: - try: - job.on_error(job, excp) - except Exception as e: - self._logger.error( - f"An error occurred while processing the on_error callback: {traceback.format_exception(e)}" - ) + self._execute_cb(job, "on_error", excp) + if self._event_bus: assert job.error_type assert job.error @@ -430,6 +457,86 @@ class DownloadQueueService(DownloadQueueServiceBase): except OSError as excp: self._logger.warning(excp) + ######################################## + # callbacks used for multifile downloads + ######################################## + def _mfd_started(self, download_job: DownloadJob) -> None: + self._logger.info(f"File download started: {download_job.source}") + with self._lock: + mf_job = self._download_part2parent[download_job.source] + if mf_job.waiting: + mf_job.total_bytes = sum(x.total_bytes for x in mf_job.download_parts) + mf_job.status = DownloadJobStatus.RUNNING + self._execute_cb(mf_job, "on_start") + + def _mfd_progress(self, download_job: DownloadJob) -> None: + with self._lock: + mf_job = self._download_part2parent[download_job.source] + if mf_job.cancelled: + for part in mf_job.download_parts: + self.cancel_job(part) + elif mf_job.running: + mf_job.total_bytes = sum(x.total_bytes for x in mf_job.download_parts) + mf_job.bytes = sum(x.total_bytes for x in mf_job.download_parts) + self._execute_cb(mf_job, "on_progress") + + def _mfd_complete(self, download_job: DownloadJob) -> None: + self._logger.info(f"Download complete: {download_job.source}") + with self._lock: + mf_job = self._download_part2parent[download_job.source] + + # are there any more active jobs left in this task? + if mf_job.running and all(x.complete for x in mf_job.download_parts): + mf_job.status = DownloadJobStatus.COMPLETED + self._execute_cb(mf_job, "on_complete") + + # we're done with this sub-job + self._job_terminated_event.set() + + def _mfd_cancelled(self, download_job: DownloadJob) -> None: + with self._lock: + mf_job = self._download_part2parent[download_job.source] + assert mf_job is not None + + if not mf_job.in_terminal_state: + self._logger.warning(f"Download cancelled: {download_job.source}") + mf_job.cancel() + + for s in mf_job.download_parts: + self.cancel_job(s) + + def _mfd_error(self, download_job: DownloadJob, excp: Optional[Exception] = None) -> None: + with self._lock: + mf_job = self._download_part2parent[download_job.source] + assert mf_job is not None + if not mf_job.in_terminal_state: + mf_job.status = download_job.status + mf_job.error = download_job.error + mf_job.error_type = download_job.error_type + self._execute_cb(mf_job, "on_error", excp) + self._logger.error( + f"Cancelling {mf_job.dest} due to an error while downloading {download_job.source}: {str(excp)}" + ) + for s in [x for x in mf_job.download_parts if x.running]: + self.cancel_job(s) + self._download_part2parent.pop(download_job.source) + self._job_terminated_event.set() + + def _execute_cb( + self, + job: DownloadJob | MultiFileDownloadJob, + callback_name: str, + excp: Optional[Exception] = None, + ) -> None: + if callback := getattr(job, callback_name, None): + args = [job, excp] if excp else [job] + try: + callback(*args) + except Exception as e: + self._logger.error( + f"An error occurred while processing the {callback_name} callback: {traceback.format_exception(e)}" + ) + def get_pc_name_max(directory: str) -> int: if hasattr(os, "pathconf"): diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py index fe932649c4..f59c7b9f85 100644 --- a/invokeai/app/services/model_install/model_install_default.py +++ b/invokeai/app/services/model_install/model_install_default.py @@ -689,7 +689,6 @@ class ModelInstallService(ModelInstallServiceBase): self._logger.debug(f"metadata={metadata}") if metadata and isinstance(metadata, ModelMetadataWithFiles): remote_files = metadata.download_urls(session=self._session) - print(remote_files) else: remote_files = [RemoteModelFile(url=source.url, path=Path("."), size=0)] return self._import_remote_model( diff --git a/invokeai/backend/model_manager/metadata/metadata_base.py b/invokeai/backend/model_manager/metadata/metadata_base.py index 585c0fa31c..4abf020538 100644 --- a/invokeai/backend/model_manager/metadata/metadata_base.py +++ b/invokeai/backend/model_manager/metadata/metadata_base.py @@ -37,7 +37,7 @@ class RemoteModelFile(BaseModel): url: AnyHttpUrl = Field(description="The url to download this model file") path: Path = Field(description="The path to the file, relative to the model root") - size: int = Field(description="The size of this file, in bytes") + size: Optional[int] = Field(description="The size of this file, in bytes", default=0) sha256: Optional[str] = Field(description="SHA256 hash of this model (not always available)", default=None) diff --git a/tests/app/services/download/test_download_queue.py b/tests/app/services/download/test_download_queue.py index 07c473b183..578dbd2907 100644 --- a/tests/app/services/download/test_download_queue.py +++ b/tests/app/services/download/test_download_queue.py @@ -4,7 +4,7 @@ import re import time from contextlib import contextmanager from pathlib import Path -from typing import Generator +from typing import Generator, Optional import pytest from pydantic.networks import AnyHttpUrl @@ -13,7 +13,8 @@ from requests_testadapter import TestAdapter, TestSession from invokeai.app.services.config import get_config from invokeai.app.services.config.config_default import URLRegexTokenPair -from invokeai.app.services.download import DownloadJob, DownloadJobStatus, DownloadQueueService +from invokeai.app.services.download import DownloadJob, DownloadJobStatus, DownloadQueueService, MultiFileDownloadJob +from invokeai.backend.model_manager.metadata import HuggingFaceMetadataFetch, RemoteModelFile from tests.backend.model_manager.model_manager_fixtures import * # noqa F403 from tests.test_nodes import TestEventService @@ -67,11 +68,116 @@ def session() -> Session: return sess +@pytest.mark.timeout(timeout=10, method="thread") +def test_multifile_download(tmp_path: Path, mm2_session: Session) -> None: + fetcher = HuggingFaceMetadataFetch(mm2_session) + metadata = fetcher.from_id("stabilityai/sdxl-turbo") + events = set() + + def event_handler(job: DownloadJob | MultiFileDownloadJob, excp: Optional[Exception] = None) -> None: + print(f"bytes = {job.bytes}") + events.add(job.status) + + queue = DownloadQueueService( + requests_session=mm2_session, + ) + queue.start() + job = queue.multifile_download( + parts=metadata.download_urls(session=mm2_session), + dest=tmp_path, + on_start=event_handler, + on_progress=event_handler, + on_complete=event_handler, + on_error=event_handler, + ) + assert isinstance(job, MultiFileDownloadJob), "expected the job to be of type MultiFileDownloadJobBase" + queue.join() + + assert job.status == DownloadJobStatus("completed"), "expected job status to be completed" + assert job.bytes > 0, "expected download bytes to be positive" + assert job.bytes == job.total_bytes, "expected download bytes to equal total bytes" + assert Path( + tmp_path, "sdxl-turbo/model_index.json" + ).exists(), f"expected {tmp_path}/sdxl-turbo/model_inded.json to exist" + assert Path( + tmp_path, "sdxl-turbo/text_encoder/config.json" + ).exists(), f"expected {tmp_path}/sdxl-turbo/text_encoder/config.json to exist" + + assert events == {DownloadJobStatus.RUNNING, DownloadJobStatus.COMPLETED} + queue.stop() + + +@pytest.mark.timeout(timeout=10, method="thread") +def test_multifile_download_error(tmp_path: Path, mm2_session: Session) -> None: + fetcher = HuggingFaceMetadataFetch(mm2_session) + metadata = fetcher.from_id("stabilityai/sdxl-turbo") + events = set() + + def event_handler(job: DownloadJob | MultiFileDownloadJob, excp: Optional[Exception] = None) -> None: + events.add(job.status) + + queue = DownloadQueueService( + requests_session=mm2_session, + ) + queue.start() + files = metadata.download_urls(session=mm2_session) + # this will give a 404 error + files.append(RemoteModelFile(url="https://test.com/missing_model.safetensors", path=Path("sdxl-turbo/broken"))) + job = queue.multifile_download( + parts=files, + dest=tmp_path, + on_start=event_handler, + on_progress=event_handler, + on_complete=event_handler, + on_error=event_handler, + ) + queue.join() + + assert job.status == DownloadJobStatus("error"), "expected job status to be errored" + assert "HTTPError(NOT FOUND)" in job.error_type + assert DownloadJobStatus.ERROR in events + queue.stop() + + +@pytest.mark.timeout(timeout=15, method="thread") +def test_multifile_cancel(tmp_path: Path, mm2_session: Session, monkeypatch) -> None: + event_bus = TestEventService() + + queue = DownloadQueueService(requests_session=mm2_session, event_bus=event_bus) + queue.start() + + cancelled = False + + def cancelled_callback(job: DownloadJob) -> None: + nonlocal cancelled + cancelled = True + + def handler(signum, frame): + raise TimeoutError("Join took too long to return") + + fetcher = HuggingFaceMetadataFetch(mm2_session) + metadata = fetcher.from_id("stabilityai/sdxl-turbo") + + job = queue.multifile_download( + parts=metadata.download_urls(session=mm2_session), + dest=tmp_path, + on_cancelled=cancelled_callback, + ) + queue.cancel_job(job) + queue.join() + + assert job.status == DownloadJobStatus.CANCELLED + assert cancelled + events = event_bus.events + assert "download_cancelled" in [x.event_name for x in events] + queue.stop() + + @pytest.mark.timeout(timeout=20, method="thread") def test_basic_queue_download(tmp_path: Path, session: Session) -> None: events = set() - def event_handler(job: DownloadJob) -> None: + def event_handler(job: DownloadJob, excp: Optional[Exception] = None) -> None: events.add(job.status) queue = DownloadQueueService( From 287c679f7b14b8faa00e93110b9b03a0ba46c35c Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Mon, 13 May 2024 18:31:40 -0400 Subject: [PATCH 022/110] clean up type checking for single file and multifile download job callbacks --- .../app/services/download/download_base.py | 25 +- .../app/services/download/download_default.py | 19 +- .../services/download/test_download_queue.py | 314 +++++++++--------- 3 files changed, 186 insertions(+), 172 deletions(-) diff --git a/invokeai/app/services/download/download_base.py b/invokeai/app/services/download/download_base.py index 9bb2300eb6..3e415091c7 100644 --- a/invokeai/app/services/download/download_base.py +++ b/invokeai/app/services/download/download_base.py @@ -5,7 +5,7 @@ from abc import ABC, abstractmethod from enum import Enum from functools import total_ordering from pathlib import Path -from typing import Any, Callable, List, Optional, Set +from typing import Any, Callable, List, Optional, Set, Union from pydantic import BaseModel, Field, PrivateAttr from pydantic.networks import AnyHttpUrl @@ -35,12 +35,12 @@ class ServiceInactiveException(Exception): """This exception is raised when user attempts to initiate a download before the service is started.""" -DownloadEventHandler = Callable[["DownloadJobBase"], None] -DownloadExceptionHandler = Callable[["DownloadJobBase", Optional[Exception]], None] - +SingleFileDownloadEventHandler = Callable[["DownloadJob"], None] +SingleFileDownloadExceptionHandler = Callable[["DownloadJob", Optional[Exception]], None] MultiFileDownloadEventHandler = Callable[["MultiFileDownloadJob"], None] MultiFileDownloadExceptionHandler = Callable[["MultiFileDownloadJob", Optional[Exception]], None] - +DownloadEventHandler = Union[SingleFileDownloadEventHandler, MultiFileDownloadEventHandler] +DownloadExceptionHandler = Union[SingleFileDownloadExceptionHandler, MultiFileDownloadExceptionHandler] class DownloadJobBase(BaseModel): """Base of classes to monitor and control downloads.""" @@ -228,6 +228,7 @@ class DownloadQueueServiceBase(ABC): parts: Set[RemoteModelFile], dest: Path, access_token: Optional[str] = None, + submit_job: bool = True, on_start: Optional[DownloadEventHandler] = None, on_progress: Optional[DownloadEventHandler] = None, on_complete: Optional[DownloadEventHandler] = None, @@ -239,6 +240,11 @@ class DownloadQueueServiceBase(ABC): :param parts: Set of URL / filename pairs :param dest: Path to download to. See below. + :param access_token: Access token to download the indicated files. If not provided, + each file's URL may be matched to an access token using the config file matching + system. + :param submit_job: If true [default] then submit the job for execution. Otherwise, + you will need to pass the job to submit_multifile_download(). :param on_start, on_progress, on_complete, on_error: Callbacks for the indicated events. :returns: A MultiFileDownloadJob object for monitoring the state of the download. @@ -249,6 +255,15 @@ class DownloadQueueServiceBase(ABC): """ pass + @abstractmethod + def submit_multifile_download(self, job: MultiFileDownloadJob) -> None: + """ + Enqueue a previously-created multi-file download job. + + :param job: A MultiFileDownloadJob created with multifile_download() + """ + pass + @abstractmethod def submit_download_job( self, diff --git a/invokeai/app/services/download/download_default.py b/invokeai/app/services/download/download_default.py index 9ab452c1ef..3f55e9a254 100644 --- a/invokeai/app/services/download/download_default.py +++ b/invokeai/app/services/download/download_default.py @@ -25,11 +25,10 @@ from .download_base import ( DownloadEventHandler, DownloadExceptionHandler, DownloadJob, + DownloadJobBase, DownloadJobCancelledException, DownloadJobStatus, DownloadQueueServiceBase, - MultiFileDownloadEventHandler, - MultiFileDownloadExceptionHandler, MultiFileDownloadJob, ServiceInactiveException, UnknownJobIDException, @@ -165,11 +164,11 @@ class DownloadQueueService(DownloadQueueServiceBase): parts: Set[RemoteModelFile], dest: Path, access_token: Optional[str] = None, - on_start: Optional[MultiFileDownloadEventHandler] = None, - on_progress: Optional[MultiFileDownloadEventHandler] = None, - on_complete: Optional[MultiFileDownloadEventHandler] = None, - on_cancelled: Optional[MultiFileDownloadEventHandler] = None, - on_error: Optional[MultiFileDownloadExceptionHandler] = None, + on_start: Optional[DownloadEventHandler] = None, + on_progress: Optional[DownloadEventHandler] = None, + on_complete: Optional[DownloadEventHandler] = None, + on_cancelled: Optional[DownloadEventHandler] = None, + on_error: Optional[DownloadExceptionHandler] = None, ) -> MultiFileDownloadJob: mfdj = MultiFileDownloadJob(dest=dest) mfdj.set_callbacks( @@ -191,8 +190,11 @@ class DownloadQueueService(DownloadQueueServiceBase): ) mfdj.download_parts.add(job) self._download_part2parent[job.source] = mfdj + self.submit_multifile_download(mfdj) + return mfdj - for download_job in mfdj.download_parts: + def submit_multifile_download(self, job: MultiFileDownloadJob) -> None: + for download_job in job.download_parts: self.submit_download_job( download_job, on_start=self._mfd_started, @@ -201,7 +203,6 @@ class DownloadQueueService(DownloadQueueServiceBase): on_cancelled=self._mfd_cancelled, on_error=self._mfd_error, ) - return mfdj def join(self) -> None: """Wait for all jobs to complete.""" diff --git a/tests/app/services/download/test_download_queue.py b/tests/app/services/download/test_download_queue.py index 578dbd2907..393cd54a03 100644 --- a/tests/app/services/download/test_download_queue.py +++ b/tests/app/services/download/test_download_queue.py @@ -68,6 +68,161 @@ def session() -> Session: return sess +@pytest.mark.timeout(timeout=10, method="thread") +def test_basic_queue_download(tmp_path: Path, session: Session) -> None: + events = set() + + def event_handler(job: DownloadJob, excp: Optional[Exception] = None) -> None: + events.add(job.status) + + queue = DownloadQueueService( + requests_session=session, + ) + queue.start() + job = queue.download( + source=AnyHttpUrl("http://www.civitai.com/models/12345"), + dest=tmp_path, + on_start=event_handler, + on_progress=event_handler, + on_complete=event_handler, + on_error=event_handler, + ) + assert isinstance(job, DownloadJob), "expected the job to be of type DownloadJobBase" + assert isinstance(job.id, int), "expected the job id to be numeric" + queue.join() + + assert job.status == DownloadJobStatus("completed"), "expected job status to be completed" + assert Path(tmp_path, "mock12345.safetensors").exists(), f"expected {tmp_path}/mock12345.safetensors to exist" + + assert events == {DownloadJobStatus.RUNNING, DownloadJobStatus.COMPLETED} + queue.stop() + + +@pytest.mark.timeout(timeout=10, method="thread") +def test_errors(tmp_path: Path, session: Session) -> None: + queue = DownloadQueueService( + requests_session=session, + ) + queue.start() + + for bad_url in ["http://www.civitai.com/models/broken", "http://www.civitai.com/models/missing"]: + queue.download(AnyHttpUrl(bad_url), dest=tmp_path) + + queue.join() + jobs = queue.list_jobs() + print(jobs) + assert len(jobs) == 2 + jobs_dict = {str(x.source): x for x in jobs} + assert jobs_dict["http://www.civitai.com/models/broken"].status == DownloadJobStatus.ERROR + assert jobs_dict["http://www.civitai.com/models/broken"].error_type == "HTTPError(NOT FOUND)" + assert jobs_dict["http://www.civitai.com/models/missing"].status == DownloadJobStatus.COMPLETED + assert jobs_dict["http://www.civitai.com/models/missing"].total_bytes == 0 + queue.stop() + + +@pytest.mark.timeout(timeout=10, method="thread") +def test_event_bus(tmp_path: Path, session: Session) -> None: + event_bus = TestEventService() + + queue = DownloadQueueService(requests_session=session, event_bus=event_bus) + queue.start() + queue.download( + source=AnyHttpUrl("http://www.civitai.com/models/12345"), + dest=tmp_path, + ) + queue.join() + events = event_bus.events + assert len(events) == 3 + assert events[0].payload["timestamp"] <= events[1].payload["timestamp"] + assert events[1].payload["timestamp"] <= events[2].payload["timestamp"] + assert events[0].event_name == "download_started" + assert events[1].event_name == "download_progress" + assert events[1].payload["total_bytes"] > 0 + assert events[1].payload["current_bytes"] <= events[1].payload["total_bytes"] + assert events[2].event_name == "download_complete" + assert events[2].payload["total_bytes"] == 32029 + + # test a failure + event_bus.events = [] # reset our accumulator + queue.download(source=AnyHttpUrl("http://www.civitai.com/models/broken"), dest=tmp_path) + queue.join() + events = event_bus.events + print("\n".join([x.model_dump_json() for x in events])) + assert len(events) == 1 + assert events[0].event_name == "download_error" + assert events[0].payload["error_type"] == "HTTPError(NOT FOUND)" + assert events[0].payload["error"] is not None + assert re.search(r"requests.exceptions.HTTPError: NOT FOUND", events[0].payload["error"]) + queue.stop() + + +@pytest.mark.timeout(timeout=10, method="thread") +def test_broken_callbacks(tmp_path: Path, session: Session, capsys) -> None: + queue = DownloadQueueService( + requests_session=session, + ) + queue.start() + + callback_ran = False + + def broken_callback(job: DownloadJob) -> None: + nonlocal callback_ran + callback_ran = True + print(1 / 0) # deliberate error here + + job = queue.download( + source=AnyHttpUrl("http://www.civitai.com/models/12345"), + dest=tmp_path, + on_progress=broken_callback, + ) + + queue.join() + assert job.status == DownloadJobStatus.COMPLETED # should complete even though the callback is borked + assert Path(tmp_path, "mock12345.safetensors").exists() + assert callback_ran + # LS: The pytest capsys fixture does not seem to be working. I can see the + # correct stderr message in the pytest log, but it is not appearing in + # capsys.readouterr(). + # captured = capsys.readouterr() + # assert re.search("division by zero", captured.err) + queue.stop() + + +@pytest.mark.timeout(timeout=10, method="thread") +def test_cancel(tmp_path: Path, session: Session) -> None: + event_bus = TestEventService() + + queue = DownloadQueueService(requests_session=session, event_bus=event_bus) + queue.start() + + cancelled = False + + def slow_callback(job: DownloadJob) -> None: + time.sleep(2) + + def cancelled_callback(job: DownloadJob) -> None: + nonlocal cancelled + cancelled = True + + def handler(signum, frame): + raise TimeoutError("Join took too long to return") + + job = queue.download( + source=AnyHttpUrl("http://www.civitai.com/models/12345"), + dest=tmp_path, + on_start=slow_callback, + on_cancelled=cancelled_callback, + ) + queue.cancel_job(job) + queue.join() + + assert job.status == DownloadJobStatus.CANCELLED + assert cancelled + events = event_bus.events + assert events[-1].event_name == "download_cancelled" + assert events[-1].payload["source"] == "http://www.civitai.com/models/12345" + queue.stop() + @pytest.mark.timeout(timeout=10, method="thread") def test_multifile_download(tmp_path: Path, mm2_session: Session) -> None: fetcher = HuggingFaceMetadataFetch(mm2_session) @@ -139,7 +294,7 @@ def test_multifile_download_error(tmp_path: Path, mm2_session: Session) -> None: queue.stop() -@pytest.mark.timeout(timeout=15, method="thread") +@pytest.mark.timeout(timeout=10, method="thread") def test_multifile_cancel(tmp_path: Path, mm2_session: Session, monkeypatch) -> None: event_bus = TestEventService() @@ -172,163 +327,6 @@ def test_multifile_cancel(tmp_path: Path, mm2_session: Session, monkeypatch) -> assert "download_cancelled" in [x.event_name for x in events] queue.stop() - -@pytest.mark.timeout(timeout=20, method="thread") -def test_basic_queue_download(tmp_path: Path, session: Session) -> None: - events = set() - - def event_handler(job: DownloadJob, excp: Optional[Exception] = None) -> None: - events.add(job.status) - - queue = DownloadQueueService( - requests_session=session, - ) - queue.start() - job = queue.download( - source=AnyHttpUrl("http://www.civitai.com/models/12345"), - dest=tmp_path, - on_start=event_handler, - on_progress=event_handler, - on_complete=event_handler, - on_error=event_handler, - ) - assert isinstance(job, DownloadJob), "expected the job to be of type DownloadJobBase" - assert isinstance(job.id, int), "expected the job id to be numeric" - queue.join() - - assert job.status == DownloadJobStatus("completed"), "expected job status to be completed" - assert Path(tmp_path, "mock12345.safetensors").exists(), f"expected {tmp_path}/mock12345.safetensors to exist" - - assert events == {DownloadJobStatus.RUNNING, DownloadJobStatus.COMPLETED} - queue.stop() - - -@pytest.mark.timeout(timeout=20, method="thread") -def test_errors(tmp_path: Path, session: Session) -> None: - queue = DownloadQueueService( - requests_session=session, - ) - queue.start() - - for bad_url in ["http://www.civitai.com/models/broken", "http://www.civitai.com/models/missing"]: - queue.download(AnyHttpUrl(bad_url), dest=tmp_path) - - queue.join() - jobs = queue.list_jobs() - print(jobs) - assert len(jobs) == 2 - jobs_dict = {str(x.source): x for x in jobs} - assert jobs_dict["http://www.civitai.com/models/broken"].status == DownloadJobStatus.ERROR - assert jobs_dict["http://www.civitai.com/models/broken"].error_type == "HTTPError(NOT FOUND)" - assert jobs_dict["http://www.civitai.com/models/missing"].status == DownloadJobStatus.COMPLETED - assert jobs_dict["http://www.civitai.com/models/missing"].total_bytes == 0 - queue.stop() - - -@pytest.mark.timeout(timeout=20, method="thread") -def test_event_bus(tmp_path: Path, session: Session) -> None: - event_bus = TestEventService() - - queue = DownloadQueueService(requests_session=session, event_bus=event_bus) - queue.start() - queue.download( - source=AnyHttpUrl("http://www.civitai.com/models/12345"), - dest=tmp_path, - ) - queue.join() - events = event_bus.events - assert len(events) == 3 - assert events[0].payload["timestamp"] <= events[1].payload["timestamp"] - assert events[1].payload["timestamp"] <= events[2].payload["timestamp"] - assert events[0].event_name == "download_started" - assert events[1].event_name == "download_progress" - assert events[1].payload["total_bytes"] > 0 - assert events[1].payload["current_bytes"] <= events[1].payload["total_bytes"] - assert events[2].event_name == "download_complete" - assert events[2].payload["total_bytes"] == 32029 - - # test a failure - event_bus.events = [] # reset our accumulator - queue.download(source=AnyHttpUrl("http://www.civitai.com/models/broken"), dest=tmp_path) - queue.join() - events = event_bus.events - print("\n".join([x.model_dump_json() for x in events])) - assert len(events) == 1 - assert events[0].event_name == "download_error" - assert events[0].payload["error_type"] == "HTTPError(NOT FOUND)" - assert events[0].payload["error"] is not None - assert re.search(r"requests.exceptions.HTTPError: NOT FOUND", events[0].payload["error"]) - queue.stop() - - -@pytest.mark.timeout(timeout=20, method="thread") -def test_broken_callbacks(tmp_path: Path, session: Session, capsys) -> None: - queue = DownloadQueueService( - requests_session=session, - ) - queue.start() - - callback_ran = False - - def broken_callback(job: DownloadJob) -> None: - nonlocal callback_ran - callback_ran = True - print(1 / 0) # deliberate error here - - job = queue.download( - source=AnyHttpUrl("http://www.civitai.com/models/12345"), - dest=tmp_path, - on_progress=broken_callback, - ) - - queue.join() - assert job.status == DownloadJobStatus.COMPLETED # should complete even though the callback is borked - assert Path(tmp_path, "mock12345.safetensors").exists() - assert callback_ran - # LS: The pytest capsys fixture does not seem to be working. I can see the - # correct stderr message in the pytest log, but it is not appearing in - # capsys.readouterr(). - # captured = capsys.readouterr() - # assert re.search("division by zero", captured.err) - queue.stop() - - -@pytest.mark.timeout(timeout=15, method="thread") -def test_cancel(tmp_path: Path, session: Session) -> None: - event_bus = TestEventService() - - queue = DownloadQueueService(requests_session=session, event_bus=event_bus) - queue.start() - - cancelled = False - - def slow_callback(job: DownloadJob) -> None: - time.sleep(2) - - def cancelled_callback(job: DownloadJob) -> None: - nonlocal cancelled - cancelled = True - - def handler(signum, frame): - raise TimeoutError("Join took too long to return") - - job = queue.download( - source=AnyHttpUrl("http://www.civitai.com/models/12345"), - dest=tmp_path, - on_start=slow_callback, - on_cancelled=cancelled_callback, - ) - queue.cancel_job(job) - queue.join() - - assert job.status == DownloadJobStatus.CANCELLED - assert cancelled - events = event_bus.events - assert events[-1].event_name == "download_cancelled" - assert events[-1].payload["source"] == "http://www.civitai.com/models/12345" - queue.stop() - - @contextmanager def clear_config() -> Generator[None, None, None]: try: From f29c406fed4f398a4134643f356f402e9a4426f5 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Mon, 13 May 2024 22:49:15 -0400 Subject: [PATCH 023/110] refactor model_install to work with refactored download queue --- .../app/services/download/download_base.py | 12 +- .../app/services/download/download_default.py | 45 +++-- .../model_install/model_install_base.py | 24 +-- .../model_install/model_install_default.py | 167 +++++++----------- .../model_manager/metadata/metadata_base.py | 3 + .../services/download/test_download_queue.py | 117 +++++------- .../model_install/test_model_install.py | 37 +++- .../model_manager/model_manager_fixtures.py | 41 +++++ 8 files changed, 226 insertions(+), 220 deletions(-) diff --git a/invokeai/app/services/download/download_base.py b/invokeai/app/services/download/download_base.py index 3e415091c7..4880ab98b8 100644 --- a/invokeai/app/services/download/download_base.py +++ b/invokeai/app/services/download/download_base.py @@ -42,9 +42,13 @@ MultiFileDownloadExceptionHandler = Callable[["MultiFileDownloadJob", Optional[E DownloadEventHandler = Union[SingleFileDownloadEventHandler, MultiFileDownloadEventHandler] DownloadExceptionHandler = Union[SingleFileDownloadExceptionHandler, MultiFileDownloadExceptionHandler] + class DownloadJobBase(BaseModel): """Base of classes to monitor and control downloads.""" + # automatically assigned on creation + id: int = Field(description="Numeric ID of this job", default=-1) # default id is a sentinel + dest: Path = Field(description="Initial destination of downloaded model on local disk; a directory or file path") download_path: Optional[Path] = Field(default=None, description="Final location of downloaded file or directory") status: DownloadJobStatus = Field(default=DownloadJobStatus.WAITING, description="Status of the download") @@ -149,8 +153,6 @@ class DownloadJob(DownloadJobBase): # required variables to be passed in on creation source: AnyHttpUrl = Field(description="Where to download from. Specific types specified in child classes.") access_token: Optional[str] = Field(default=None, description="authorization token for protected resources") - # automatically assigned on creation - id: int = Field(description="Numeric ID of this job", default=-1) # default id is a sentinel priority: int = Field(default=10, description="Queue priority; lower values are higher priority") # set internally during download process @@ -225,7 +227,7 @@ class DownloadQueueServiceBase(ABC): @abstractmethod def multifile_download( self, - parts: Set[RemoteModelFile], + parts: List[RemoteModelFile], dest: Path, access_token: Optional[str] = None, submit_job: bool = True, @@ -315,7 +317,7 @@ class DownloadQueueServiceBase(ABC): pass @abstractmethod - def cancel_job(self, job: DownloadJob) -> None: + def cancel_job(self, job: DownloadJobBase) -> None: """Cancel the job, clearing partial downloads and putting it into ERROR state.""" pass @@ -325,7 +327,7 @@ class DownloadQueueServiceBase(ABC): pass @abstractmethod - def wait_for_job(self, job: DownloadJob | MultiFileDownloadJob, timeout: int = 0) -> DownloadJob: + def wait_for_job(self, job: DownloadJobBase, timeout: int = 0) -> DownloadJobBase: """Wait until the indicated download job has reached a terminal state. This will block until the indicated install job has completed, diff --git a/invokeai/app/services/download/download_default.py b/invokeai/app/services/download/download_default.py index 3f55e9a254..4555477004 100644 --- a/invokeai/app/services/download/download_default.py +++ b/invokeai/app/services/download/download_default.py @@ -113,18 +113,16 @@ class DownloadQueueService(DownloadQueueServiceBase): raise ServiceInactiveException( "The download service is not currently accepting requests. Please call start() to initialize the service." ) - with self._lock: - job.id = self._next_job_id - self._next_job_id += 1 - job.set_callbacks( - on_start=on_start, - on_progress=on_progress, - on_complete=on_complete, - on_cancelled=on_cancelled, - on_error=on_error, - ) - self._jobs[job.id] = job - self._queue.put(job) + job.id = self._next_id() + job.set_callbacks( + on_start=on_start, + on_progress=on_progress, + on_complete=on_complete, + on_cancelled=on_cancelled, + on_error=on_error, + ) + self._jobs[job.id] = job + self._queue.put(job) def download( self, @@ -161,16 +159,17 @@ class DownloadQueueService(DownloadQueueServiceBase): def multifile_download( self, - parts: Set[RemoteModelFile], + parts: List[RemoteModelFile], dest: Path, access_token: Optional[str] = None, + submit_job: bool = True, on_start: Optional[DownloadEventHandler] = None, on_progress: Optional[DownloadEventHandler] = None, on_complete: Optional[DownloadEventHandler] = None, on_cancelled: Optional[DownloadEventHandler] = None, on_error: Optional[DownloadExceptionHandler] = None, ) -> MultiFileDownloadJob: - mfdj = MultiFileDownloadJob(dest=dest) + mfdj = MultiFileDownloadJob(dest=dest, id=self._next_id()) mfdj.set_callbacks( on_start=on_start, on_progress=on_progress, @@ -190,7 +189,8 @@ class DownloadQueueService(DownloadQueueServiceBase): ) mfdj.download_parts.add(job) self._download_part2parent[job.source] = mfdj - self.submit_multifile_download(mfdj) + if submit_job: + self.submit_multifile_download(mfdj) return mfdj def submit_multifile_download(self, job: MultiFileDownloadJob) -> None: @@ -208,6 +208,12 @@ class DownloadQueueService(DownloadQueueServiceBase): """Wait for all jobs to complete.""" self._queue.join() + def _next_id(self) -> int: + with self._lock: + id = self._next_job_id + self._next_job_id += 1 + return id + def list_jobs(self) -> List[DownloadJob]: """List all the jobs.""" return list(self._jobs.values()) @@ -229,7 +235,7 @@ class DownloadQueueService(DownloadQueueServiceBase): except KeyError as excp: raise UnknownJobIDException("Unrecognized job") from excp - def cancel_job(self, job: DownloadJob) -> None: + def cancel_job(self, job: DownloadJobBase) -> None: """ Cancel the indicated job. @@ -245,7 +251,7 @@ class DownloadQueueService(DownloadQueueServiceBase): if not job.in_terminal_state: self.cancel_job(job) - def wait_for_job(self, job: DownloadJob | MultiFileDownloadJob, timeout: int = 0) -> DownloadJob: + def wait_for_job(self, job: DownloadJobBase, timeout: int = 0) -> DownloadJobBase: """Block until the indicated job has reached terminal state, or when timeout limit reached.""" start = time.time() while not job.in_terminal_state: @@ -468,6 +474,11 @@ class DownloadQueueService(DownloadQueueServiceBase): if mf_job.waiting: mf_job.total_bytes = sum(x.total_bytes for x in mf_job.download_parts) mf_job.status = DownloadJobStatus.RUNNING + assert download_job.download_path is not None + path_relative_to_destdir = download_job.download_path.relative_to(mf_job.dest) + mf_job.download_path = ( + mf_job.dest / path_relative_to_destdir.parts[0] + ) # keep just the first component of the path self._execute_cb(mf_job, "on_start") def _mfd_progress(self, download_job: DownloadJob) -> None: diff --git a/invokeai/app/services/model_install/model_install_base.py b/invokeai/app/services/model_install/model_install_base.py index ccb8e3772e..68cf9591e0 100644 --- a/invokeai/app/services/model_install/model_install_base.py +++ b/invokeai/app/services/model_install/model_install_base.py @@ -6,14 +6,14 @@ import traceback from abc import ABC, abstractmethod from enum import Enum from pathlib import Path -from typing import Any, Dict, List, Literal, Optional, Set, Union +from typing import Any, Dict, List, Literal, Optional, Union from pydantic import BaseModel, Field, PrivateAttr, field_validator from pydantic.networks import AnyHttpUrl from typing_extensions import Annotated from invokeai.app.services.config import InvokeAIAppConfig -from invokeai.app.services.download import DownloadJob, DownloadQueueServiceBase +from invokeai.app.services.download import DownloadQueueServiceBase, MultiFileDownloadJob from invokeai.app.services.events.events_base import EventServiceBase from invokeai.app.services.invoker import Invoker from invokeai.app.services.model_records import ModelRecordServiceBase @@ -166,9 +166,6 @@ class ModelInstallJob(BaseModel): source_metadata: Optional[AnyModelRepoMetadata] = Field( default=None, description="Metadata provided by the model source" ) - download_parts: Set[DownloadJob] = Field( - default_factory=set, description="Download jobs contributing to this install" - ) error: Optional[str] = Field( default=None, description="On an error condition, this field will contain the text of the exception" ) @@ -177,7 +174,7 @@ class ModelInstallJob(BaseModel): ) # internal flags and transitory settings _install_tmpdir: Optional[Path] = PrivateAttr(default=None) - _do_install: Optional[bool] = PrivateAttr(default=True) + _download_job: Optional[MultiFileDownloadJob] = PrivateAttr(default=None) _exception: Optional[Exception] = PrivateAttr(default=None) def set_error(self, e: Exception) -> None: @@ -408,21 +405,6 @@ class ModelInstallServiceBase(ABC): """ - @abstractmethod - def download_diffusers_model( - self, - source: HFModelSource, - download_to: Path, - ) -> ModelInstallJob: - """ - Download, but do not install, a diffusers model. - - :param source: An HFModelSource object containing a repo_id - :param download_to: Path to directory that will contain the downloaded model. - - Returns: a ModelInstallJob - """ - @abstractmethod def get_job_by_source(self, source: ModelSource) -> List[ModelInstallJob]: """Return the ModelInstallJob(s) corresponding to the provided source.""" diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py index f59c7b9f85..2ad321c260 100644 --- a/invokeai/app/services/model_install/model_install_default.py +++ b/invokeai/app/services/model_install/model_install_default.py @@ -9,7 +9,7 @@ from pathlib import Path from queue import Empty, Queue from shutil import copyfile, copytree, move, rmtree from tempfile import mkdtemp -from typing import Any, Dict, List, Optional, Union +from typing import Any, Dict, List, Optional, Type, Union import torch import yaml @@ -18,7 +18,7 @@ from pydantic.networks import AnyHttpUrl from requests import Session from invokeai.app.services.config import InvokeAIAppConfig -from invokeai.app.services.download import DownloadJob, DownloadQueueServiceBase, TqdmProgress +from invokeai.app.services.download import DownloadQueueServiceBase, MultiFileDownloadJob, TqdmProgress from invokeai.app.services.events.events_base import EventServiceBase from invokeai.app.services.invoker import Invoker from invokeai.app.services.model_records import DuplicateModelException, ModelRecordServiceBase @@ -89,7 +89,7 @@ class ModelInstallService(ModelInstallServiceBase): self._downloads_changed_event = threading.Event() self._install_completed_event = threading.Event() self._download_queue = download_queue - self._download_cache: Dict[AnyHttpUrl, ModelInstallJob] = {} + self._download_cache: Dict[int, ModelInstallJob] = {} self._running = False self._session = session self._install_thread: Optional[threading.Thread] = None @@ -249,9 +249,6 @@ class ModelInstallService(ModelInstallServiceBase): self._install_jobs.append(install_job) return install_job - def download_diffusers_model(self, source: HFModelSource, download_to: Path) -> ModelInstallJob: - return self._import_from_hf(source, download_path=download_to) - def list_jobs(self) -> List[ModelInstallJob]: # noqa D102 return self._install_jobs @@ -291,8 +288,9 @@ class ModelInstallService(ModelInstallServiceBase): def cancel_job(self, job: ModelInstallJob) -> None: """Cancel the indicated job.""" job.cancel() - with self._lock: - self._cancel_download_parts(job) + self._logger.warning(f"Cancelling {job.source}") + if dj := job._download_job: + self._download_queue.cancel_job(dj) def prune_jobs(self) -> None: """Prune all completed and errored jobs.""" @@ -340,7 +338,7 @@ class ModelInstallService(ModelInstallServiceBase): legacy_config_path = stanza.get("config") if legacy_config_path: # In v3, these paths were relative to the root. Migrate them to be relative to the legacy_conf_dir. - legacy_config_path: Path = self._app_config.root_path / legacy_config_path + legacy_config_path = self._app_config.root_path / legacy_config_path if legacy_config_path.is_relative_to(self._app_config.legacy_conf_path): legacy_config_path = legacy_config_path.relative_to(self._app_config.legacy_conf_path) config["config_path"] = str(legacy_config_path) @@ -476,16 +474,19 @@ class ModelInstallService(ModelInstallServiceBase): job.config_out = self.record_store.get_model(key) self._signal_job_completed(job) - def _set_error(self, job: ModelInstallJob, excp: Exception) -> None: - if any(x.content_type is not None and "text/html" in x.content_type for x in job.download_parts): - job.set_error( + def _set_error(self, install_job: ModelInstallJob, excp: Exception) -> None: + download_job = install_job._download_job + if download_job and any( + x.content_type is not None and "text/html" in x.content_type for x in download_job.download_parts + ): + install_job.set_error( InvalidModelConfigException( - f"At least one file in {job.local_path} is an HTML page, not a model. This can happen when an access token is required to download." + f"At least one file in {install_job.local_path} is an HTML page, not a model. This can happen when an access token is required to download." ) ) else: - job.set_error(excp) - self._signal_job_errored(job) + install_job.set_error(excp) + self._signal_job_errored(install_job) # -------------------------------------------------------------------------------------------- # Internal functions that manage the models directory @@ -511,7 +512,6 @@ class ModelInstallService(ModelInstallServiceBase): This is typically only used during testing with a new DB or when using the memory DB, because those are the only situations in which we may have orphaned models in the models directory. """ - installed_model_paths = { (self._app_config.models_path / x.path).resolve() for x in self.record_store.all_models() } @@ -648,7 +648,6 @@ class ModelInstallService(ModelInstallServiceBase): self, source: HFModelSource, config: Optional[Dict[str, Any]] = None, - download_path: Optional[Path] = None, ) -> ModelInstallJob: # Add user's cached access token to HuggingFace requests source.access_token = source.access_token or HfFolder.get_token() @@ -668,7 +667,6 @@ class ModelInstallService(ModelInstallServiceBase): config=config, remote_files=remote_files, metadata=metadata, - download_path=download_path, ) def _import_from_url( @@ -704,14 +702,10 @@ class ModelInstallService(ModelInstallServiceBase): remote_files: List[RemoteModelFile], metadata: Optional[AnyModelRepoMetadata], config: Optional[Dict[str, Any]], - download_path: Optional[Path] = None, # if defined, download only - don't install! ) -> ModelInstallJob: - # TODO: Replace with tempfile.tmpdir() when multithreading is cleaned up. - # Currently the tmpdir isn't automatically removed at exit because it is - # being held in a daemon thread. if len(remote_files) == 0: raise ValueError(f"{source}: No downloadable files found") - destdir = download_path or Path( + destdir = Path( mkdtemp( dir=self._app_config.models_path, prefix=TMPDIR_PREFIX, @@ -726,6 +720,9 @@ class ModelInstallService(ModelInstallServiceBase): bytes=0, total_bytes=0, ) + # remember the temporary directory for later removal + install_job._install_tmpdir = destdir + # In the event that there is a subfolder specified in the source, # we need to remove it from the destination path in order to avoid # creating unwanted subfolders @@ -739,39 +736,31 @@ class ModelInstallService(ModelInstallServiceBase): # we remember the path up to the top of the destdir so that it may be # removed safely at the end of the install process. install_job._install_tmpdir = destdir - install_job._do_install = download_path is None - assert install_job.total_bytes is not None # to avoid type checking complaints in the loop below + + parts: List[RemoteModelFile] = [] + for model_file in remote_files: + assert install_job.total_bytes is not None + assert model_file.size is not None + install_job.total_bytes += model_file.size + parts.append(RemoteModelFile(url=model_file.url, path=model_file.path.relative_to(subfolder))) + multifile_job = self._download_queue.multifile_download( + parts=parts, + dest=destdir, + access_token=source.access_token, + submit_job=False, + on_start=self._download_started_callback, + on_progress=self._download_progress_callback, + on_complete=self._download_complete_callback, + on_error=self._download_error_callback, + on_cancelled=self._download_cancelled_callback, + ) + self._download_cache[multifile_job.id] = install_job + install_job._download_job = multifile_job files_string = "file" if len(remote_files) == 1 else "file" self._logger.info(f"Queuing model install: {source} ({len(remote_files)} {files_string})") self._logger.debug(f"remote_files={remote_files}") - for model_file in remote_files: - url = model_file.url - path = root / model_file.path.relative_to(subfolder) - self._logger.debug(f"Downloading {url} => {path}") - install_job.total_bytes += model_file.size - assert hasattr(source, "access_token") - dest = destdir / path.parent - dest.mkdir(parents=True, exist_ok=True) - download_job = DownloadJob( - source=url, - dest=dest, - access_token=source.access_token, - ) - self._download_cache[download_job.source] = install_job # matches a download job to an install job - install_job.download_parts.add(download_job) - - # only start the jobs once install_job.download_parts is fully populated - for download_job in install_job.download_parts: - self._download_queue.submit_download_job( - download_job, - on_start=self._download_started_callback, - on_progress=self._download_progress_callback, - on_complete=self._download_complete_callback, - on_error=self._download_error_callback, - on_cancelled=self._download_cancelled_callback, - ) - + self._download_queue.submit_multifile_download(multifile_job) return install_job def _stat_size(self, path: Path) -> int: @@ -786,86 +775,59 @@ class ModelInstallService(ModelInstallServiceBase): # ------------------------------------------------------------------ # Callbacks are executed by the download queue in a separate thread # ------------------------------------------------------------------ - def _download_started_callback(self, download_job: DownloadJob) -> None: - self._logger.info(f"Model download started: {download_job.source}") + def _download_started_callback(self, download_job: MultiFileDownloadJob) -> None: with self._lock: - install_job = self._download_cache[download_job.source] + install_job = self._download_cache[download_job.id] install_job.status = InstallStatus.DOWNLOADING assert download_job.download_path - if install_job.local_path == install_job._install_tmpdir: - partial_path = download_job.download_path.relative_to(install_job._install_tmpdir) - dest_name = partial_path.parts[0] - install_job.local_path = install_job._install_tmpdir / dest_name + if install_job.local_path == install_job._install_tmpdir: # first time + install_job.local_path = download_job.download_path + install_job.total_bytes = download_job.total_bytes - # Update the total bytes count for remote sources. - if not install_job.total_bytes: - install_job.total_bytes = sum(x.total_bytes for x in install_job.download_parts) - - def _download_progress_callback(self, download_job: DownloadJob) -> None: + def _download_progress_callback(self, download_job: MultiFileDownloadJob) -> None: with self._lock: - install_job = self._download_cache[download_job.source] + install_job = self._download_cache[download_job.id] if install_job.cancelled: # This catches the case in which the caller directly calls job.cancel() - self._cancel_download_parts(install_job) + self._download_queue.cancel_job(download_job) else: # update sizes - install_job.bytes = sum(x.bytes for x in install_job.download_parts) + install_job.bytes = sum(x.bytes for x in download_job.download_parts) self._signal_job_downloading(install_job) - def _download_complete_callback(self, download_job: DownloadJob) -> None: - self._logger.info(f"Model download complete: {download_job.source}") + def _download_complete_callback(self, download_job: MultiFileDownloadJob) -> None: with self._lock: - install_job = self._download_cache[download_job.source] - - # are there any more active jobs left in this task? - if install_job.downloading and all(x.complete for x in install_job.download_parts): - self._signal_job_downloads_done(install_job) - if install_job._do_install: - self._put_in_queue(install_job) + install_job = self._download_cache.pop(download_job.id) + self._signal_job_downloads_done(install_job) + self._put_in_queue(install_job) # this starts the installation and registration # Let other threads know that the number of downloads has changed - self._download_cache.pop(download_job.source, None) self._downloads_changed_event.set() - def _download_error_callback(self, download_job: DownloadJob, excp: Optional[Exception] = None) -> None: + def _download_error_callback(self, download_job: MultiFileDownloadJob, excp: Optional[Exception] = None) -> None: with self._lock: - install_job = self._download_cache.pop(download_job.source, None) + install_job = self._download_cache.pop(download_job.id) assert install_job is not None assert excp is not None install_job.set_error(excp) - self._logger.error( - f"Cancelling {install_job.source} due to an error while downloading {download_job.source}: {str(excp)}" - ) - self._cancel_download_parts(install_job) + self._download_queue.cancel_job(download_job) # Let other threads know that the number of downloads has changed self._downloads_changed_event.set() - def _download_cancelled_callback(self, download_job: DownloadJob) -> None: + def _download_cancelled_callback(self, download_job: MultiFileDownloadJob) -> None: with self._lock: - install_job = self._download_cache.pop(download_job.source, None) + install_job = self._download_cache.pop(download_job.id, None) if not install_job: return self._downloads_changed_event.set() - self._logger.warning(f"Model download canceled: {download_job.source}") # if install job has already registered an error, then do not replace its status with cancelled if not install_job.errored: install_job.cancel() - self._cancel_download_parts(install_job) # Let other threads know that the number of downloads has changed self._downloads_changed_event.set() - def _cancel_download_parts(self, install_job: ModelInstallJob) -> None: - # on multipart downloads, _cancel_components() will get called repeatedly from the download callbacks - # do not lock here because it gets called within a locked context - for s in install_job.download_parts: - self._download_queue.cancel_job(s) - - if all(x.in_terminal_state for x in install_job.download_parts): - # When all parts have reached their terminal state, we finalize the job to clean up the temporary directory and other resources - self._put_in_queue(install_job) - # ------------------------------------------------------------------------------------------------ # Internal methods that put events on the event bus # ------------------------------------------------------------------------------------------------ @@ -877,6 +839,7 @@ class ModelInstallService(ModelInstallServiceBase): def _signal_job_downloading(self, job: ModelInstallJob) -> None: if self._event_bus: + assert job._download_job is not None parts: List[Dict[str, str | int]] = [ { "url": str(x.source), @@ -884,7 +847,7 @@ class ModelInstallService(ModelInstallServiceBase): "bytes": x.bytes, "total_bytes": x.total_bytes, } - for x in job.download_parts + for x in job._download_job.download_parts ] assert job.bytes is not None assert job.total_bytes is not None @@ -929,7 +892,13 @@ class ModelInstallService(ModelInstallServiceBase): self._event_bus.emit_model_install_cancelled(str(job.source), id=job.id) @staticmethod - def get_fetcher_from_url(url: str) -> ModelMetadataFetchBase: + def get_fetcher_from_url(url: str) -> Type[ModelMetadataFetchBase]: + """ + Return a metadata fetcher appropriate for provided url. + + This used to be more useful, but the number of supported model + sources has been reduced to HuggingFace alone. + """ if re.match(r"^https?://huggingface.co/[^/]+/[^/]+$", url.lower()): return HuggingFaceMetadataFetch raise ValueError(f"Unsupported model source: '{url}'") diff --git a/invokeai/backend/model_manager/metadata/metadata_base.py b/invokeai/backend/model_manager/metadata/metadata_base.py index 4abf020538..f9f5335d17 100644 --- a/invokeai/backend/model_manager/metadata/metadata_base.py +++ b/invokeai/backend/model_manager/metadata/metadata_base.py @@ -40,6 +40,9 @@ class RemoteModelFile(BaseModel): size: Optional[int] = Field(description="The size of this file, in bytes", default=0) sha256: Optional[str] = Field(description="SHA256 hash of this model (not always available)", default=None) + def __hash__(self) -> int: + return hash(str(self)) + class ModelMetadataBase(BaseModel): """Base class for model metadata information.""" diff --git a/tests/app/services/download/test_download_queue.py b/tests/app/services/download/test_download_queue.py index 393cd54a03..564d9c30a0 100644 --- a/tests/app/services/download/test_download_queue.py +++ b/tests/app/services/download/test_download_queue.py @@ -4,79 +4,33 @@ import re import time from contextlib import contextmanager from pathlib import Path -from typing import Generator, Optional +from typing import Any, Generator, Optional import pytest from pydantic.networks import AnyHttpUrl from requests.sessions import Session -from requests_testadapter import TestAdapter, TestSession +from requests_testadapter import TestAdapter from invokeai.app.services.config import get_config from invokeai.app.services.config.config_default import URLRegexTokenPair from invokeai.app.services.download import DownloadJob, DownloadJobStatus, DownloadQueueService, MultiFileDownloadJob -from invokeai.backend.model_manager.metadata import HuggingFaceMetadataFetch, RemoteModelFile +from invokeai.backend.model_manager.metadata import HuggingFaceMetadataFetch, ModelMetadataWithFiles, RemoteModelFile from tests.backend.model_manager.model_manager_fixtures import * # noqa F403 from tests.test_nodes import TestEventService # Prevent pytest deprecation warnings -TestAdapter.__test__ = False # type: ignore - - -@pytest.fixture -def session() -> Session: - sess = TestSession() - for i in ["12345", "9999", "54321"]: - content = ( - b"I am a safetensors file " + bytearray(i, "utf-8") + bytearray(32_000) - ) # for pause tests, must make content large - sess.mount( - f"http://www.civitai.com/models/{i}", - TestAdapter( - content, - headers={ - "Content-Length": len(content), - "Content-Disposition": f'filename="mock{i}.safetensors"', - }, - ), - ) - - sess.mount( - "http://www.huggingface.co/foo.txt", - TestAdapter( - content, - headers={ - "Content-Length": len(content), - "Content-Disposition": 'filename="foo.safetensors"', - }, - ), - ) - - # here are some malformed URLs to test - # missing the content length - sess.mount( - "http://www.civitai.com/models/missing", - TestAdapter( - b"Missing content length", - headers={ - "Content-Disposition": 'filename="missing.txt"', - }, - ), - ) - # not found test - sess.mount("http://www.civitai.com/models/broken", TestAdapter(b"Not found", status=404)) - - return sess +TestAdapter.__test__ = False @pytest.mark.timeout(timeout=10, method="thread") -def test_basic_queue_download(tmp_path: Path, session: Session) -> None: +def test_basic_queue_download(tmp_path: Path, mm2_session: Session) -> None: events = set() def event_handler(job: DownloadJob, excp: Optional[Exception] = None) -> None: events.add(job.status) queue = DownloadQueueService( - requests_session=session, + requests_session=mm2_session, ) queue.start() job = queue.download( @@ -92,6 +46,7 @@ def test_basic_queue_download(tmp_path: Path, session: Session) -> None: queue.join() assert job.status == DownloadJobStatus("completed"), "expected job status to be completed" + assert job.download_path == tmp_path / "mock12345.safetensors" assert Path(tmp_path, "mock12345.safetensors").exists(), f"expected {tmp_path}/mock12345.safetensors to exist" assert events == {DownloadJobStatus.RUNNING, DownloadJobStatus.COMPLETED} @@ -99,9 +54,9 @@ def test_basic_queue_download(tmp_path: Path, session: Session) -> None: @pytest.mark.timeout(timeout=10, method="thread") -def test_errors(tmp_path: Path, session: Session) -> None: +def test_errors(tmp_path: Path, mm2_session: Session) -> None: queue = DownloadQueueService( - requests_session=session, + requests_session=mm2_session, ) queue.start() @@ -121,10 +76,10 @@ def test_errors(tmp_path: Path, session: Session) -> None: @pytest.mark.timeout(timeout=10, method="thread") -def test_event_bus(tmp_path: Path, session: Session) -> None: +def test_event_bus(tmp_path: Path, mm2_session: Session) -> None: event_bus = TestEventService() - queue = DownloadQueueService(requests_session=session, event_bus=event_bus) + queue = DownloadQueueService(requests_session=mm2_session, event_bus=event_bus) queue.start() queue.download( source=AnyHttpUrl("http://www.civitai.com/models/12345"), @@ -157,9 +112,9 @@ def test_event_bus(tmp_path: Path, session: Session) -> None: @pytest.mark.timeout(timeout=10, method="thread") -def test_broken_callbacks(tmp_path: Path, session: Session, capsys) -> None: +def test_broken_callbacks(tmp_path: Path, mm2_session: Session, capsys) -> None: queue = DownloadQueueService( - requests_session=session, + requests_session=mm2_session, ) queue.start() @@ -189,10 +144,10 @@ def test_broken_callbacks(tmp_path: Path, session: Session, capsys) -> None: @pytest.mark.timeout(timeout=10, method="thread") -def test_cancel(tmp_path: Path, session: Session) -> None: +def test_cancel(tmp_path: Path, mm2_session: Session) -> None: event_bus = TestEventService() - queue = DownloadQueueService(requests_session=session, event_bus=event_bus) + queue = DownloadQueueService(requests_session=mm2_session, event_bus=event_bus) queue.start() cancelled = False @@ -204,9 +159,6 @@ def test_cancel(tmp_path: Path, session: Session) -> None: nonlocal cancelled cancelled = True - def handler(signum, frame): - raise TimeoutError("Join took too long to return") - job = queue.download( source=AnyHttpUrl("http://www.civitai.com/models/12345"), dest=tmp_path, @@ -223,14 +175,15 @@ def test_cancel(tmp_path: Path, session: Session) -> None: assert events[-1].payload["source"] == "http://www.civitai.com/models/12345" queue.stop() + @pytest.mark.timeout(timeout=10, method="thread") def test_multifile_download(tmp_path: Path, mm2_session: Session) -> None: fetcher = HuggingFaceMetadataFetch(mm2_session) metadata = fetcher.from_id("stabilityai/sdxl-turbo") + assert isinstance(metadata, ModelMetadataWithFiles) events = set() def event_handler(job: DownloadJob | MultiFileDownloadJob, excp: Optional[Exception] = None) -> None: - print(f"bytes = {job.bytes}") events.add(job.status) queue = DownloadQueueService( @@ -251,6 +204,7 @@ def test_multifile_download(tmp_path: Path, mm2_session: Session) -> None: assert job.status == DownloadJobStatus("completed"), "expected job status to be completed" assert job.bytes > 0, "expected download bytes to be positive" assert job.bytes == job.total_bytes, "expected download bytes to equal total bytes" + assert job.download_path == tmp_path / "sdxl-turbo" assert Path( tmp_path, "sdxl-turbo/model_index.json" ).exists(), f"expected {tmp_path}/sdxl-turbo/model_inded.json to exist" @@ -266,6 +220,7 @@ def test_multifile_download(tmp_path: Path, mm2_session: Session) -> None: def test_multifile_download_error(tmp_path: Path, mm2_session: Session) -> None: fetcher = HuggingFaceMetadataFetch(mm2_session) metadata = fetcher.from_id("stabilityai/sdxl-turbo") + assert isinstance(metadata, ModelMetadataWithFiles) events = set() def event_handler(job: DownloadJob | MultiFileDownloadJob, excp: Optional[Exception] = None) -> None: @@ -289,13 +244,14 @@ def test_multifile_download_error(tmp_path: Path, mm2_session: Session) -> None: queue.join() assert job.status == DownloadJobStatus("error"), "expected job status to be errored" + assert job.error_type is not None assert "HTTPError(NOT FOUND)" in job.error_type assert DownloadJobStatus.ERROR in events queue.stop() @pytest.mark.timeout(timeout=10, method="thread") -def test_multifile_cancel(tmp_path: Path, mm2_session: Session, monkeypatch) -> None: +def test_multifile_cancel(tmp_path: Path, mm2_session: Session, monkeypatch: Any) -> None: event_bus = TestEventService() queue = DownloadQueueService(requests_session=mm2_session, event_bus=event_bus) @@ -307,11 +263,9 @@ def test_multifile_cancel(tmp_path: Path, mm2_session: Session, monkeypatch) -> nonlocal cancelled cancelled = True - def handler(signum, frame): - raise TimeoutError("Join took too long to return") - fetcher = HuggingFaceMetadataFetch(mm2_session) metadata = fetcher.from_id("stabilityai/sdxl-turbo") + assert isinstance(metadata, ModelMetadataWithFiles) job = queue.multifile_download( parts=metadata.download_urls(session=mm2_session), @@ -327,6 +281,29 @@ def test_multifile_cancel(tmp_path: Path, mm2_session: Session, monkeypatch) -> assert "download_cancelled" in [x.event_name for x in events] queue.stop() + +def test_multifile_onefile(tmp_path: Path, mm2_session: Session) -> None: + queue = DownloadQueueService( + requests_session=mm2_session, + ) + queue.start() + job = queue.multifile_download( + parts=[ + RemoteModelFile(url=AnyHttpUrl("http://www.civitai.com/models/12345"), path=Path("mock12345.safetensors")) + ], + dest=tmp_path, + ) + assert isinstance(job, MultiFileDownloadJob), "expected the job to be of type MultiFileDownloadJobBase" + queue.join() + + assert job.status == DownloadJobStatus("completed"), "expected job status to be completed" + assert job.bytes > 0, "expected download bytes to be positive" + assert job.bytes == job.total_bytes, "expected download bytes to equal total bytes" + assert job.download_path == tmp_path / "mock12345.safetensors" + assert Path(tmp_path, "mock12345.safetensors").exists(), f"expected {tmp_path}/mock12345.safetensors to exist" + queue.stop() + + @contextmanager def clear_config() -> Generator[None, None, None]: try: @@ -335,11 +312,11 @@ def clear_config() -> Generator[None, None, None]: get_config.cache_clear() -def test_tokens(tmp_path: Path, session: Session): +def test_tokens(tmp_path: Path, mm2_session: Session): with clear_config(): config = get_config() config.remote_api_tokens = [URLRegexTokenPair(url_regex="civitai", token="cv_12345")] - queue = DownloadQueueService(requests_session=session) + queue = DownloadQueueService(requests_session=mm2_session) queue.start() # this one has an access token assigned job1 = queue.download( diff --git a/tests/app/services/model_install/test_model_install.py b/tests/app/services/model_install/test_model_install.py index ba84455240..31d09d1029 100644 --- a/tests/app/services/model_install/test_model_install.py +++ b/tests/app/services/model_install/test_model_install.py @@ -286,14 +286,36 @@ def test_huggingface_install(mm2_installer: ModelInstallServiceBase, mm2_app_con @pytest.mark.timeout(timeout=20, method="thread") -def test_huggingface_download(mm2_installer: ModelInstallServiceBase, tmp_path: Path) -> None: +def test_huggingface_repo_id(mm2_installer: ModelInstallServiceBase, mm2_app_config: InvokeAIAppConfig) -> None: + # TODO: Test subfolder download source = HFModelSource(repo_id="stabilityai/sdxl-turbo", variant=ModelRepoVariant.Default) - job = mm2_installer.download_diffusers_model(source, tmp_path) - mm2_installer.wait_for_installs(timeout=5) - print(job.local_path) - assert job.status == InstallStatus.DOWNLOADS_DONE - assert (tmp_path / "sdxl-turbo").exists() - assert (tmp_path / "sdxl-turbo" / "model_index.json").exists() + + bus = mm2_installer.event_bus + store = mm2_installer.record_store + assert isinstance(bus, EventServiceBase) + assert store is not None + + job = mm2_installer.import_model(source) + job_list = mm2_installer.wait_for_installs(timeout=10) + assert len(job_list) == 1 + assert job.complete + assert job.config_out + + key = job.config_out.key + model_record = store.get_model(key) + assert (mm2_app_config.models_path / model_record.path).exists() + assert model_record.type == ModelType.Main + assert model_record.format == ModelFormat.Diffusers + + assert hasattr(bus, "events") # the dummyeventservice has this + assert len(bus.events) >= 3 + event_names = {x.event_name for x in bus.events} + assert event_names == { + "model_install_downloading", + "model_install_downloads_done", + "model_install_running", + "model_install_completed", + } def test_404_download(mm2_installer: ModelInstallServiceBase, mm2_app_config: InvokeAIAppConfig) -> None: @@ -327,7 +349,6 @@ def test_other_error_during_install( assert job.error == "Test error" -# TODO: Fix bug in model install causing jobs to get installed multiple times then uncomment this test @pytest.mark.parametrize( "model_params", [ diff --git a/tests/backend/model_manager/model_manager_fixtures.py b/tests/backend/model_manager/model_manager_fixtures.py index 980f6ea17b..0301101a19 100644 --- a/tests/backend/model_manager/model_manager_fixtures.py +++ b/tests/backend/model_manager/model_manager_fixtures.py @@ -317,4 +317,45 @@ def mm2_session(embedding_file: Path, diffusers_dir: Path) -> Session: }, ), ) + + for i in ["12345", "9999", "54321"]: + content = ( + b"I am a safetensors file " + bytearray(i, "utf-8") + bytearray(32_000) + ) # for pause tests, must make content large + sess.mount( + f"http://www.civitai.com/models/{i}", + TestAdapter( + content, + headers={ + "Content-Length": len(content), + "Content-Disposition": f'filename="mock{i}.safetensors"', + }, + ), + ) + + sess.mount( + "http://www.huggingface.co/foo.txt", + TestAdapter( + content, + headers={ + "Content-Length": len(content), + "Content-Disposition": 'filename="foo.safetensors"', + }, + ), + ) + + # here are some malformed URLs to test + # missing the content length + sess.mount( + "http://www.civitai.com/models/missing", + TestAdapter( + b"Missing content length", + headers={ + "Content-Disposition": 'filename="missing.txt"', + }, + ), + ) + # not found test + sess.mount("http://www.civitai.com/models/broken", TestAdapter(b"Not found", status=404)) + return sess From 911a24479b15e4858beda43817d91b22e6a32b51 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Thu, 16 May 2024 07:18:33 -0400 Subject: [PATCH 024/110] add tests for model install file size reporting --- .../app/services/model_install/model_install_default.py | 9 ++++++--- tests/app/services/model_install/test_model_install.py | 5 +++++ 2 files changed, 11 insertions(+), 3 deletions(-) diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py index 2ad321c260..1d77b2c6e1 100644 --- a/invokeai/app/services/model_install/model_install_default.py +++ b/invokeai/app/services/model_install/model_install_default.py @@ -855,8 +855,8 @@ class ModelInstallService(ModelInstallServiceBase): str(job.source), local_path=job.local_path.as_posix(), parts=parts, - bytes=job.bytes, - total_bytes=job.total_bytes, + bytes=sum(x["bytes"] for x in parts), + total_bytes=sum(x["total_bytes"] for x in parts), id=job.id, ) @@ -875,7 +875,10 @@ class ModelInstallService(ModelInstallServiceBase): assert job.local_path is not None assert job.config_out is not None key = job.config_out.key - self._event_bus.emit_model_install_completed(str(job.source), key, id=job.id) + self._event_bus.emit_model_install_completed(source=str(job.source), + key=key, + id=job.id, + total_bytes=job.bytes) def _signal_job_errored(self, job: ModelInstallJob) -> None: self._logger.error(f"Model install error: {job.source}\n{job.error_type}: {job.error}") diff --git a/tests/app/services/model_install/test_model_install.py b/tests/app/services/model_install/test_model_install.py index 31d09d1029..f73b827534 100644 --- a/tests/app/services/model_install/test_model_install.py +++ b/tests/app/services/model_install/test_model_install.py @@ -317,6 +317,11 @@ def test_huggingface_repo_id(mm2_installer: ModelInstallServiceBase, mm2_app_con "model_install_completed", } + completed_events = [x for x in bus.events if x.event_name == "model_install_completed"] + downloading_events = [x for x in bus.events if x.event_name == "model_install_downloading"] + assert completed_events[0].payload["total_bytes"] == downloading_events[-1].payload["bytes"] + assert job.total_bytes == completed_events[0].payload["total_bytes"] + assert job.total_bytes == sum(x["total_bytes"] for x in downloading_events[-1].payload["parts"]) def test_404_download(mm2_installer: ModelInstallServiceBase, mm2_app_config: InvokeAIAppConfig) -> None: source = URLModelSource(url=Url("https://test.com/missing_model.safetensors")) From 2dae5eb7ad6da3fb7e90a948e903430eacc507eb Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Thu, 16 May 2024 22:26:18 -0400 Subject: [PATCH 025/110] more refactoring; HF subfolders not working --- docs/contributing/MODEL_MANAGER.md | 15 +- .../model_install/model_install_base.py | 9 +- .../model_install/model_install_default.py | 169 ++++++++++-------- .../model_records/model_records_base.py | 8 +- .../model_install/test_model_install.py | 14 +- 5 files changed, 113 insertions(+), 102 deletions(-) diff --git a/docs/contributing/MODEL_MANAGER.md b/docs/contributing/MODEL_MANAGER.md index c12046293c..d53198b98e 100644 --- a/docs/contributing/MODEL_MANAGER.md +++ b/docs/contributing/MODEL_MANAGER.md @@ -397,26 +397,25 @@ In the event you wish to create a new installer, you may use the following initialization pattern: ``` -from invokeai.app.services.config import InvokeAIAppConfig +from invokeai.app.services.config import get_config from invokeai.app.services.model_records import ModelRecordServiceSQL from invokeai.app.services.model_install import ModelInstallService from invokeai.app.services.download import DownloadQueueService -from invokeai.app.services.shared.sqlite import SqliteDatabase +from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase from invokeai.backend.util.logging import InvokeAILogger -config = InvokeAIAppConfig.get_config() -config.parse_args() +config = get_config() logger = InvokeAILogger.get_logger(config=config) -db = SqliteDatabase(config, logger) +db = SqliteDatabase(config.db_path, logger) record_store = ModelRecordServiceSQL(db) queue = DownloadQueueService() queue.start() -installer = ModelInstallService(app_config=config, +installer = ModelInstallService(app_config=config, record_store=record_store, - download_queue=queue - ) + download_queue=queue + ) installer.start() ``` diff --git a/invokeai/app/services/model_install/model_install_base.py b/invokeai/app/services/model_install/model_install_base.py index 68cf9591e0..b622c8dade 100644 --- a/invokeai/app/services/model_install/model_install_base.py +++ b/invokeai/app/services/model_install/model_install_base.py @@ -466,17 +466,14 @@ class ModelInstallServiceBase(ABC): """ @abstractmethod - def download_and_cache_ckpt( + def download_and_cache_model( self, - source: str | AnyHttpUrl, - access_token: Optional[str] = None, - timeout: int = 0, + source: str, ) -> Path: """ Download the model file located at source to the models cache and return its Path. - :param source: A Url or a string that can be converted into one. - :param access_token: Optional access token to access restricted resources. + :param source: A string representing a URL or repo_id. The model file will be downloaded into the system-wide model cache (`models/.cache`) if it isn't already there. Note that the model cache diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py index 1d77b2c6e1..a6bb7ad10d 100644 --- a/invokeai/app/services/model_install/model_install_default.py +++ b/invokeai/app/services/model_install/model_install_default.py @@ -9,7 +9,7 @@ from pathlib import Path from queue import Empty, Queue from shutil import copyfile, copytree, move, rmtree from tempfile import mkdtemp -from typing import Any, Dict, List, Optional, Type, Union +from typing import Any, Dict, List, Optional, Tuple, Type, Union import torch import yaml @@ -18,7 +18,7 @@ from pydantic.networks import AnyHttpUrl from requests import Session from invokeai.app.services.config import InvokeAIAppConfig -from invokeai.app.services.download import DownloadQueueServiceBase, MultiFileDownloadJob, TqdmProgress +from invokeai.app.services.download import DownloadQueueServiceBase, MultiFileDownloadJob from invokeai.app.services.events.events_base import EventServiceBase from invokeai.app.services.invoker import Invoker from invokeai.app.services.model_records import DuplicateModelException, ModelRecordServiceBase @@ -208,26 +208,12 @@ class ModelInstallService(ModelInstallServiceBase): access_token: Optional[str] = None, inplace: Optional[bool] = False, ) -> ModelInstallJob: - variants = "|".join(ModelRepoVariant.__members__.values()) - hf_repoid_re = f"^([^/:]+/[^/:]+)(?::({variants})?(?::/?([^:]+))?)?$" - source_obj: Optional[StringLikeSource] = None - - if Path(source).exists(): # A local file or directory - source_obj = LocalModelSource(path=Path(source), inplace=inplace) - elif match := re.match(hf_repoid_re, source): - source_obj = HFModelSource( - repo_id=match.group(1), - variant=match.group(2) if match.group(2) else None, # pass None rather than '' - subfolder=Path(match.group(3)) if match.group(3) else None, - access_token=access_token, - ) - elif re.match(r"^https?://[^/]+", source): - source_obj = URLModelSource( - url=AnyHttpUrl(source), - access_token=access_token, - ) - else: - raise ValueError(f"Unsupported model source: '{source}'") + """Install a model using pattern matching to infer the type of source.""" + source_obj = self._guess_source(source) + if isinstance(source_obj, LocalModelSource): + source_obj.inplace = inplace + elif isinstance(source_obj, HFModelSource) or isinstance(source_obj, URLModelSource): + source_obj.access_token = access_token return self.import_model(source_obj, config) def import_model(self, source: ModelSource, config: Optional[Dict[str, Any]] = None) -> ModelInstallJob: # noqa D102 @@ -383,37 +369,86 @@ class ModelInstallService(ModelInstallServiceBase): escaped_source = slugify(str(source)) return app_config.download_cache_path / escaped_source - def download_and_cache_ckpt( + def download_and_cache_model( self, - source: str | AnyHttpUrl, - access_token: Optional[str] = None, - timeout: int = 0, + source: str, ) -> Path: """Download the model file located at source to the models cache and return its Path.""" - model_path = self._download_cache_path(source, self._app_config) + model_path = self._download_cache_path(str(source), self._app_config) - # We expect the cache directory to contain one and only one downloaded file. + # We expect the cache directory to contain one and only one downloaded file or directory. # We don't know the file's name in advance, as it is set by the download # content-disposition header. if model_path.exists(): - contents = [x for x in model_path.iterdir() if x.is_file()] + contents: List[Path] = list(model_path.iterdir()) if len(contents) > 0: return contents[0] model_path.mkdir(parents=True, exist_ok=True) - job = self._download_queue.download( - source=AnyHttpUrl(str(source)), + model_source = self._guess_source(source) + remote_files, _ = self._remote_files_from_source(model_source) + job = self._download_queue.multifile_download( + parts=remote_files, dest=model_path, - access_token=access_token, - on_progress=TqdmProgress().update, ) - self._download_queue.wait_for_job(job, timeout) + files_string = "file" if len(remote_files) == 1 else "file" + self._logger.info(f"Queuing model install: {source} ({len(remote_files)} {files_string})") + self._download_queue.wait_for_job(job) if job.complete: assert job.download_path is not None return job.download_path else: raise Exception(job.error) + def _remote_files_from_source( + self, source: ModelSource + ) -> Tuple[List[RemoteModelFile], Optional[AnyModelRepoMetadata]]: + metadata = None + if isinstance(source, HFModelSource): + metadata = HuggingFaceMetadataFetch(self._session).from_id(source.repo_id, source.variant) + assert isinstance(metadata, ModelMetadataWithFiles) + return metadata.download_urls( + variant=source.variant or self._guess_variant(), + subfolder=source.subfolder, + session=self._session, + ), metadata + + if isinstance(source, URLModelSource): + try: + fetcher = self.get_fetcher_from_url(str(source.url)) + kwargs: dict[str, Any] = {"session": self._session} + metadata = fetcher(**kwargs).from_url(source.url) + assert isinstance(metadata, ModelMetadataWithFiles) + return metadata.download_urls(session=self._session), metadata + except ValueError: + pass + + return [RemoteModelFile(url=source.url, path=Path("."), size=0)], None + + raise Exception(f"No files associated with {source}") + + def _guess_source(self, source: str) -> ModelSource: + """Turn a source string into a ModelSource object.""" + variants = "|".join(ModelRepoVariant.__members__.values()) + hf_repoid_re = f"^([^/:]+/[^/:]+)(?::({variants})?(?::/?([^:]+))?)?$" + source_obj: Optional[StringLikeSource] = None + + if Path(source).exists(): # A local file or directory + source_obj = LocalModelSource(path=Path(source)) + elif match := re.match(hf_repoid_re, source): + source_obj = HFModelSource( + repo_id=match.group(1), + variant=match.group(2) if match.group(2) else None, # pass None rather than '' + subfolder=Path(match.group(3)) if match.group(3) else None, + ) + elif re.match(r"^https?://[^/]+", source): + source_obj = URLModelSource( + url=AnyHttpUrl(source), + ) + else: + raise ValueError(f"Unsupported model source: '{source}'") + return source_obj + # -------------------------------------------------------------------------------------------- # Internal functions that manage the installer threads # -------------------------------------------------------------------------------------------- @@ -650,18 +685,9 @@ class ModelInstallService(ModelInstallServiceBase): config: Optional[Dict[str, Any]] = None, ) -> ModelInstallJob: # Add user's cached access token to HuggingFace requests - source.access_token = source.access_token or HfFolder.get_token() - if not source.access_token: - self._logger.info("No HuggingFace access token present; some models may not be downloadable.") - - metadata = HuggingFaceMetadataFetch(self._session).from_id(source.repo_id, source.variant) - assert isinstance(metadata, ModelMetadataWithFiles) - remote_files = metadata.download_urls( - variant=source.variant or self._guess_variant(), - subfolder=source.subfolder, - session=self._session, - ) - + if source.access_token is None: + source.access_token = HfFolder.get_token() + remote_files, metadata = self._remote_files_from_source(source) return self._import_remote_model( source=source, config=config, @@ -674,21 +700,7 @@ class ModelInstallService(ModelInstallServiceBase): source: URLModelSource, config: Optional[Dict[str, Any]], ) -> ModelInstallJob: - # URLs from HuggingFace will be handled specially - metadata = None - fetcher = None - try: - fetcher = self.get_fetcher_from_url(str(source.url)) - except ValueError: - pass - kwargs: dict[str, Any] = {"session": self._session} - if fetcher is not None: - metadata = fetcher(**kwargs).from_url(source.url) - self._logger.debug(f"metadata={metadata}") - if metadata and isinstance(metadata, ModelMetadataWithFiles): - remote_files = metadata.download_urls(session=self._session) - else: - remote_files = [RemoteModelFile(url=source.url, path=Path("."), size=0)] + remote_files, metadata = self._remote_files_from_source(source) return self._import_remote_model( source=source, config=config, @@ -733,26 +745,17 @@ class ModelInstallService(ModelInstallServiceBase): root = Path(".") subfolder = Path(".") - # we remember the path up to the top of the destdir so that it may be - # removed safely at the end of the install process. - install_job._install_tmpdir = destdir - parts: List[RemoteModelFile] = [] for model_file in remote_files: assert install_job.total_bytes is not None assert model_file.size is not None install_job.total_bytes += model_file.size parts.append(RemoteModelFile(url=model_file.url, path=model_file.path.relative_to(subfolder))) - multifile_job = self._download_queue.multifile_download( + multifile_job = self._multifile_download( parts=parts, dest=destdir, access_token=source.access_token, - submit_job=False, - on_start=self._download_started_callback, - on_progress=self._download_progress_callback, - on_complete=self._download_complete_callback, - on_error=self._download_error_callback, - on_cancelled=self._download_cancelled_callback, + submit_job=False, # Important! Don't submit the job until we have set our _download_cache dict ) self._download_cache[multifile_job.id] = install_job install_job._download_job = multifile_job @@ -772,6 +775,21 @@ class ModelInstallService(ModelInstallServiceBase): size += sum(self._stat_size(Path(root, x)) for x in files) return size + def _multifile_download( + self, parts: List[RemoteModelFile], dest: Path, access_token: Optional[str] = None, submit_job: bool = True + ) -> MultiFileDownloadJob: + return self._download_queue.multifile_download( + parts=parts, + dest=dest, + access_token=access_token, + submit_job=submit_job, + on_start=self._download_started_callback, + on_progress=self._download_progress_callback, + on_complete=self._download_complete_callback, + on_error=self._download_error_callback, + on_cancelled=self._download_cancelled_callback, + ) + # ------------------------------------------------------------------ # Callbacks are executed by the download queue in a separate thread # ------------------------------------------------------------------ @@ -875,10 +893,9 @@ class ModelInstallService(ModelInstallServiceBase): assert job.local_path is not None assert job.config_out is not None key = job.config_out.key - self._event_bus.emit_model_install_completed(source=str(job.source), - key=key, - id=job.id, - total_bytes=job.bytes) + self._event_bus.emit_model_install_completed( + source=str(job.source), key=key, id=job.id, total_bytes=job.bytes + ) def _signal_job_errored(self, job: ModelInstallJob) -> None: self._logger.error(f"Model install error: {job.source}\n{job.error_type}: {job.error}") diff --git a/invokeai/app/services/model_records/model_records_base.py b/invokeai/app/services/model_records/model_records_base.py index 094ade6383..57531cf3c1 100644 --- a/invokeai/app/services/model_records/model_records_base.py +++ b/invokeai/app/services/model_records/model_records_base.py @@ -12,15 +12,13 @@ from pydantic import BaseModel, Field from invokeai.app.services.shared.pagination import PaginatedResults from invokeai.app.util.model_exclude_null import BaseModelExcludeNull -from invokeai.backend.model_manager import ( +from invokeai.backend.model_manager.config import ( AnyModelConfig, BaseModelType, - ModelFormat, - ModelType, -) -from invokeai.backend.model_manager.config import ( ControlAdapterDefaultSettings, MainModelDefaultSettings, + ModelFormat, + ModelType, ModelVariantType, SchedulerPredictionType, ) diff --git a/tests/app/services/model_install/test_model_install.py b/tests/app/services/model_install/test_model_install.py index f73b827534..ca8616238f 100644 --- a/tests/app/services/model_install/test_model_install.py +++ b/tests/app/services/model_install/test_model_install.py @@ -222,7 +222,7 @@ def test_delete_register( store.get_model(key) -@pytest.mark.timeout(timeout=20, method="thread") +@pytest.mark.timeout(timeout=10, method="thread") def test_simple_download(mm2_installer: ModelInstallServiceBase, mm2_app_config: InvokeAIAppConfig) -> None: source = URLModelSource(url=Url("https://www.test.foo/download/test_embedding.safetensors")) @@ -253,7 +253,7 @@ def test_simple_download(mm2_installer: ModelInstallServiceBase, mm2_app_config: ] -@pytest.mark.timeout(timeout=20, method="thread") +@pytest.mark.timeout(timeout=10, method="thread") def test_huggingface_install(mm2_installer: ModelInstallServiceBase, mm2_app_config: InvokeAIAppConfig) -> None: source = URLModelSource(url=Url("https://huggingface.co/stabilityai/sdxl-turbo")) @@ -285,9 +285,8 @@ def test_huggingface_install(mm2_installer: ModelInstallServiceBase, mm2_app_con } -@pytest.mark.timeout(timeout=20, method="thread") +@pytest.mark.timeout(timeout=10, method="thread") def test_huggingface_repo_id(mm2_installer: ModelInstallServiceBase, mm2_app_config: InvokeAIAppConfig) -> None: - # TODO: Test subfolder download source = HFModelSource(repo_id="stabilityai/sdxl-turbo", variant=ModelRepoVariant.Default) bus = mm2_installer.event_bus @@ -323,6 +322,7 @@ def test_huggingface_repo_id(mm2_installer: ModelInstallServiceBase, mm2_app_con assert job.total_bytes == completed_events[0].payload["total_bytes"] assert job.total_bytes == sum(x["total_bytes"] for x in downloading_events[-1].payload["parts"]) + def test_404_download(mm2_installer: ModelInstallServiceBase, mm2_app_config: InvokeAIAppConfig) -> None: source = URLModelSource(url=Url("https://test.com/missing_model.safetensors")) job = mm2_installer.import_model(source) @@ -371,7 +371,7 @@ def test_other_error_during_install( }, ], ) -@pytest.mark.timeout(timeout=20, method="thread") +@pytest.mark.timeout(timeout=10, method="thread") def test_heuristic_import_with_type(mm2_installer: ModelInstallServiceBase, model_params: Dict[str, str]): """Test whether or not type is respected on configs when passed to heuristic import.""" assert "name" in model_params and "type" in model_params @@ -387,7 +387,7 @@ def test_heuristic_import_with_type(mm2_installer: ModelInstallServiceBase, mode } assert "repo_id" in model_params install_job1 = mm2_installer.heuristic_import(source=model_params["repo_id"], config=config1) - mm2_installer.wait_for_job(install_job1, timeout=20) + mm2_installer.wait_for_job(install_job1, timeout=10) if model_params["type"] != "embedding": assert install_job1.errored assert install_job1.error_type == "InvalidModelConfigException" @@ -396,6 +396,6 @@ def test_heuristic_import_with_type(mm2_installer: ModelInstallServiceBase, mode assert install_job1.config_out if model_params["type"] == "embedding" else not install_job1.config_out install_job2 = mm2_installer.heuristic_import(source=model_params["repo_id"], config=config2) - mm2_installer.wait_for_job(install_job2, timeout=20) + mm2_installer.wait_for_job(install_job2, timeout=10) assert install_job2.complete assert install_job2.config_out if model_params["type"] == "embedding" else not install_job2.config_out From d968c6f379dec510eed914b185c3872d3196e7d2 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Fri, 17 May 2024 22:29:19 -0400 Subject: [PATCH 026/110] refactor multifile download code --- docs/contributing/DOWNLOAD_QUEUE.md | 63 ++++++++- docs/contributing/MODEL_MANAGER.md | 38 ++++++ .../controlnet_image_processors.py | 6 +- invokeai/app/invocations/infill.py | 2 +- invokeai/app/invocations/upscale.py | 2 +- .../model_install/model_install_default.py | 123 ++++++++++-------- .../services/model_load/model_load_base.py | 4 +- .../services/model_load/model_load_default.py | 14 +- .../model_manager/model_manager_base.py | 2 +- .../model_manager/model_manager_default.py | 56 ++++---- .../app/services/shared/invocation_context.py | 51 ++------ .../services/download/test_download_queue.py | 13 ++ .../app/services/model_load/test_load_api.py | 32 +++-- 13 files changed, 262 insertions(+), 144 deletions(-) diff --git a/docs/contributing/DOWNLOAD_QUEUE.md b/docs/contributing/DOWNLOAD_QUEUE.md index d43c670d2c..960180961e 100644 --- a/docs/contributing/DOWNLOAD_QUEUE.md +++ b/docs/contributing/DOWNLOAD_QUEUE.md @@ -128,7 +128,8 @@ The queue operates on a series of download job objects. These objects specify the source and destination of the download, and keep track of the progress of the download. -The only job type currently implemented is `DownloadJob`, a pydantic object with the +Two job types are defined. `DownloadJob` and +`MultiFileDownloadJob`. The former is a pydantic object with the following fields: | **Field** | **Type** | **Default** | **Description** | @@ -138,7 +139,7 @@ following fields: | `dest` | Path | | Where to download to | | `access_token` | str | | [optional] string containing authentication token for access | | `on_start` | Callable | | [optional] callback when the download starts | -| `on_progress` | Callable | | [optional] callback called at intervals during download progress | +| `on_progress` | Callable | | [optional] callback called at intervals during download progress | | `on_complete` | Callable | | [optional] callback called after successful download completion | | `on_error` | Callable | | [optional] callback called after an error occurs | | `id` | int | auto assigned | Job ID, an integer >= 0 | @@ -190,6 +191,33 @@ A cancelled job will have status `DownloadJobStatus.ERROR` and an `error_type` field of "DownloadJobCancelledException". In addition, the job's `cancelled` property will be set to True. +The `MultiFileDownloadJob` is used for diffusers model downloads, +which contain multiple files and directories under a common root: + +| **Field** | **Type** | **Default** | **Description** | +|----------------|-----------------|---------------|-----------------| +| _Fields passed in at job creation time_ | +| `download_parts` | Set[DownloadJob]| | Component download jobs | +| `dest` | Path | | Where to download to | +| `on_start` | Callable | | [optional] callback when the download starts | +| `on_progress` | Callable | | [optional] callback called at intervals during download progress | +| `on_complete` | Callable | | [optional] callback called after successful download completion | +| `on_error` | Callable | | [optional] callback called after an error occurs | +| `id` | int | auto assigned | Job ID, an integer >= 0 | +| _Fields updated over the course of the download task_ +| `status` | DownloadJobStatus| | Status code | +| `download_path` | Path | | Path to the root of the downloaded files | +| `bytes` | int | 0 | Bytes downloaded so far | +| `total_bytes` | int | 0 | Total size of the file at the remote site | +| `error_type` | str | | String version of the exception that caused an error during download | +| `error` | str | | String version of the traceback associated with an error | +| `cancelled` | bool | False | Set to true if the job was cancelled by the caller| + +Note that the MultiFileDownloadJob does not support the `priority`, +`job_started`, `job_ended` or `content_type` attributes. You can get +these from the individual download jobs in `download_parts`. + + ### Callbacks Download jobs can be associated with a series of callbacks, each with @@ -251,11 +279,40 @@ jobs using `list_jobs()`, fetch a single job by its with running jobs with `cancel_all_jobs()`, and wait for all jobs to finish with `join()`. -#### job = queue.download(source, dest, priority, access_token) +#### job = queue.download(source, dest, priority, access_token, on_start, on_progress, on_complete, on_cancelled, on_error) Create a new download job and put it on the queue, returning the DownloadJob object. +#### multifile_job = queue.multifile_download(parts, dest, access_token, on_start, on_progress, on_complete, on_cancelled, on_error) + +This is similar to download(), but instead of taking a single source, +it accepts a `parts` argument consisting of a list of +`RemoteModelFile` objects. Each part corresponds to a URL/Path pair, +where the URL is the location of the remote file, and the Path is the +destination. + +`RemoteModelFile` can be imported from `invokeai.backend.model_manager.metadata`, and +consists of a url/path pair. Note that the path *must* be relative. + +The method returns a `MultiFileDownloadJob`. + + +``` +from invokeai.backend.model_manager.metadata import RemoteModelFile +remote_file_1 = RemoteModelFile(url='http://www.foo.bar/my/pytorch_model.safetensors'', + path='my_model/textencoder/pytorch_model.safetensors' + ) +remote_file_2 = RemoteModelFile(url='http://www.bar.baz/vae.ckpt', + path='my_model/vae/diffusers_model.safetensors' + ) +job = queue.multifile_download(parts=[remote_file_1, remote_file_2], + dest='/tmp/downloads', + on_progress=TqdmProgress().update) +queue.wait_for_job(job) +print(f"The files were downloaded to {job.download_path}") +``` + #### jobs = queue.list_jobs() Return a list of all active and inactive `DownloadJob`s. diff --git a/docs/contributing/MODEL_MANAGER.md b/docs/contributing/MODEL_MANAGER.md index d53198b98e..fbc9079d49 100644 --- a/docs/contributing/MODEL_MANAGER.md +++ b/docs/contributing/MODEL_MANAGER.md @@ -1577,3 +1577,41 @@ This method takes a model key, looks it up using the `ModelRecordServiceBase` object in `mm.store`, and passes the returned model configuration to `load_model_by_config()`. It may raise a `NotImplementedException`. + +## Invocation Context Model Manager API + +Within invocations, the following methods are available from the +`InvocationContext` object: + +### context.download_and_cache_model(source) -> Path + +This method accepts a `source` of a model, downloads and caches it +locally, and returns a Path to the local model. The source can be a +local file or directory, a URL, or a HuggingFace repo_id. + +In the case of HuggingFace repo_id, the following variants are +recognized: + +* stabilityai/stable-diffusion-v4 -- default model +* stabilityai/stable-diffusion-v4:fp16 -- fp16 variant +* stabilityai/stable-diffusion-v4:fp16:vae -- the fp16 vae subfolder +* stabilityai/stable-diffusion-v4:onnx:vae -- the onnx variant vae subfolder + +You can also point at an arbitrary individual file within a repo_id +directory using this syntax: + +* stabilityai/stable-diffusion-v4::/checkpoints/sd4.safetensors + +### context.load_and_cache_model(source, [loader]) -> LoadedModel + +This method takes a model source, downloads it, caches it, and then +loads it into the RAM cache for use in inference. The optional loader +is a Callable that accepts a Path to the object, and returns a +`Dict[str, torch.Tensor]`. If no loader is provided, then the method +will use `torch.load()` for a .ckpt or .bin checkpoint file, +`safetensors.torch.load_file()` for a safetensors checkpoint file, or +`*.from_pretrained()` for a directory that looks like a +diffusers directory. + + + diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py index 971179ac93..e69f4b54ad 100644 --- a/invokeai/app/invocations/controlnet_image_processors.py +++ b/invokeai/app/invocations/controlnet_image_processors.py @@ -611,7 +611,7 @@ class DepthAnythingImageProcessorInvocation(ImageProcessorInvocation): model_path, model_size=self.model_size, device=TorchDevice.choose_torch_device() ) - with context.models.load_ckpt_from_url(source=DEPTH_ANYTHING_MODELS[self.model_size], loader=loader) as model: + with context.models.load_and_cache_model(source=DEPTH_ANYTHING_MODELS[self.model_size], loader=loader) as model: depth_anything_detector = DepthAnythingDetector(model, TorchDevice.choose_torch_device()) processed_image = depth_anything_detector(image=image, resolution=self.resolution) return processed_image @@ -634,8 +634,8 @@ class DWOpenposeImageProcessorInvocation(ImageProcessorInvocation): def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: mm = context.models - onnx_det = mm.download_and_cache_ckpt(DWPOSE_MODELS["yolox_l.onnx"]) - onnx_pose = mm.download_and_cache_ckpt(DWPOSE_MODELS["dw-ll_ucoco_384.onnx"]) + onnx_det = mm.download_and_cache_model(DWPOSE_MODELS["yolox_l.onnx"]) + onnx_pose = mm.download_and_cache_model(DWPOSE_MODELS["dw-ll_ucoco_384.onnx"]) dw_openpose = DWOpenposeDetector(onnx_det=onnx_det, onnx_pose=onnx_pose) processed_image = dw_openpose( diff --git a/invokeai/app/invocations/infill.py b/invokeai/app/invocations/infill.py index f8358d1df5..ddd11cf93f 100644 --- a/invokeai/app/invocations/infill.py +++ b/invokeai/app/invocations/infill.py @@ -133,7 +133,7 @@ class LaMaInfillInvocation(InfillImageProcessorInvocation): """Infills transparent areas of an image using the LaMa model""" def infill(self, image: Image.Image, context: InvocationContext): - with context.models.load_ckpt_from_url( + with context.models.load_and_cache_model( source="https://github.com/Sanster/models/releases/download/add_big_lama/big-lama.pt", loader=LaMA.load_jit_model, ) as model: diff --git a/invokeai/app/invocations/upscale.py b/invokeai/app/invocations/upscale.py index 29cf7819de..670082f120 100644 --- a/invokeai/app/invocations/upscale.py +++ b/invokeai/app/invocations/upscale.py @@ -91,7 +91,7 @@ class ESRGANInvocation(BaseInvocation, WithMetadata, WithBoard): context.logger.error(msg) raise ValueError(msg) - loadnet = context.models.load_ckpt_from_url( + loadnet = context.models.load_and_cache_model( source=ESRGAN_MODEL_URLS[self.model_name], ) diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py index a6bb7ad10d..cde9a6502e 100644 --- a/invokeai/app/services/model_install/model_install_default.py +++ b/invokeai/app/services/model_install/model_install_default.py @@ -387,12 +387,13 @@ class ModelInstallService(ModelInstallServiceBase): model_path.mkdir(parents=True, exist_ok=True) model_source = self._guess_source(source) remote_files, _ = self._remote_files_from_source(model_source) - job = self._download_queue.multifile_download( - parts=remote_files, + job = self._multifile_download( dest=model_path, + remote_files=remote_files, + subfolder=model_source.subfolder if isinstance(model_source, HFModelSource) else None, ) - files_string = "file" if len(remote_files) == 1 else "file" - self._logger.info(f"Queuing model install: {source} ({len(remote_files)} {files_string})") + files_string = "file" if len(remote_files) == 1 else "files" + self._logger.info(f"Queuing model download: {source} ({len(remote_files)} {files_string})") self._download_queue.wait_for_job(job) if job.complete: assert job.download_path is not None @@ -734,26 +735,12 @@ class ModelInstallService(ModelInstallServiceBase): ) # remember the temporary directory for later removal install_job._install_tmpdir = destdir + install_job.total_bytes = sum((x.size or 0) for x in remote_files) - # In the event that there is a subfolder specified in the source, - # we need to remove it from the destination path in order to avoid - # creating unwanted subfolders - if isinstance(source, HFModelSource) and source.subfolder: - root = Path(remote_files[0].path.parts[0]) - subfolder = root / source.subfolder - else: - root = Path(".") - subfolder = Path(".") - - parts: List[RemoteModelFile] = [] - for model_file in remote_files: - assert install_job.total_bytes is not None - assert model_file.size is not None - install_job.total_bytes += model_file.size - parts.append(RemoteModelFile(url=model_file.url, path=model_file.path.relative_to(subfolder))) multifile_job = self._multifile_download( - parts=parts, + remote_files=remote_files, dest=destdir, + subfolder=source.subfolder if isinstance(source, HFModelSource) else None, access_token=source.access_token, submit_job=False, # Important! Don't submit the job until we have set our _download_cache dict ) @@ -776,8 +763,35 @@ class ModelInstallService(ModelInstallServiceBase): return size def _multifile_download( - self, parts: List[RemoteModelFile], dest: Path, access_token: Optional[str] = None, submit_job: bool = True + self, + remote_files: List[RemoteModelFile], + dest: Path, + subfolder: Optional[Path] = None, + access_token: Optional[str] = None, + submit_job: bool = True, ) -> MultiFileDownloadJob: + # HuggingFace repo subfolders are a little tricky. If the name of the model is "sdxl-turbo", and + # we are installing the "vae" subfolder, we do not want to create an additional folder level, such + # as "sdxl-turbo/vae", nor do we want to put the contents of the vae folder directly into "sdxl-turbo". + # So what we do is to synthesize a folder named "sdxl-turbo_vae" here. + if subfolder: + top = Path(remote_files[0].path.parts[0]) # e.g. "sdxl-turbo/" + path_to_remove = top / subfolder.parts[-1] # sdxl-turbo/vae/ + path_to_add = Path(f"{top}_{subfolder}") + else: + path_to_remove = Path(".") + path_to_add = Path(".") + + parts: List[RemoteModelFile] = [] + for model_file in remote_files: + assert model_file.size is not None + parts.append( + RemoteModelFile( + url=model_file.url, # if a subfolder, then sdxl-turbo_vae/config.json + path=path_to_add / model_file.path.relative_to(path_to_remove), + ) + ) + return self._download_queue.multifile_download( parts=parts, dest=dest, @@ -795,56 +809,53 @@ class ModelInstallService(ModelInstallServiceBase): # ------------------------------------------------------------------ def _download_started_callback(self, download_job: MultiFileDownloadJob) -> None: with self._lock: - install_job = self._download_cache[download_job.id] - install_job.status = InstallStatus.DOWNLOADING + if install_job := self._download_cache.get(download_job.id, None): + install_job.status = InstallStatus.DOWNLOADING - assert download_job.download_path - if install_job.local_path == install_job._install_tmpdir: # first time - install_job.local_path = download_job.download_path - install_job.total_bytes = download_job.total_bytes + assert download_job.download_path + if install_job.local_path == install_job._install_tmpdir: # first time + install_job.local_path = download_job.download_path + install_job.total_bytes = download_job.total_bytes def _download_progress_callback(self, download_job: MultiFileDownloadJob) -> None: with self._lock: - install_job = self._download_cache[download_job.id] - if install_job.cancelled: # This catches the case in which the caller directly calls job.cancel() - self._download_queue.cancel_job(download_job) - else: - # update sizes - install_job.bytes = sum(x.bytes for x in download_job.download_parts) - self._signal_job_downloading(install_job) + if install_job := self._download_cache.get(download_job.id, None): + if install_job.cancelled: # This catches the case in which the caller directly calls job.cancel() + self._download_queue.cancel_job(download_job) + else: + # update sizes + install_job.bytes = sum(x.bytes for x in download_job.download_parts) + self._signal_job_downloading(install_job) def _download_complete_callback(self, download_job: MultiFileDownloadJob) -> None: with self._lock: - install_job = self._download_cache.pop(download_job.id) - self._signal_job_downloads_done(install_job) - self._put_in_queue(install_job) # this starts the installation and registration + if install_job := self._download_cache.pop(download_job.id, None): + self._signal_job_downloads_done(install_job) + self._put_in_queue(install_job) # this starts the installation and registration - # Let other threads know that the number of downloads has changed - self._downloads_changed_event.set() + # Let other threads know that the number of downloads has changed + self._downloads_changed_event.set() def _download_error_callback(self, download_job: MultiFileDownloadJob, excp: Optional[Exception] = None) -> None: with self._lock: - install_job = self._download_cache.pop(download_job.id) - assert install_job is not None - assert excp is not None - install_job.set_error(excp) - self._download_queue.cancel_job(download_job) + if install_job := self._download_cache.pop(download_job.id, None): + assert excp is not None + install_job.set_error(excp) + self._download_queue.cancel_job(download_job) - # Let other threads know that the number of downloads has changed - self._downloads_changed_event.set() + # Let other threads know that the number of downloads has changed + self._downloads_changed_event.set() def _download_cancelled_callback(self, download_job: MultiFileDownloadJob) -> None: with self._lock: - install_job = self._download_cache.pop(download_job.id, None) - if not install_job: - return - self._downloads_changed_event.set() - # if install job has already registered an error, then do not replace its status with cancelled - if not install_job.errored: - install_job.cancel() + if install_job := self._download_cache.pop(download_job.id, None): + self._downloads_changed_event.set() + # if install job has already registered an error, then do not replace its status with cancelled + if not install_job.errored: + install_job.cancel() - # Let other threads know that the number of downloads has changed - self._downloads_changed_event.set() + # Let other threads know that the number of downloads has changed + self._downloads_changed_event.set() # ------------------------------------------------------------------------------------------------ # Internal methods that put events on the event bus diff --git a/invokeai/app/services/model_load/model_load_base.py b/invokeai/app/services/model_load/model_load_base.py index 32fc62fa5b..7de36793fb 100644 --- a/invokeai/app/services/model_load/model_load_base.py +++ b/invokeai/app/services/model_load/model_load_base.py @@ -43,11 +43,11 @@ class ModelLoadServiceBase(ABC): """Return the checkpoint convert cache used by this loader.""" @abstractmethod - def load_ckpt_from_path( + def load_model_from_path( self, model_path: Path, loader: Optional[Callable[[Path], Dict[str, Tensor]]] = None ) -> LoadedModel: """ - Load the checkpoint-format model file located at the indicated Path. + Load the model file or directory located at the indicated Path. This will load an arbitrary model file into the RAM cache. If the optional loader argument is provided, the loader will be invoked to load the model into diff --git a/invokeai/app/services/model_load/model_load_default.py b/invokeai/app/services/model_load/model_load_default.py index af211c260e..cd14235ee0 100644 --- a/invokeai/app/services/model_load/model_load_default.py +++ b/invokeai/app/services/model_load/model_load_default.py @@ -20,6 +20,8 @@ from invokeai.backend.model_manager.load import ( ) from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase +from invokeai.backend.model_manager.load.model_loaders.generic_diffusers import GenericDiffusersLoader +from invokeai.backend.util.devices import TorchDevice from invokeai.backend.util.logging import InvokeAILogger from .model_load_base import ModelLoadServiceBase @@ -94,7 +96,7 @@ class ModelLoadService(ModelLoadServiceBase): ) return loaded_model - def load_ckpt_from_path( + def load_model_from_path( self, model_path: Path, loader: Optional[Callable[[Path], Dict[str, Tensor]]] = None ) -> LoadedModel: """ @@ -128,6 +130,16 @@ class ModelLoadService(ModelLoadServiceBase): result: Dict[str, Tensor] = torch_load(checkpoint, map_location="cpu") return result + def diffusers_load_directory(directory: Path) -> AnyModel: + load_class = GenericDiffusersLoader( + app_config=self._app_config, + logger=self._logger, + ram_cache=self._ram_cache, + convert_cache=self.convert_cache, + ).get_hf_load_class(directory) + result: AnyModel = load_class.from_pretrained(model_path, torch_dtype=TorchDevice.choose_torch_dtype()) + return result + if loader is None: loader = ( torch_load_file diff --git a/invokeai/app/services/model_manager/model_manager_base.py b/invokeai/app/services/model_manager/model_manager_base.py index d16c00302e..063979ebe6 100644 --- a/invokeai/app/services/model_manager/model_manager_base.py +++ b/invokeai/app/services/model_manager/model_manager_base.py @@ -72,7 +72,7 @@ class ModelManagerServiceBase(ABC): pass @abstractmethod - def load_ckpt_from_url( + def load_model_from_url( self, source: str | AnyHttpUrl, loader: Optional[Callable[[Path], Dict[str, torch.Tensor]]] = None, diff --git a/invokeai/app/services/model_manager/model_manager_default.py b/invokeai/app/services/model_manager/model_manager_default.py index ed274266f3..dd78f1f3b2 100644 --- a/invokeai/app/services/model_manager/model_manager_default.py +++ b/invokeai/app/services/model_manager/model_manager_default.py @@ -64,6 +64,34 @@ class ModelManagerService(ModelManagerServiceBase): if hasattr(service, "stop"): service.stop(invoker) + def load_model_from_url( + self, + source: str | AnyHttpUrl, + loader: Optional[Callable[[Path], Dict[str, torch.Tensor]]] = None, + ) -> LoadedModel: + """ + Download, cache, and Load the model file located at the indicated URL. + + This will check the model download cache for the model designated + by the provided URL and download it if needed using download_and_cache_ckpt(). + It will then load the model into the RAM cache. If the optional loader + argument is provided, the loader will be invoked to load the model into + memory. Otherwise the method will call safetensors.torch.load_file() or + torch.load() as appropriate to the file suffix. + + Be aware that the LoadedModel object will have a `config` attribute of None. + + Args: + source: A URL or a string that can be converted in one. Repo_ids + do not work here. + loader: A Callable that expects a Path and returns a Dict[str|int, Any] + + Returns: + A LoadedModel object. + """ + model_path = self.install.download_and_cache_model(source=str(source)) + return self.load.load_model_from_path(model_path=model_path, loader=loader) + @classmethod def build_model_manager( cls, @@ -102,31 +130,3 @@ class ModelManagerService(ModelManagerServiceBase): event_bus=events, ) return cls(store=model_record_service, install=installer, load=loader) - - def load_ckpt_from_url( - self, - source: str | AnyHttpUrl, - loader: Optional[Callable[[Path], Dict[str, torch.Tensor]]] = None, - ) -> LoadedModel: - """ - Download, cache, and Load the model file located at the indicated URL. - - This will check the model download cache for the model designated - by the provided URL and download it if needed using download_and_cache_ckpt(). - It will then load the model into the RAM cache. If the optional loader - argument is provided, the loader will be invoked to load the model into - memory. Otherwise the method will call safetensors.torch.load_file() or - torch.load() as appropriate to the file suffix. - - Be aware that the LoadedModel object will have a `config` attribute of None. - - Args: - source: A URL or a string that can be converted in one. Repo_ids - do not work here. - loader: A Callable that expects a Path and returns a Dict[str|int, Any] - - Returns: - A LoadedModel object. - """ - model_path = self.install.download_and_cache_ckpt(source=source) - return self.load.load_ckpt_from_path(model_path=model_path, loader=loader) diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py index c7602760f7..32d32e227b 100644 --- a/invokeai/app/services/shared/invocation_context.py +++ b/invokeai/app/services/shared/invocation_context.py @@ -435,11 +435,9 @@ class ModelsInterface(InvocationContextInterface): ) return result - def download_and_cache_ckpt( + def download_and_cache_model( self, source: str | AnyHttpUrl, - access_token: Optional[str] = None, - timeout: Optional[int] = 0, ) -> Path: """ Download the model file located at source to the models cache and return its Path. @@ -449,12 +447,7 @@ class ModelsInterface(InvocationContextInterface): installed, the cached path will be returned. Otherwise it will be downloaded. Args: - source: A URL or a string that can be converted in one. Repo_ids - do not work here. - access_token: Optional access token for restricted resources. - timeout: Wait up to the indicated number of seconds before timing - out long downloads. - + source: A model path, URL or repo_id. Result: Path to the downloaded model @@ -463,39 +456,14 @@ class ModelsInterface(InvocationContextInterface): TimeoutError """ installer = self._services.model_manager.install - path: Path = installer.download_and_cache_ckpt( + path: Path = installer.download_and_cache_model( source=source, - access_token=access_token, - timeout=timeout, ) return path - def load_ckpt_from_path( - self, model_path: Path, loader: Optional[Callable[[Path], Dict[str, torch.Tensor]]] = None - ) -> LoadedModel: - """ - Load the checkpoint-format model file located at the indicated Path. - - This will load an arbitrary model file into the RAM cache. If the optional loader - argument is provided, the loader will be invoked to load the model into - memory. Otherwise the method will call safetensors.torch.load_file() or - torch.load() as appropriate to the file suffix. - - Be aware that the LoadedModel object will have a `config` attribute of None. - - Args: - model_path: A pathlib.Path to a checkpoint-style models file - loader: A Callable that expects a Path and returns a Dict[str|int, Any] - - Returns: - A LoadedModel object. - """ - result: LoadedModel = self._services.model_manager.load.load_ckpt_from_path(model_path, loader=loader) - return result - - def load_ckpt_from_url( + def load_and_cache_model( self, - source: str | AnyHttpUrl, + source: Path | str | AnyHttpUrl, loader: Optional[Callable[[Path], Dict[str, torch.Tensor]]] = None, ) -> LoadedModel: """ @@ -511,14 +479,17 @@ class ModelsInterface(InvocationContextInterface): Be aware that the LoadedModel object will have a `config` attribute of None. Args: - source: A URL or a string that can be converted in one. Repo_ids - do not work here. + source: A model Path, URL, or repoid. loader: A Callable that expects a Path and returns a Dict[str|int, Any] Returns: A LoadedModel object. """ - result: LoadedModel = self._services.model_manager.load_ckpt_from_url(source=source, loader=loader) + result: LoadedModel = ( + self._services.model_manager.load.load_model_from_path(model_path=source, loader=loader) + if isinstance(source, Path) + else self._services.model_manager.load_model_from_url(source=source, loader=loader) + ) return result diff --git a/tests/app/services/download/test_download_queue.py b/tests/app/services/download/test_download_queue.py index 564d9c30a0..c9317163c8 100644 --- a/tests/app/services/download/test_download_queue.py +++ b/tests/app/services/download/test_download_queue.py @@ -304,6 +304,19 @@ def test_multifile_onefile(tmp_path: Path, mm2_session: Session) -> None: queue.stop() +def test_multifile_no_rel_paths(tmp_path: Path, mm2_session: Session) -> None: + queue = DownloadQueueService( + requests_session=mm2_session, + ) + + with pytest.raises(AssertionError) as error: + queue.multifile_download( + parts=[RemoteModelFile(url=AnyHttpUrl("http://www.civitai.com/models/12345"), path=Path("/etc/passwd"))], + dest=tmp_path, + ) + assert str(error.value) == "only relative download paths accepted" + + @contextmanager def clear_config() -> Generator[None, None, None]: try: diff --git a/tests/app/services/model_load/test_load_api.py b/tests/app/services/model_load/test_load_api.py index 7eb09fb375..bd3a67a894 100644 --- a/tests/app/services/model_load/test_load_api.py +++ b/tests/app/services/model_load/test_load_api.py @@ -24,7 +24,7 @@ def mock_context( def test_download_and_cache(mock_context: InvocationContext, mm2_root_dir: Path) -> None: - downloaded_path = mock_context.models.download_and_cache_ckpt( + downloaded_path = mock_context.models.download_and_cache_model( "https://www.test.foo/download/test_embedding.safetensors" ) assert downloaded_path.is_file() @@ -32,24 +32,24 @@ def test_download_and_cache(mock_context: InvocationContext, mm2_root_dir: Path) assert downloaded_path.name == "test_embedding.safetensors" assert downloaded_path.parent.parent == mm2_root_dir / "models/.download_cache" - downloaded_path_2 = mock_context.models.download_and_cache_ckpt( + downloaded_path_2 = mock_context.models.download_and_cache_model( "https://www.test.foo/download/test_embedding.safetensors" ) assert downloaded_path == downloaded_path_2 def test_load_from_path(mock_context: InvocationContext, embedding_file: Path) -> None: - downloaded_path = mock_context.models.download_and_cache_ckpt( + downloaded_path = mock_context.models.download_and_cache_model( "https://www.test.foo/download/test_embedding.safetensors" ) - loaded_model_1 = mock_context.models.load_ckpt_from_path(downloaded_path) + loaded_model_1 = mock_context.models.load_and_cache_model(downloaded_path) assert isinstance(loaded_model_1, LoadedModel) - loaded_model_2 = mock_context.models.load_ckpt_from_path(downloaded_path) + loaded_model_2 = mock_context.models.load_and_cache_model(downloaded_path) assert isinstance(loaded_model_2, LoadedModel) assert loaded_model_1.model is loaded_model_2.model - loaded_model_3 = mock_context.models.load_ckpt_from_path(embedding_file) + loaded_model_3 = mock_context.models.load_and_cache_model(embedding_file) assert isinstance(loaded_model_3, LoadedModel) assert loaded_model_1.model is not loaded_model_3.model assert isinstance(loaded_model_1.model, dict) @@ -58,9 +58,25 @@ def test_load_from_path(mock_context: InvocationContext, embedding_file: Path) - def test_download_and_load(mock_context: InvocationContext) -> None: - loaded_model_1 = mock_context.models.load_ckpt_from_url("https://www.test.foo/download/test_embedding.safetensors") + loaded_model_1 = mock_context.models.load_and_cache_model( + "https://www.test.foo/download/test_embedding.safetensors" + ) assert isinstance(loaded_model_1, LoadedModel) - loaded_model_2 = mock_context.models.load_ckpt_from_url("https://www.test.foo/download/test_embedding.safetensors") + loaded_model_2 = mock_context.models.load_and_cache_model( + "https://www.test.foo/download/test_embedding.safetensors" + ) assert isinstance(loaded_model_2, LoadedModel) assert loaded_model_1.model is loaded_model_2.model # should be cached copy + + +def test_download_diffusers(mock_context: InvocationContext) -> None: + model_path = mock_context.models.download_and_cache_model("stabilityai/sdxl-turbo") + assert (model_path / "model_index.json").exists() + assert (model_path / "vae").is_dir() + + +def test_download_diffusers_subfolder(mock_context: InvocationContext) -> None: + model_path = mock_context.models.download_and_cache_model("stabilityai/sdxl-turbo::vae") + assert model_path.is_dir() + assert (model_path / "diffusion_pytorch_model.fp16.safetensors").exists() From 8aebc29b91d0723848aafe04b2f84ff015e42ade Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Fri, 17 May 2024 22:48:54 -0400 Subject: [PATCH 027/110] fix test to run on 32bit cpu --- tests/app/services/model_load/test_load_api.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/app/services/model_load/test_load_api.py b/tests/app/services/model_load/test_load_api.py index bd3a67a894..57d0fed341 100644 --- a/tests/app/services/model_load/test_load_api.py +++ b/tests/app/services/model_load/test_load_api.py @@ -79,4 +79,4 @@ def test_download_diffusers(mock_context: InvocationContext) -> None: def test_download_diffusers_subfolder(mock_context: InvocationContext) -> None: model_path = mock_context.models.download_and_cache_model("stabilityai/sdxl-turbo::vae") assert model_path.is_dir() - assert (model_path / "diffusion_pytorch_model.fp16.safetensors").exists() + assert (model_path / "diffusion_pytorch_model.fp16.safetensors").exists() or (model_path / "diffusion_pytorch_model.safetensors").exists() From e77c7e40b7981d04f21cbb1ec6258d9c632ce0dc Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Fri, 17 May 2024 22:53:45 -0400 Subject: [PATCH 028/110] fix ruff error --- tests/app/services/model_load/test_load_api.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/tests/app/services/model_load/test_load_api.py b/tests/app/services/model_load/test_load_api.py index 57d0fed341..2af321d60f 100644 --- a/tests/app/services/model_load/test_load_api.py +++ b/tests/app/services/model_load/test_load_api.py @@ -79,4 +79,6 @@ def test_download_diffusers(mock_context: InvocationContext) -> None: def test_download_diffusers_subfolder(mock_context: InvocationContext) -> None: model_path = mock_context.models.download_and_cache_model("stabilityai/sdxl-turbo::vae") assert model_path.is_dir() - assert (model_path / "diffusion_pytorch_model.fp16.safetensors").exists() or (model_path / "diffusion_pytorch_model.safetensors").exists() + assert (model_path / "diffusion_pytorch_model.fp16.safetensors").exists() or ( + model_path / "diffusion_pytorch_model.safetensors" + ).exists() From cd12ca6e85c5fd9836da847abccc743024b3289b Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Mon, 27 May 2024 22:40:01 -0400 Subject: [PATCH 029/110] add migration_11; fix typo --- invokeai/app/services/model_install/model_install_default.py | 5 +++-- invokeai/app/services/shared/sqlite/sqlite_util.py | 2 ++ 2 files changed, 5 insertions(+), 2 deletions(-) diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py index c78a09ce87..cd4bce4108 100644 --- a/invokeai/app/services/model_install/model_install_default.py +++ b/invokeai/app/services/model_install/model_install_default.py @@ -750,8 +750,8 @@ class ModelInstallService(ModelInstallServiceBase): self._download_cache[multifile_job.id] = install_job install_job._download_job = multifile_job - files_string = "file" if len(remote_files) == 1 else "file" - self._logger.info(f"Queuing model install: {source} ({len(remote_files)} {files_string})") + files_string = "file" if len(remote_files) == 1 else "files" + self._logger.info(f"Queueing model install: {source} ({len(remote_files)} {files_string})") self._logger.debug(f"remote_files={remote_files}") self._download_queue.submit_multifile_download(multifile_job) return install_job @@ -828,6 +828,7 @@ class ModelInstallService(ModelInstallServiceBase): else: # update sizes install_job.bytes = sum(x.bytes for x in download_job.download_parts) + install_job.total_bytes = sum(x.total_bytes for x in download_job.download_parts) install_job.download_parts = download_job.download_parts self._signal_job_downloading(install_job) diff --git a/invokeai/app/services/shared/sqlite/sqlite_util.py b/invokeai/app/services/shared/sqlite/sqlite_util.py index cadf09f457..3b5f447306 100644 --- a/invokeai/app/services/shared/sqlite/sqlite_util.py +++ b/invokeai/app/services/shared/sqlite/sqlite_util.py @@ -13,6 +13,7 @@ from invokeai.app.services.shared.sqlite_migrator.migrations.migration_7 import from invokeai.app.services.shared.sqlite_migrator.migrations.migration_8 import build_migration_8 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_9 import build_migration_9 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_10 import build_migration_10 +from invokeai.app.services.shared.sqlite_migrator.migrations.migration_11 import build_migration_11 from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_impl import SqliteMigrator @@ -43,6 +44,7 @@ def init_db(config: InvokeAIAppConfig, logger: Logger, image_files: ImageFileSto migrator.register_migration(build_migration_8(app_config=config)) migrator.register_migration(build_migration_9()) migrator.register_migration(build_migration_10()) + migrator.register_migration(build_migration_11(app_config=config, logger=logger)) migrator.run_migrations() return db From ead1748c544696faf49c8e0d73366feaf34463a9 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Tue, 28 May 2024 19:30:42 -0400 Subject: [PATCH 030/110] issue a download progress event when install download starts --- .../services/model_install/model_install_default.py | 8 +++++--- .../app/services/model_install/test_model_install.py | 11 ++++++----- 2 files changed, 11 insertions(+), 8 deletions(-) diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py index cd4bce4108..3b8a408e97 100644 --- a/invokeai/app/services/model_install/model_install_default.py +++ b/invokeai/app/services/model_install/model_install_default.py @@ -815,10 +815,13 @@ class ModelInstallService(ModelInstallServiceBase): if install_job := self._download_cache.get(download_job.id, None): install_job.status = InstallStatus.DOWNLOADING - assert download_job.download_path if install_job.local_path == install_job._install_tmpdir: # first time + assert download_job.download_path install_job.local_path = download_job.download_path - install_job.total_bytes = download_job.total_bytes + install_job.download_parts = download_job.download_parts + install_job.bytes = sum(x.bytes for x in download_job.download_parts) + install_job.total_bytes = download_job.total_bytes + self._signal_job_downloading(install_job) def _download_progress_callback(self, download_job: MultiFileDownloadJob) -> None: with self._lock: @@ -829,7 +832,6 @@ class ModelInstallService(ModelInstallServiceBase): # update sizes install_job.bytes = sum(x.bytes for x in download_job.download_parts) install_job.total_bytes = sum(x.total_bytes for x in download_job.download_parts) - install_job.download_parts = download_job.download_parts self._signal_job_downloading(install_job) def _download_complete_callback(self, download_job: MultiFileDownloadJob) -> None: diff --git a/tests/app/services/model_install/test_model_install.py b/tests/app/services/model_install/test_model_install.py index 5c9f908ccc..9602a79a27 100644 --- a/tests/app/services/model_install/test_model_install.py +++ b/tests/app/services/model_install/test_model_install.py @@ -251,11 +251,12 @@ def test_simple_download(mm2_installer: ModelInstallServiceBase, mm2_app_config: model_record = store.get_model(key) assert (mm2_app_config.models_path / model_record.path).exists() - assert len(bus.events) == 4 - assert isinstance(bus.events[0], ModelInstallDownloadProgressEvent) - assert isinstance(bus.events[1], ModelInstallDownloadsCompleteEvent) - assert isinstance(bus.events[2], ModelInstallStartedEvent) - assert isinstance(bus.events[3], ModelInstallCompleteEvent) + assert len(bus.events) == 5 + assert isinstance(bus.events[0], ModelInstallDownloadProgressEvent) # download starts + assert isinstance(bus.events[1], ModelInstallDownloadProgressEvent) # download progresses + assert isinstance(bus.events[2], ModelInstallDownloadsCompleteEvent) # download completed + assert isinstance(bus.events[3], ModelInstallStartedEvent) # install started + assert isinstance(bus.events[4], ModelInstallCompleteEvent) # install completed @pytest.mark.timeout(timeout=10, method="thread") From 132bbf330a0218549b773bae7e5d8f36cd4c6e29 Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 3 Jun 2024 08:35:23 +1000 Subject: [PATCH 031/110] tidy(app): remove unnecessary changes in invocation_context - Any mypy issues are a misconfiguration of mypy - Use simple conditionals instead of ternaries - Consistent & standards-compliant docstring formatting - Use `dict` instead of `typing.Dict` --- .../app/services/shared/invocation_context.py | 68 ++++++++----------- 1 file changed, 28 insertions(+), 40 deletions(-) diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py index c932e66989..08ca207118 100644 --- a/invokeai/app/services/shared/invocation_context.py +++ b/invokeai/app/services/shared/invocation_context.py @@ -1,10 +1,10 @@ from dataclasses import dataclass from pathlib import Path -from typing import TYPE_CHECKING, Callable, Dict, Optional, Union +from typing import TYPE_CHECKING, Callable, Optional, Union -import torch from PIL.Image import Image from pydantic.networks import AnyHttpUrl +from torch import Tensor from invokeai.app.invocations.constants import IMAGE_MODES from invokeai.app.invocations.fields import MetadataField, WithBoard, WithMetadata @@ -268,7 +268,7 @@ class ImagesInterface(InvocationContextInterface): class TensorsInterface(InvocationContextInterface): - def save(self, tensor: torch.Tensor) -> str: + def save(self, tensor: Tensor) -> str: """Saves a tensor, returning its name. Args: @@ -281,7 +281,7 @@ class TensorsInterface(InvocationContextInterface): name = self._services.tensors.save(obj=tensor) return name - def load(self, name: str) -> torch.Tensor: + def load(self, name: str) -> Tensor: """Loads a tensor by name. Args: @@ -333,13 +333,9 @@ class ModelsInterface(InvocationContextInterface): True if the model exists, False if not. """ if isinstance(identifier, str): - # For some reason, Mypy is not getting the type annotations for many of - # the model manager service calls and raises a "returning Any in typed - # context" error. Hence the extra typing hints here and below. - result: bool = self._services.model_manager.store.exists(identifier) + return self._services.model_manager.store.exists(identifier) else: - result = self._services.model_manager.store.exists(identifier.key) - return result + return self._services.model_manager.store.exists(identifier.key) def load( self, identifier: Union[str, "ModelIdentifierField"], submodel_type: Optional[SubModelType] = None @@ -353,6 +349,7 @@ class ModelsInterface(InvocationContextInterface): Returns: An object representing the loaded model. """ + # The model manager emits events as it loads the model. It needs the context data to build # the event payloads. @@ -379,6 +376,7 @@ class ModelsInterface(InvocationContextInterface): Returns: An object representing the loaded model. """ + configs = self._services.model_manager.store.search_by_attr(model_name=name, base_model=base, model_type=type) if len(configs) == 0: raise UnknownModelException(f"No model found with name {name}, base {base}, and type {type}") @@ -398,10 +396,9 @@ class ModelsInterface(InvocationContextInterface): The model's config. """ if isinstance(identifier, str): - result: AnyModelConfig = self._services.model_manager.store.get_model(identifier) + return self._services.model_manager.store.get_model(identifier) else: - result = self._services.model_manager.store.get_model(identifier.key) - return result + return self._services.model_manager.store.get_model(identifier.key) def search_by_path(self, path: Path) -> list[AnyModelConfig]: """Search for models by path. @@ -412,8 +409,7 @@ class ModelsInterface(InvocationContextInterface): Returns: A list of models that match the path. """ - result: list[AnyModelConfig] = self._services.model_manager.store.search_by_path(path) - return result + return self._services.model_manager.store.search_by_path(path) def search_by_attrs( self, @@ -433,13 +429,13 @@ class ModelsInterface(InvocationContextInterface): Returns: A list of models that match the attributes. """ - result: list[AnyModelConfig] = self._services.model_manager.store.search_by_attr( + + return self._services.model_manager.store.search_by_attr( model_name=name, base_model=base, model_type=type, model_format=format, ) - return result def download_and_cache_model( self, @@ -453,24 +449,18 @@ class ModelsInterface(InvocationContextInterface): installed, the cached path will be returned. Otherwise it will be downloaded. Args: - source: A model path, URL or repo_id. - Result: - Path to the downloaded model + source: A model path, URL or repo_id. - May Raise: - HTTPError - TimeoutError + Returns: + Path to the downloaded model """ - installer = self._services.model_manager.install - path: Path = installer.download_and_cache_model( - source=source, - ) - return path + + return self._services.model_manager.install.download_and_cache_model(source=source) def load_and_cache_model( self, source: Path | str | AnyHttpUrl, - loader: Optional[Callable[[Path], Dict[str, torch.Tensor]]] = None, + loader: Optional[Callable[[Path], dict[str, Tensor]]] = None, ) -> LoadedModel: """ Download, cache, and load the model file located at the indicated URL. @@ -485,24 +475,22 @@ class ModelsInterface(InvocationContextInterface): Be aware that the LoadedModel object will have a `config` attribute of None. Args: - source: A model Path, URL, or repoid. - loader: A Callable that expects a Path and returns a Dict[str|int, Any] + source: A model Path, URL, or repoid. + loader: A Callable that expects a Path and returns a dict[str|int, Any] Returns: - A LoadedModel object. + A LoadedModel object. """ - result: LoadedModel = ( - self._services.model_manager.load.load_model_from_path(model_path=source, loader=loader) - if isinstance(source, Path) - else self._services.model_manager.load_model_from_url(source=source, loader=loader) - ) - return result + + if isinstance(source, Path): + return self._services.model_manager.load.load_model_from_path(model_path=source, loader=loader) + else: + return self._services.model_manager.load_model_from_url(source=source, loader=loader) class ConfigInterface(InvocationContextInterface): def get(self) -> InvokeAIAppConfig: - """ - Gets the app's config. + """Gets the app's config. Returns: The app's config. From e3a70e598e0c566f2f43bc67588edc0d87c78738 Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 3 Jun 2024 08:40:29 +1000 Subject: [PATCH 032/110] docs(app): simplify docstring in invocation_context --- invokeai/app/services/shared/invocation_context.py | 10 ++++------ 1 file changed, 4 insertions(+), 6 deletions(-) diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py index 08ca207118..27a29f6646 100644 --- a/invokeai/app/services/shared/invocation_context.py +++ b/invokeai/app/services/shared/invocation_context.py @@ -465,12 +465,10 @@ class ModelsInterface(InvocationContextInterface): """ Download, cache, and load the model file located at the indicated URL. - This will check the model download cache for the model designated - by the provided URL and download it if needed using download_and_cache_ckpt(). - It will then load the model into the RAM cache. If the optional loader - argument is provided, the loader will be invoked to load the model into - memory. Otherwise the method will call safetensors.torch.load_file() or - torch.load() as appropriate to the file suffix. + If the model is already downloaded, it will be loaded from the cache. + + If the a loader callable is provided, it will be invoked to load the model. Otherwise, + `safetensors.torch.load_file()` or `torch.load()` will be called to load the model. Be aware that the LoadedModel object will have a `config` attribute of None. From b1244400234cd3a44d4b060751c758d231a8da98 Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 3 Jun 2024 08:51:21 +1000 Subject: [PATCH 033/110] tidy(mm): move `load_model_from_url` from mm to invocation context --- .../model_manager/model_manager_base.py | 31 ----------------- .../model_manager/model_manager_default.py | 34 ++----------------- .../app/services/shared/invocation_context.py | 4 ++- 3 files changed, 5 insertions(+), 64 deletions(-) diff --git a/invokeai/app/services/model_manager/model_manager_base.py b/invokeai/app/services/model_manager/model_manager_base.py index 063979ebe6..af1b68e1ec 100644 --- a/invokeai/app/services/model_manager/model_manager_base.py +++ b/invokeai/app/services/model_manager/model_manager_base.py @@ -1,15 +1,11 @@ # Copyright (c) 2023 Lincoln D. Stein and the InvokeAI Team from abc import ABC, abstractmethod -from pathlib import Path -from typing import Callable, Dict, Optional import torch -from pydantic.networks import AnyHttpUrl from typing_extensions import Self from invokeai.app.services.invoker import Invoker -from invokeai.backend.model_manager.load import LoadedModel from ..config import InvokeAIAppConfig from ..download import DownloadQueueServiceBase @@ -70,30 +66,3 @@ class ModelManagerServiceBase(ABC): @abstractmethod def stop(self, invoker: Invoker) -> None: pass - - @abstractmethod - def load_model_from_url( - self, - source: str | AnyHttpUrl, - loader: Optional[Callable[[Path], Dict[str, torch.Tensor]]] = None, - ) -> LoadedModel: - """ - Download, cache, and Load the model file located at the indicated URL. - - This will check the model download cache for the model designated - by the provided URL and download it if needed using download_and_cache_ckpt(). - It will then load the model into the RAM cache. If the optional loader - argument is provided, the loader will be invoked to load the model into - memory. Otherwise the method will call safetensors.torch.load_file() or - torch.load() as appropriate to the file suffix. - - Be aware that the LoadedModel object will have a `config` attribute of None. - - Args: - source: A URL or a string that can be converted in one. Repo_ids - do not work here. - loader: A Callable that expects a Path and returns a Dict[str|int, Any] - - Returns: - A LoadedModel object. - """ diff --git a/invokeai/app/services/model_manager/model_manager_default.py b/invokeai/app/services/model_manager/model_manager_default.py index dd78f1f3b2..1a2b9a3402 100644 --- a/invokeai/app/services/model_manager/model_manager_default.py +++ b/invokeai/app/services/model_manager/model_manager_default.py @@ -1,15 +1,13 @@ # Copyright (c) 2023 Lincoln D. Stein and the InvokeAI Team """Implementation of ModelManagerServiceBase.""" -from pathlib import Path -from typing import Callable, Dict, Optional +from typing import Optional import torch -from pydantic.networks import AnyHttpUrl from typing_extensions import Self from invokeai.app.services.invoker import Invoker -from invokeai.backend.model_manager.load import LoadedModel, ModelCache, ModelConvertCache, ModelLoaderRegistry +from invokeai.backend.model_manager.load import ModelCache, ModelConvertCache, ModelLoaderRegistry from invokeai.backend.util.devices import TorchDevice from invokeai.backend.util.logging import InvokeAILogger @@ -64,34 +62,6 @@ class ModelManagerService(ModelManagerServiceBase): if hasattr(service, "stop"): service.stop(invoker) - def load_model_from_url( - self, - source: str | AnyHttpUrl, - loader: Optional[Callable[[Path], Dict[str, torch.Tensor]]] = None, - ) -> LoadedModel: - """ - Download, cache, and Load the model file located at the indicated URL. - - This will check the model download cache for the model designated - by the provided URL and download it if needed using download_and_cache_ckpt(). - It will then load the model into the RAM cache. If the optional loader - argument is provided, the loader will be invoked to load the model into - memory. Otherwise the method will call safetensors.torch.load_file() or - torch.load() as appropriate to the file suffix. - - Be aware that the LoadedModel object will have a `config` attribute of None. - - Args: - source: A URL or a string that can be converted in one. Repo_ids - do not work here. - loader: A Callable that expects a Path and returns a Dict[str|int, Any] - - Returns: - A LoadedModel object. - """ - model_path = self.install.download_and_cache_model(source=str(source)) - return self.load.load_model_from_path(model_path=model_path, loader=loader) - @classmethod def build_model_manager( cls, diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py index 27a29f6646..b0d1ee4d2f 100644 --- a/invokeai/app/services/shared/invocation_context.py +++ b/invokeai/app/services/shared/invocation_context.py @@ -483,7 +483,9 @@ class ModelsInterface(InvocationContextInterface): if isinstance(source, Path): return self._services.model_manager.load.load_model_from_path(model_path=source, loader=loader) else: - return self._services.model_manager.load_model_from_url(source=source, loader=loader) + model_path = self._services.model_manager.install.download_and_cache_model(source=str(source)) + return self._services.model_manager.load.load_model_from_path(model_path=model_path, loader=loader) + class ConfigInterface(InvocationContextInterface): From ccdecf21a3dda1dc051eed59a5567aa60406f2f2 Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 3 Jun 2024 09:41:17 +1000 Subject: [PATCH 034/110] tidy(nodes): cnet processors - Set `self._context=context` instead of changing the type signature of `run_processor` - Tidy a few typing things --- .../controlnet_image_processors.py | 52 ++++++++++--------- 1 file changed, 27 insertions(+), 25 deletions(-) diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py index e533583829..1e4ad672bf 100644 --- a/invokeai/app/invocations/controlnet_image_processors.py +++ b/invokeai/app/invocations/controlnet_image_processors.py @@ -132,7 +132,7 @@ class ImageProcessorInvocation(BaseInvocation, WithMetadata, WithBoard): image: ImageField = InputField(description="The image to process") - def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + def run_processor(self, image: Image.Image) -> Image.Image: # superclass just passes through image without processing return image @@ -141,9 +141,10 @@ class ImageProcessorInvocation(BaseInvocation, WithMetadata, WithBoard): return context.images.get_pil(self.image.image_name, "RGB") def invoke(self, context: InvocationContext) -> ImageOutput: + self._context = context raw_image = self.load_image(context) # image type should be PIL.PngImagePlugin.PngImageFile ? - processed_image = self.run_processor(raw_image, context) + processed_image = self.run_processor(raw_image) # currently can't see processed image in node UI without a showImage node, # so for now setting image_type to RESULT instead of INTERMEDIATE so will get saved in gallery @@ -184,7 +185,7 @@ class CannyImageProcessorInvocation(ImageProcessorInvocation): # Keep alpha channel for Canny processing to detect edges of transparent areas return context.images.get_pil(self.image.image_name, "RGBA") - def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + def run_processor(self, image: Image.Image) -> Image.Image: processed_image = get_canny_edges( image, self.low_threshold, @@ -211,7 +212,7 @@ class HedImageProcessorInvocation(ImageProcessorInvocation): # safe: bool = InputField(default=False, description=FieldDescriptions.safe_mode) scribble: bool = InputField(default=False, description=FieldDescriptions.scribble_mode) - def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + def run_processor(self, image: Image.Image) -> Image.Image: hed_processor = HEDProcessor() processed_image = hed_processor.run( image, @@ -238,7 +239,7 @@ class LineartImageProcessorInvocation(ImageProcessorInvocation): image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res) coarse: bool = InputField(default=False, description="Whether to use coarse mode") - def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + def run_processor(self, image: Image.Image) -> Image.Image: lineart_processor = LineartProcessor() processed_image = lineart_processor.run( image, detect_resolution=self.detect_resolution, image_resolution=self.image_resolution, coarse=self.coarse @@ -259,7 +260,7 @@ class LineartAnimeImageProcessorInvocation(ImageProcessorInvocation): detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res) image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res) - def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + def run_processor(self, image: Image.Image) -> Image.Image: processor = LineartAnimeProcessor() processed_image = processor.run( image, @@ -286,7 +287,7 @@ class MidasDepthImageProcessorInvocation(ImageProcessorInvocation): # depth_and_normal not supported in controlnet_aux v0.0.3 # depth_and_normal: bool = InputField(default=False, description="whether to use depth and normal mode") - def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + def run_processor(self, image: Image.Image) -> Image.Image: # TODO: replace from_pretrained() calls with context.models.download_and_cache() (or similar) midas_processor = MidasDetector.from_pretrained("lllyasviel/Annotators") processed_image = midas_processor( @@ -314,9 +315,9 @@ class NormalbaeImageProcessorInvocation(ImageProcessorInvocation): detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res) image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res) - def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + def run_processor(self, image: Image.Image) -> Image.Image: normalbae_processor = NormalBaeDetector.from_pretrained("lllyasviel/Annotators") - processed_image: Image.Image = normalbae_processor( + processed_image = normalbae_processor( image, detect_resolution=self.detect_resolution, image_resolution=self.image_resolution ) return processed_image @@ -333,7 +334,7 @@ class MlsdImageProcessorInvocation(ImageProcessorInvocation): thr_v: float = InputField(default=0.1, ge=0, description="MLSD parameter `thr_v`") thr_d: float = InputField(default=0.1, ge=0, description="MLSD parameter `thr_d`") - def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + def run_processor(self, image: Image.Image) -> Image.Image: mlsd_processor = MLSDdetector.from_pretrained("lllyasviel/Annotators") processed_image = mlsd_processor( image, @@ -356,7 +357,7 @@ class PidiImageProcessorInvocation(ImageProcessorInvocation): safe: bool = InputField(default=False, description=FieldDescriptions.safe_mode) scribble: bool = InputField(default=False, description=FieldDescriptions.scribble_mode) - def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + def run_processor(self, image: Image.Image) -> Image.Image: pidi_processor = PidiNetDetector.from_pretrained("lllyasviel/Annotators") processed_image = pidi_processor( image, @@ -384,7 +385,7 @@ class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation): w: int = InputField(default=512, ge=0, description="Content shuffle `w` parameter") f: int = InputField(default=256, ge=0, description="Content shuffle `f` parameter") - def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + def run_processor(self, image: Image.Image) -> Image.Image: content_shuffle_processor = ContentShuffleDetector() processed_image = content_shuffle_processor( image, @@ -408,7 +409,7 @@ class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation): class ZoeDepthImageProcessorInvocation(ImageProcessorInvocation): """Applies Zoe depth processing to image""" - def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + def run_processor(self, image: Image.Image) -> Image.Image: zoe_depth_processor = ZoeDetector.from_pretrained("lllyasviel/Annotators") processed_image = zoe_depth_processor(image) return processed_image @@ -429,7 +430,7 @@ class MediapipeFaceProcessorInvocation(ImageProcessorInvocation): detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res) image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res) - def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + def run_processor(self, image: Image.Image) -> Image.Image: mediapipe_face_processor = MediapipeFaceDetector() processed_image = mediapipe_face_processor( image, @@ -457,7 +458,7 @@ class LeresImageProcessorInvocation(ImageProcessorInvocation): detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res) image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res) - def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + def run_processor(self, image: Image.Image) -> Image.Image: leres_processor = LeresDetector.from_pretrained("lllyasviel/Annotators") processed_image = leres_processor( image, @@ -499,8 +500,8 @@ class TileResamplerProcessorInvocation(ImageProcessorInvocation): np_img = cv2.resize(np_img, (W, H), interpolation=cv2.INTER_AREA) return np_img - def run_processor(self, img: Image.Image, context: InvocationContext) -> Image.Image: - np_img = np.array(img, dtype=np.uint8) + def run_processor(self, image: Image.Image) -> Image.Image: + np_img = np.array(image, dtype=np.uint8) processed_np_image = self.tile_resample( np_img, # res=self.tile_size, @@ -523,7 +524,7 @@ class SegmentAnythingProcessorInvocation(ImageProcessorInvocation): detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res) image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res) - def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + def run_processor(self, image: Image.Image) -> Image.Image: # segment_anything_processor = SamDetector.from_pretrained("ybelkada/segment-anything", subfolder="checkpoints") segment_anything_processor = SamDetectorReproducibleColors.from_pretrained( "ybelkada/segment-anything", subfolder="checkpoints" @@ -569,7 +570,7 @@ class ColorMapImageProcessorInvocation(ImageProcessorInvocation): color_map_tile_size: int = InputField(default=64, ge=1, description=FieldDescriptions.tile_size) - def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + def run_processor(self, image: Image.Image) -> Image.Image: np_image = np.array(image, dtype=np.uint8) height, width = np_image.shape[:2] @@ -604,13 +605,15 @@ class DepthAnythingImageProcessorInvocation(ImageProcessorInvocation): ) resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res) - def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: + def run_processor(self, image: Image.Image) -> Image.Image: def loader(model_path: Path): return DepthAnythingDetector.load_model( model_path, model_size=self.model_size, device=TorchDevice.choose_torch_device() ) - with context.models.load_and_cache_model(source=DEPTH_ANYTHING_MODELS[self.model_size], loader=loader) as model: + with self._context.models.load_and_cache_model( + source=DEPTH_ANYTHING_MODELS[self.model_size], loader=loader + ) as model: depth_anything_detector = DepthAnythingDetector(model, TorchDevice.choose_torch_device()) processed_image = depth_anything_detector(image=image, resolution=self.resolution) return processed_image @@ -631,10 +634,9 @@ class DWOpenposeImageProcessorInvocation(ImageProcessorInvocation): draw_hands: bool = InputField(default=False) image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res) - def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image: - mm = context.models - onnx_det = mm.download_and_cache_model(DWPOSE_MODELS["yolox_l.onnx"]) - onnx_pose = mm.download_and_cache_model(DWPOSE_MODELS["dw-ll_ucoco_384.onnx"]) + def run_processor(self, image: Image.Image) -> Image.Image: + onnx_det = self._context.models.download_and_cache_model(DWPOSE_MODELS["yolox_l.onnx"]) + onnx_pose = self._context.models.download_and_cache_model(DWPOSE_MODELS["dw-ll_ucoco_384.onnx"]) dw_openpose = DWOpenposeDetector(onnx_det=onnx_det, onnx_pose=onnx_pose) processed_image = dw_openpose( From 521f907f587854612960ef5a27cc85a465f59d03 Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 3 Jun 2024 09:43:25 +1000 Subject: [PATCH 035/110] tidy(nodes): infill - Set `self._context=context` instead of passing it as an arg --- invokeai/app/invocations/infill.py | 25 +++++++++++++------------ 1 file changed, 13 insertions(+), 12 deletions(-) diff --git a/invokeai/app/invocations/infill.py b/invokeai/app/invocations/infill.py index ddd11cf93f..f188ecf8f7 100644 --- a/invokeai/app/invocations/infill.py +++ b/invokeai/app/invocations/infill.py @@ -38,26 +38,27 @@ class InfillImageProcessorInvocation(BaseInvocation, WithMetadata, WithBoard): image: ImageField = InputField(description="The image to process") @abstractmethod - def infill(self, image: Image.Image, context: InvocationContext) -> Image.Image: + def infill(self, image: Image.Image) -> Image.Image: """Infill the image with the specified method""" pass - def load_image(self, context: InvocationContext) -> tuple[Image.Image, bool]: + def load_image(self) -> tuple[Image.Image, bool]: """Process the image to have an alpha channel before being infilled""" - image = context.images.get_pil(self.image.image_name) + image = self._context.images.get_pil(self.image.image_name) has_alpha = True if image.mode == "RGBA" else False return image, has_alpha def invoke(self, context: InvocationContext) -> ImageOutput: + self._context = context # Retrieve and process image to be infilled - input_image, has_alpha = self.load_image(context) + input_image, has_alpha = self.load_image() # If the input image has no alpha channel, return it if has_alpha is False: return ImageOutput.build(context.images.get_dto(self.image.image_name)) # Perform Infill action - infilled_image = self.infill(input_image, context) + infilled_image = self.infill(input_image) # Create ImageDTO for Infilled Image infilled_image_dto = context.images.save(image=infilled_image) @@ -75,7 +76,7 @@ class InfillColorInvocation(InfillImageProcessorInvocation): description="The color to use to infill", ) - def infill(self, image: Image.Image, context: InvocationContext): + def infill(self, image: Image.Image): solid_bg = Image.new("RGBA", image.size, self.color.tuple()) infilled = Image.alpha_composite(solid_bg, image.convert("RGBA")) infilled.paste(image, (0, 0), image.split()[-1]) @@ -94,7 +95,7 @@ class InfillTileInvocation(InfillImageProcessorInvocation): description="The seed to use for tile generation (omit for random)", ) - def infill(self, image: Image.Image, context: InvocationContext): + def infill(self, image: Image.Image): output = infill_tile(image, seed=self.seed, tile_size=self.tile_size) return output.infilled @@ -108,7 +109,7 @@ class InfillPatchMatchInvocation(InfillImageProcessorInvocation): downscale: float = InputField(default=2.0, gt=0, description="Run patchmatch on downscaled image to speedup infill") resample_mode: PIL_RESAMPLING_MODES = InputField(default="bicubic", description="The resampling mode") - def infill(self, image: Image.Image, context: InvocationContext): + def infill(self, image: Image.Image): resample_mode = PIL_RESAMPLING_MAP[self.resample_mode] width = int(image.width / self.downscale) @@ -132,8 +133,8 @@ class InfillPatchMatchInvocation(InfillImageProcessorInvocation): class LaMaInfillInvocation(InfillImageProcessorInvocation): """Infills transparent areas of an image using the LaMa model""" - def infill(self, image: Image.Image, context: InvocationContext): - with context.models.load_and_cache_model( + def infill(self, image: Image.Image): + with self._context.models.load_and_cache_model( source="https://github.com/Sanster/models/releases/download/add_big_lama/big-lama.pt", loader=LaMA.load_jit_model, ) as model: @@ -145,7 +146,7 @@ class LaMaInfillInvocation(InfillImageProcessorInvocation): class CV2InfillInvocation(InfillImageProcessorInvocation): """Infills transparent areas of an image using OpenCV Inpainting""" - def infill(self, image: Image.Image, context: InvocationContext): + def infill(self, image: Image.Image): return cv2_inpaint(image) @@ -167,5 +168,5 @@ class MosaicInfillInvocation(InfillImageProcessorInvocation): description="The max threshold for color", ) - def infill(self, image: Image.Image, context: InvocationContext): + def infill(self, image: Image.Image): return infill_mosaic(image, (self.tile_width, self.tile_height), self.min_color.tuple(), self.max_color.tuple()) From 6cc6a452741f9eef5394300b06a0f2c3e4a4b4a0 Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 3 Jun 2024 10:05:52 +1000 Subject: [PATCH 036/110] feat(download): add type for callback_name Just a bit of typo protection in lieu of full type safety for these methods, which is difficult due to the typing of `DownloadEventHandler`. --- invokeai/app/services/download/download_default.py | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/invokeai/app/services/download/download_default.py b/invokeai/app/services/download/download_default.py index 5025255c91..4640a656dc 100644 --- a/invokeai/app/services/download/download_default.py +++ b/invokeai/app/services/download/download_default.py @@ -8,7 +8,7 @@ import time import traceback from pathlib import Path from queue import Empty, PriorityQueue -from typing import TYPE_CHECKING, Any, Dict, List, Optional, Set +from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional, Set import requests from pydantic.networks import AnyHttpUrl @@ -528,7 +528,13 @@ class DownloadQueueService(DownloadQueueServiceBase): def _execute_cb( self, job: DownloadJob | MultiFileDownloadJob, - callback_name: str, + callback_name: Literal[ + "on_start", + "on_progress", + "on_complete", + "on_cancelled", + "on_error", + ], excp: Optional[Exception] = None, ) -> None: if callback := getattr(job, callback_name, None): From c58ac1e80d14d23b9e00b0944830a7994c64bfaa Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 3 Jun 2024 10:11:08 +1000 Subject: [PATCH 037/110] tidy(mm): minor formatting --- invokeai/app/services/model_install/model_install_base.py | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/invokeai/app/services/model_install/model_install_base.py b/invokeai/app/services/model_install/model_install_base.py index 76b77f0419..734f05d574 100644 --- a/invokeai/app/services/model_install/model_install_base.py +++ b/invokeai/app/services/model_install/model_install_base.py @@ -241,10 +241,7 @@ class ModelInstallServiceBase(ABC): """ @abstractmethod - def download_and_cache_model( - self, - source: str, - ) -> Path: + def download_and_cache_model(self, source: str) -> Path: """ Download the model file located at source to the models cache and return its Path. From aa9695e377acb6f3485e564c4a117063889ada9c Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 3 Jun 2024 10:15:53 +1000 Subject: [PATCH 038/110] tidy(download): `_download_job` -> `_multifile_job` --- .../services/model_install/model_install_common.py | 2 +- .../services/model_install/model_install_default.py | 12 ++++++------ 2 files changed, 7 insertions(+), 7 deletions(-) diff --git a/invokeai/app/services/model_install/model_install_common.py b/invokeai/app/services/model_install/model_install_common.py index 751b5baa4b..c1538f543d 100644 --- a/invokeai/app/services/model_install/model_install_common.py +++ b/invokeai/app/services/model_install/model_install_common.py @@ -162,7 +162,7 @@ class ModelInstallJob(BaseModel): ) # internal flags and transitory settings _install_tmpdir: Optional[Path] = PrivateAttr(default=None) - _download_job: Optional[MultiFileDownloadJob] = PrivateAttr(default=None) + _multifile_job: Optional[MultiFileDownloadJob] = PrivateAttr(default=None) _exception: Optional[Exception] = PrivateAttr(default=None) def set_error(self, e: Exception) -> None: diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py index 3b8a408e97..b561744ff4 100644 --- a/invokeai/app/services/model_install/model_install_default.py +++ b/invokeai/app/services/model_install/model_install_default.py @@ -278,7 +278,7 @@ class ModelInstallService(ModelInstallServiceBase): """Cancel the indicated job.""" job.cancel() self._logger.warning(f"Cancelling {job.source}") - if dj := job._download_job: + if dj := job._multifile_job: self._download_queue.cancel_job(dj) def prune_jobs(self) -> None: @@ -514,9 +514,9 @@ class ModelInstallService(ModelInstallServiceBase): self._signal_job_completed(job) def _set_error(self, install_job: ModelInstallJob, excp: Exception) -> None: - download_job = install_job._download_job - if download_job and any( - x.content_type is not None and "text/html" in x.content_type for x in download_job.download_parts + multifile_download_job = install_job._multifile_job + if multifile_download_job and any( + x.content_type is not None and "text/html" in x.content_type for x in multifile_download_job.download_parts ): install_job.set_error( InvalidModelConfigException( @@ -748,7 +748,7 @@ class ModelInstallService(ModelInstallServiceBase): submit_job=False, # Important! Don't submit the job until we have set our _download_cache dict ) self._download_cache[multifile_job.id] = install_job - install_job._download_job = multifile_job + install_job._multifile_job = multifile_job files_string = "file" if len(remote_files) == 1 else "files" self._logger.info(f"Queueing model install: {source} ({len(remote_files)} {files_string})") @@ -875,7 +875,7 @@ class ModelInstallService(ModelInstallServiceBase): def _signal_job_downloading(self, job: ModelInstallJob) -> None: if self._event_bus: - assert job._download_job is not None + assert job._multifile_job is not None assert job.bytes is not None assert job.total_bytes is not None self._event_bus.emit_model_install_download_progress(job) From 99413256ce1f847ec42918ed1af49fad3c54736a Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 3 Jun 2024 10:43:09 +1000 Subject: [PATCH 039/110] tidy(mm): pass enum member instead of string --- invokeai/app/services/model_install/model_install_default.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py index b561744ff4..de9bb8eed8 100644 --- a/invokeai/app/services/model_install/model_install_default.py +++ b/invokeai/app/services/model_install/model_install_default.py @@ -442,7 +442,7 @@ class ModelInstallService(ModelInstallServiceBase): elif match := re.match(hf_repoid_re, source): source_obj = HFModelSource( repo_id=match.group(1), - variant=match.group(2) if match.group(2) else None, # pass None rather than '' + variant=ModelRepoVariant(match.group(2)) if match.group(2) else None, # pass None rather than '' subfolder=Path(match.group(3)) if match.group(3) else None, ) elif re.match(r"^https?://[^/]+", source): From c7f22b6a3b36e0b0bf7b2320ece7db1c84c22a3e Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 3 Jun 2024 10:46:28 +1000 Subject: [PATCH 040/110] tidy(mm): remove extraneous docstring It's inherited from the ABC. --- .../services/model_load/model_load_default.py | 17 ----------------- 1 file changed, 17 deletions(-) diff --git a/invokeai/app/services/model_load/model_load_default.py b/invokeai/app/services/model_load/model_load_default.py index 221a042da5..776620edca 100644 --- a/invokeai/app/services/model_load/model_load_default.py +++ b/invokeai/app/services/model_load/model_load_default.py @@ -87,23 +87,6 @@ class ModelLoadService(ModelLoadServiceBase): def load_model_from_path( self, model_path: Path, loader: Optional[Callable[[Path], Dict[str, Tensor]]] = None ) -> LoadedModel: - """ - Load the checkpoint-format model file located at the indicated Path. - - This will load an arbitrary model file into the RAM cache. If the optional loader - argument is provided, the loader will be invoked to load the model into - memory. Otherwise the method will call safetensors.torch.load_file() or - torch.load() as appropriate to the file suffix. - - Be aware that the LoadedModel object will have a `config` attribute of None. - - Args: - model_path: A pathlib.Path to a checkpoint-style models file - loader: A Callable that expects a Path and returns a Dict[str, Tensor] - - Returns: - A LoadedModel object. - """ cache_key = str(model_path) ram_cache = self.ram_cache try: From e7513f60887b358055e23631024e701d3ffca20d Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 3 Jun 2024 10:56:04 +1000 Subject: [PATCH 041/110] docs(mm): add comment in `move_model_to_device` --- .../model_manager/load/model_cache/model_cache_default.py | 1 + 1 file changed, 1 insertion(+) diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py index 10c0210052..335a15a5c8 100644 --- a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py +++ b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py @@ -261,6 +261,7 @@ class ModelCache(ModelCacheBase[AnyModel]): if torch.device(source_device).type == torch.device(target_device).type: return + # Some models don't have a `to` method, in which case they run in RAM/CPU. if not hasattr(cache_entry.model, "to"): return From a9962fd104823458f658f989eb73eca1f8a81444 Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 3 Jun 2024 11:53:20 +1000 Subject: [PATCH 042/110] chore: ruff --- invokeai/app/services/shared/invocation_context.py | 1 - 1 file changed, 1 deletion(-) diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py index b0d1ee4d2f..260bf6a61f 100644 --- a/invokeai/app/services/shared/invocation_context.py +++ b/invokeai/app/services/shared/invocation_context.py @@ -487,7 +487,6 @@ class ModelsInterface(InvocationContextInterface): return self._services.model_manager.load.load_model_from_path(model_path=model_path, loader=loader) - class ConfigInterface(InvocationContextInterface): def get(self) -> InvokeAIAppConfig: """Gets the app's config. From 1c59fce6ad81ca8969b99ff7763039c73cd891c8 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Tue, 28 May 2024 22:41:44 -0400 Subject: [PATCH 043/110] reduce peak VRAM memory usage of IP adapter --- invokeai/app/invocations/latent.py | 59 ++++++++++++++++++++---------- 1 file changed, 39 insertions(+), 20 deletions(-) diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index a88eff0fcb..8dd90a18e6 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -50,7 +50,6 @@ from invokeai.app.invocations.primitives import DenoiseMaskOutput, ImageOutput, from invokeai.app.invocations.t2i_adapter import T2IAdapterField from invokeai.app.services.shared.invocation_context import InvocationContext from invokeai.app.util.controlnet_utils import prepare_control_image -from invokeai.backend.ip_adapter.ip_adapter import IPAdapter, IPAdapterPlus from invokeai.backend.lora import LoRAModelRaw from invokeai.backend.model_manager import BaseModelType, LoadedModel from invokeai.backend.model_manager.config import MainConfigBase, ModelVariantType @@ -672,6 +671,39 @@ class DenoiseLatentsInvocation(BaseInvocation): return controlnet_data + def prep_ip_adapter_image_prompts( + self, + context: InvocationContext, + ip_adapter: Optional[Union[IPAdapterField, list[IPAdapterField]]], + ) -> List[Tuple[torch.Tensor, torch.Tensor]]: + """Run the IPAdapter CLIPVisionModel, returning image prompt embeddings.""" + # ip_adapter could be a list or a single IPAdapterField. Normalize to a list here. + if not isinstance(ip_adapter, list): + ip_adapter = [ip_adapter] + + if len(ip_adapter) == 0: + return [] + + image_prompts = [] + for single_ip_adapter in ip_adapter: + with context.models.load(single_ip_adapter.ip_adapter_model) as ip_adapter_model: + image_encoder_model_info = context.models.load(single_ip_adapter.image_encoder_model) + # `single_ip_adapter.image` could be a list or a single ImageField. Normalize to a list here. + single_ipa_image_fields = single_ip_adapter.image + if not isinstance(single_ipa_image_fields, list): + single_ipa_image_fields = [single_ipa_image_fields] + + single_ipa_images = [context.images.get_pil(image.image_name) for image in single_ipa_image_fields] + with image_encoder_model_info as image_encoder_model: + assert isinstance(image_encoder_model, CLIPVisionModelWithProjection) + # Get image embeddings from CLIP and ImageProjModel. + image_prompt_embeds, uncond_image_prompt_embeds = ip_adapter_model.get_image_embeds( + single_ipa_images, image_encoder_model + ) + image_prompts.append((image_prompt_embeds, uncond_image_prompt_embeds)) + + return image_prompts + def prep_ip_adapter_data( self, context: InvocationContext, @@ -680,6 +712,7 @@ class DenoiseLatentsInvocation(BaseInvocation): latent_height: int, latent_width: int, dtype: torch.dtype, + image_prompts: List[Tuple[torch.Tensor, torch.Tensor]], ) -> Optional[list[IPAdapterData]]: """If IP-Adapter is enabled, then this function loads the requisite models, and adds the image prompt embeddings to the `conditioning_data` (in-place). @@ -696,26 +729,9 @@ class DenoiseLatentsInvocation(BaseInvocation): ip_adapter_data_list = [] for single_ip_adapter in ip_adapter: - ip_adapter_model: Union[IPAdapter, IPAdapterPlus] = exit_stack.enter_context( - context.models.load(single_ip_adapter.ip_adapter_model) - ) + ip_adapter_model = exit_stack.enter_context(context.models.load(single_ip_adapter.ip_adapter_model)) - image_encoder_model_info = context.models.load(single_ip_adapter.image_encoder_model) - # `single_ip_adapter.image` could be a list or a single ImageField. Normalize to a list here. - single_ipa_image_fields = single_ip_adapter.image - if not isinstance(single_ipa_image_fields, list): - single_ipa_image_fields = [single_ipa_image_fields] - - single_ipa_images = [context.images.get_pil(image.image_name) for image in single_ipa_image_fields] - - # TODO(ryand): With some effort, the step of running the CLIP Vision encoder could be done before any other - # models are needed in memory. This would help to reduce peak memory utilization in low-memory environments. - with image_encoder_model_info as image_encoder_model: - assert isinstance(image_encoder_model, CLIPVisionModelWithProjection) - # Get image embeddings from CLIP and ImageProjModel. - image_prompt_embeds, uncond_image_prompt_embeds = ip_adapter_model.get_image_embeds( - single_ipa_images, image_encoder_model - ) + image_prompt_embeds, uncond_image_prompt_embeds = image_prompts.pop(0) mask = single_ip_adapter.mask if mask is not None: @@ -912,6 +928,8 @@ class DenoiseLatentsInvocation(BaseInvocation): do_classifier_free_guidance=True, ) + image_prompts = self.prep_ip_adapter_image_prompts(context=context, ip_adapter=self.ip_adapter) + # get the unet's config so that we can pass the base to dispatch_progress() unet_config = context.models.get_config(self.unet.unet.key) @@ -975,6 +993,7 @@ class DenoiseLatentsInvocation(BaseInvocation): latent_height=latent_height, latent_width=latent_width, dtype=unet.dtype, + image_prompts=image_prompts, ) num_inference_steps, timesteps, init_timestep, scheduler_step_kwargs = self.init_scheduler( From 7391c126d3948241db9e199228338a7e3d03c171 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Tue, 28 May 2024 22:57:01 -0400 Subject: [PATCH 044/110] handle case of no IP adapters requested --- invokeai/app/invocations/latent.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index 8dd90a18e6..f4d2eecf0a 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -678,6 +678,9 @@ class DenoiseLatentsInvocation(BaseInvocation): ) -> List[Tuple[torch.Tensor, torch.Tensor]]: """Run the IPAdapter CLIPVisionModel, returning image prompt embeddings.""" # ip_adapter could be a list or a single IPAdapterField. Normalize to a list here. + if ip_adapter is None: + return [] + if not isinstance(ip_adapter, list): ip_adapter = [ip_adapter] From e28737fc8b5d2def727d965a5c5b270e2b843ddc Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Tue, 28 May 2024 23:00:07 -0400 Subject: [PATCH 045/110] add check for congruence between # of ip_adapters and image_prompts --- invokeai/app/invocations/latent.py | 1 + 1 file changed, 1 insertion(+) diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index f4d2eecf0a..59897f5333 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -731,6 +731,7 @@ class DenoiseLatentsInvocation(BaseInvocation): return None ip_adapter_data_list = [] + assert len(ip_adapter) == len(image_prompts) for single_ip_adapter in ip_adapter: ip_adapter_model = exit_stack.enter_context(context.models.load(single_ip_adapter.ip_adapter_model)) From f13427e3f49e27595698f35fa9bfd8e059250ea3 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Wed, 29 May 2024 10:29:54 -0400 Subject: [PATCH 046/110] refactor redundant code and fix typechecking errors --- invokeai/app/invocations/latent.py | 61 ++++++++++++------------------ 1 file changed, 24 insertions(+), 37 deletions(-) diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index 59897f5333..44cfd67d0c 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -50,6 +50,7 @@ from invokeai.app.invocations.primitives import DenoiseMaskOutput, ImageOutput, from invokeai.app.invocations.t2i_adapter import T2IAdapterField from invokeai.app.services.shared.invocation_context import InvocationContext from invokeai.app.util.controlnet_utils import prepare_control_image +from invokeai.backend.ip_adapter.ip_adapter import IPAdapter from invokeai.backend.lora import LoRAModelRaw from invokeai.backend.model_manager import BaseModelType, LoadedModel from invokeai.backend.model_manager.config import MainConfigBase, ModelVariantType @@ -674,22 +675,13 @@ class DenoiseLatentsInvocation(BaseInvocation): def prep_ip_adapter_image_prompts( self, context: InvocationContext, - ip_adapter: Optional[Union[IPAdapterField, list[IPAdapterField]]], + ip_adapters: List[IPAdapterField], ) -> List[Tuple[torch.Tensor, torch.Tensor]]: """Run the IPAdapter CLIPVisionModel, returning image prompt embeddings.""" - # ip_adapter could be a list or a single IPAdapterField. Normalize to a list here. - if ip_adapter is None: - return [] - - if not isinstance(ip_adapter, list): - ip_adapter = [ip_adapter] - - if len(ip_adapter) == 0: - return [] - image_prompts = [] - for single_ip_adapter in ip_adapter: + for single_ip_adapter in ip_adapters: with context.models.load(single_ip_adapter.ip_adapter_model) as ip_adapter_model: + assert isinstance(ip_adapter_model, IPAdapter) image_encoder_model_info = context.models.load(single_ip_adapter.image_encoder_model) # `single_ip_adapter.image` could be a list or a single ImageField. Normalize to a list here. single_ipa_image_fields = single_ip_adapter.image @@ -710,36 +702,23 @@ class DenoiseLatentsInvocation(BaseInvocation): def prep_ip_adapter_data( self, context: InvocationContext, - ip_adapter: Optional[Union[IPAdapterField, list[IPAdapterField]]], + ip_adapters: List[IPAdapterField], + image_prompts: List[Tuple[torch.Tensor, torch.Tensor]], exit_stack: ExitStack, latent_height: int, latent_width: int, dtype: torch.dtype, - image_prompts: List[Tuple[torch.Tensor, torch.Tensor]], - ) -> Optional[list[IPAdapterData]]: - """If IP-Adapter is enabled, then this function loads the requisite models, and adds the image prompt embeddings - to the `conditioning_data` (in-place). - """ - if ip_adapter is None: - return None - - # ip_adapter could be a list or a single IPAdapterField. Normalize to a list here. - if not isinstance(ip_adapter, list): - ip_adapter = [ip_adapter] - - if len(ip_adapter) == 0: - return None - + ) -> Optional[List[IPAdapterData]]: + """If IP-Adapter is enabled, then this function loads the requisite models and adds the image prompt conditioning data.""" ip_adapter_data_list = [] - assert len(ip_adapter) == len(image_prompts) - for single_ip_adapter in ip_adapter: + assert len(ip_adapters) == len(image_prompts) + for single_ip_adapter in ip_adapters: ip_adapter_model = exit_stack.enter_context(context.models.load(single_ip_adapter.ip_adapter_model)) image_prompt_embeds, uncond_image_prompt_embeds = image_prompts.pop(0) - mask = single_ip_adapter.mask - if mask is not None: - mask = context.tensors.load(mask.tensor_name) + mask_field = single_ip_adapter.mask + mask = context.tensors.load(mask_field.tensor_name) if mask_field is not None else None mask = self._preprocess_regional_prompt_mask(mask, latent_height, latent_width, dtype=dtype) ip_adapter_data_list.append( @@ -754,7 +733,7 @@ class DenoiseLatentsInvocation(BaseInvocation): ) ) - return ip_adapter_data_list + return ip_adapter_data_list if len(ip_adapter_data_list) > 0 else None def run_t2i_adapters( self, @@ -932,7 +911,15 @@ class DenoiseLatentsInvocation(BaseInvocation): do_classifier_free_guidance=True, ) - image_prompts = self.prep_ip_adapter_image_prompts(context=context, ip_adapter=self.ip_adapter) + ip_adapters: List[IPAdapterField] = [] + if self.ip_adapter is not None: + # ip_adapter could be a list or a single IPAdapterField. Normalize to a list here. + if isinstance(self.ip_adapter, list): + ip_adapters = self.ip_adapter + else: + ip_adapters = [self.ip_adapter] + + image_prompts = self.prep_ip_adapter_image_prompts(context=context, ip_adapters=ip_adapters) # get the unet's config so that we can pass the base to dispatch_progress() unet_config = context.models.get_config(self.unet.unet.key) @@ -992,12 +979,12 @@ class DenoiseLatentsInvocation(BaseInvocation): ip_adapter_data = self.prep_ip_adapter_data( context=context, - ip_adapter=self.ip_adapter, + ip_adapters=ip_adapters, + image_prompts=image_prompts, exit_stack=exit_stack, latent_height=latent_height, latent_width=latent_width, dtype=unet.dtype, - image_prompts=image_prompts, ) num_inference_steps, timesteps, init_timestep, scheduler_step_kwargs = self.init_scheduler( From 493f81788c88b93e8d6cbeb8f13c5bcd943ea255 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Wed, 29 May 2024 19:45:38 -0400 Subject: [PATCH 047/110] added a few comments to document design choices --- invokeai/app/invocations/latent.py | 4 ++++ invokeai/app/invocations/mask.py | 6 +++--- invokeai/app/services/events/events_common.py | 3 ++- .../shared/sqlite_migrator/sqlite_migrator_common.py | 3 ++- 4 files changed, 11 insertions(+), 5 deletions(-) diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index 44cfd67d0c..c8d0b875a8 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -919,6 +919,10 @@ class DenoiseLatentsInvocation(BaseInvocation): else: ip_adapters = [self.ip_adapter] + # If there are IP adapters, the following line runs the adapters' CLIPVision image encoders to return + # a series of image conditioning embeddings. This is being done here rather than in the + # big model context below in order to use less VRAM on low-VRAM systems. + # The image prompts are then passed to prep_ip_adapter_data(). image_prompts = self.prep_ip_adapter_image_prompts(context=context, ip_adapters=ip_adapters) # get the unet's config so that we can pass the base to dispatch_progress() diff --git a/invokeai/app/invocations/mask.py b/invokeai/app/invocations/mask.py index 6f54660847..6b9524e7a8 100644 --- a/invokeai/app/invocations/mask.py +++ b/invokeai/app/invocations/mask.py @@ -25,9 +25,9 @@ class RectangleMaskInvocation(BaseInvocation, WithMetadata): def invoke(self, context: InvocationContext) -> MaskOutput: mask = torch.zeros((1, self.height, self.width), dtype=torch.bool) - mask[:, self.y_top : self.y_top + self.rectangle_height, self.x_left : self.x_left + self.rectangle_width] = ( - True - ) + mask[ + :, self.y_top : self.y_top + self.rectangle_height, self.x_left : self.x_left + self.rectangle_width + ] = True mask_tensor_name = context.tensors.save(mask) return MaskOutput( diff --git a/invokeai/app/services/events/events_common.py b/invokeai/app/services/events/events_common.py index 0adcaa2ab1..f30b054f36 100644 --- a/invokeai/app/services/events/events_common.py +++ b/invokeai/app/services/events/events_common.py @@ -62,7 +62,8 @@ Provide a generic type to `TEvent` to specify the payload type. class FastAPIEventFunc(Protocol, Generic[TEvent]): - def __call__(self, event: FastAPIEvent[TEvent]) -> Optional[Coroutine[Any, Any, None]]: ... + def __call__(self, event: FastAPIEvent[TEvent]) -> Optional[Coroutine[Any, Any, None]]: + ... def register_events(events: set[type[TEvent]] | type[TEvent], func: FastAPIEventFunc[TEvent]) -> None: diff --git a/invokeai/app/services/shared/sqlite_migrator/sqlite_migrator_common.py b/invokeai/app/services/shared/sqlite_migrator/sqlite_migrator_common.py index 9b2444dae4..47ed5da505 100644 --- a/invokeai/app/services/shared/sqlite_migrator/sqlite_migrator_common.py +++ b/invokeai/app/services/shared/sqlite_migrator/sqlite_migrator_common.py @@ -17,7 +17,8 @@ class MigrateCallback(Protocol): See :class:`Migration` for an example. """ - def __call__(self, cursor: sqlite3.Cursor) -> None: ... + def __call__(self, cursor: sqlite3.Cursor) -> None: + ... class MigrationError(RuntimeError): From 93c9852142e7ce6a133d053b1b6055f07ea51419 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Wed, 29 May 2024 19:46:46 -0400 Subject: [PATCH 048/110] fix ruff --- invokeai/app/invocations/mask.py | 6 +++--- invokeai/app/services/events/events_common.py | 3 +-- .../shared/sqlite_migrator/sqlite_migrator_common.py | 3 +-- 3 files changed, 5 insertions(+), 7 deletions(-) diff --git a/invokeai/app/invocations/mask.py b/invokeai/app/invocations/mask.py index 6b9524e7a8..6f54660847 100644 --- a/invokeai/app/invocations/mask.py +++ b/invokeai/app/invocations/mask.py @@ -25,9 +25,9 @@ class RectangleMaskInvocation(BaseInvocation, WithMetadata): def invoke(self, context: InvocationContext) -> MaskOutput: mask = torch.zeros((1, self.height, self.width), dtype=torch.bool) - mask[ - :, self.y_top : self.y_top + self.rectangle_height, self.x_left : self.x_left + self.rectangle_width - ] = True + mask[:, self.y_top : self.y_top + self.rectangle_height, self.x_left : self.x_left + self.rectangle_width] = ( + True + ) mask_tensor_name = context.tensors.save(mask) return MaskOutput( diff --git a/invokeai/app/services/events/events_common.py b/invokeai/app/services/events/events_common.py index f30b054f36..0adcaa2ab1 100644 --- a/invokeai/app/services/events/events_common.py +++ b/invokeai/app/services/events/events_common.py @@ -62,8 +62,7 @@ Provide a generic type to `TEvent` to specify the payload type. class FastAPIEventFunc(Protocol, Generic[TEvent]): - def __call__(self, event: FastAPIEvent[TEvent]) -> Optional[Coroutine[Any, Any, None]]: - ... + def __call__(self, event: FastAPIEvent[TEvent]) -> Optional[Coroutine[Any, Any, None]]: ... def register_events(events: set[type[TEvent]] | type[TEvent], func: FastAPIEventFunc[TEvent]) -> None: diff --git a/invokeai/app/services/shared/sqlite_migrator/sqlite_migrator_common.py b/invokeai/app/services/shared/sqlite_migrator/sqlite_migrator_common.py index 47ed5da505..9b2444dae4 100644 --- a/invokeai/app/services/shared/sqlite_migrator/sqlite_migrator_common.py +++ b/invokeai/app/services/shared/sqlite_migrator/sqlite_migrator_common.py @@ -17,8 +17,7 @@ class MigrateCallback(Protocol): See :class:`Migration` for an example. """ - def __call__(self, cursor: sqlite3.Cursor) -> None: - ... + def __call__(self, cursor: sqlite3.Cursor) -> None: ... class MigrationError(RuntimeError): From 68d628dc14807b6b4b2ea291a4c44efbc2dc3468 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Thu, 30 May 2024 06:40:04 -0400 Subject: [PATCH 049/110] use zip to iterate over image prompts and adapters --- invokeai/app/invocations/latent.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index c8d0b875a8..86e217e165 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -712,11 +712,11 @@ class DenoiseLatentsInvocation(BaseInvocation): """If IP-Adapter is enabled, then this function loads the requisite models and adds the image prompt conditioning data.""" ip_adapter_data_list = [] assert len(ip_adapters) == len(image_prompts) - for single_ip_adapter in ip_adapters: + for single_ip_adapter, (image_prompt_embeds, uncond_image_prompt_embeds) in zip( + ip_adapters, image_prompts, strict=False + ): ip_adapter_model = exit_stack.enter_context(context.models.load(single_ip_adapter.ip_adapter_model)) - image_prompt_embeds, uncond_image_prompt_embeds = image_prompts.pop(0) - mask_field = single_ip_adapter.mask mask = context.tensors.load(mask_field.tensor_name) if mask_field is not None else None mask = self._preprocess_regional_prompt_mask(mask, latent_height, latent_width, dtype=dtype) From 756108f6bd54b99cd2c5f4d96948204b4bc33e14 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Sat, 1 Jun 2024 08:54:28 -0400 Subject: [PATCH 050/110] Update invokeai/app/invocations/latent.py Co-authored-by: Ryan Dick --- invokeai/app/invocations/latent.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index 86e217e165..c74dd8d55a 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -711,9 +711,8 @@ class DenoiseLatentsInvocation(BaseInvocation): ) -> Optional[List[IPAdapterData]]: """If IP-Adapter is enabled, then this function loads the requisite models and adds the image prompt conditioning data.""" ip_adapter_data_list = [] - assert len(ip_adapters) == len(image_prompts) for single_ip_adapter, (image_prompt_embeds, uncond_image_prompt_embeds) in zip( - ip_adapters, image_prompts, strict=False + ip_adapters, image_prompts, strict=True ): ip_adapter_model = exit_stack.enter_context(context.models.load(single_ip_adapter.ip_adapter_model)) From 89a764a35905feb4863a84d1248b57ad599dc87d Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 3 Jun 2024 17:33:07 +1000 Subject: [PATCH 051/110] fix(ui): improve model metadata parsing fallback When the model in metadata's key no longer exists, fall back to fetching by name, base and type. This was the intention all along but the logic was never put in place. --- .../metadata/util/modelFetchingHelpers.ts | 24 ++++++++++++++----- 1 file changed, 18 insertions(+), 6 deletions(-) diff --git a/invokeai/frontend/web/src/features/metadata/util/modelFetchingHelpers.ts b/invokeai/frontend/web/src/features/metadata/util/modelFetchingHelpers.ts index a2db414937..4bd2436c0b 100644 --- a/invokeai/frontend/web/src/features/metadata/util/modelFetchingHelpers.ts +++ b/invokeai/frontend/web/src/features/metadata/util/modelFetchingHelpers.ts @@ -1,6 +1,7 @@ import { getStore } from 'app/store/nanostores/store'; import type { ModelIdentifierField } from 'features/nodes/types/common'; import { isModelIdentifier, isModelIdentifierV2 } from 'features/nodes/types/common'; +import type { ModelIdentifier } from 'features/nodes/types/v2/common'; import { modelsApi } from 'services/api/endpoints/models'; import type { AnyModelConfig, BaseModelType, ModelType } from 'services/api/types'; @@ -107,19 +108,30 @@ export const fetchModelConfigWithTypeGuard = async ( /** * Fetches the model key from a model identifier. This includes fetching the key for MM1 format model identifiers. - * @param modelIdentifier The model identifier. The MM2 format `{key: string}` simply extracts the key. The MM1 format - * `{model_name: string, base_model: BaseModelType}` must do a network request to fetch the key. + * @param modelIdentifier The model identifier. This can be a MM1 or MM2 identifier. In every case, we attempt to fetch + * the model config from the server to ensure that the model identifier is valid and represents an installed model. * @param type The type of model to fetch. This is used to fetch the key for MM1 format model identifiers. * @param message An optional custom message to include in the error if the model identifier is invalid. * @returns A promise that resolves to the model key. * @throws {InvalidModelConfigError} If the model identifier is invalid. */ -export const getModelKey = async (modelIdentifier: unknown, type: ModelType, message?: string): Promise => { +export const getModelKey = async ( + modelIdentifier: unknown | ModelIdentifierField | ModelIdentifier, + type: ModelType, + message?: string +): Promise => { if (isModelIdentifier(modelIdentifier)) { - return modelIdentifier.key; - } - if (isModelIdentifierV2(modelIdentifier)) { + try { + // Check if the model exists by key + return (await fetchModelConfig(modelIdentifier.key)).key; + } catch { + // If not, fetch the model key by name and base model + return (await fetchModelConfigByAttrs(modelIdentifier.name, modelIdentifier.base, type)).key; + } + } else if (isModelIdentifierV2(modelIdentifier)) { + // Try by old-format model identifier return (await fetchModelConfigByAttrs(modelIdentifier.model_name, modelIdentifier.base_model, type)).key; } + // Nope, couldn't find it throw new InvalidModelConfigError(message || `Invalid model identifier: ${modelIdentifier}`); }; From 64523c4b1b4add4d705cb98abe1b282af35c8bea Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 3 Jun 2024 18:34:35 +1000 Subject: [PATCH 052/110] fix(ui): handle concat when recalling prompts This required some minor reworking of of the logic to recall multiple items. I split this into a utility function that includes some special handling for concat. Closes #6478 --- .../src/features/metadata/util/handlers.ts | 123 +++++++++--------- 1 file changed, 65 insertions(+), 58 deletions(-) diff --git a/invokeai/frontend/web/src/features/metadata/util/handlers.ts b/invokeai/frontend/web/src/features/metadata/util/handlers.ts index 2829507dcd..33715cbbe1 100644 --- a/invokeai/frontend/web/src/features/metadata/util/handlers.ts +++ b/invokeai/frontend/web/src/features/metadata/util/handlers.ts @@ -1,4 +1,7 @@ +import { getStore } from 'app/store/nanostores/store'; +import { deepClone } from 'common/util/deepClone'; import { objectKeys } from 'common/util/objectKeys'; +import { shouldConcatPromptsChanged } from 'features/controlLayers/store/controlLayersSlice'; import type { Layer } from 'features/controlLayers/store/types'; import type { LoRA } from 'features/lora/store/loraSlice'; import type { @@ -16,6 +19,7 @@ import { validators } from 'features/metadata/util/validators'; import type { ModelIdentifierField } from 'features/nodes/types/common'; import { toast } from 'features/toast/toast'; import { t } from 'i18next'; +import { size } from 'lodash-es'; import { assert } from 'tsafe'; import { parsers } from './parsers'; @@ -376,54 +380,25 @@ export const handlers = { }), } as const; +type ParsedValue = Awaited>; +type RecallResults = Partial>; + export const parseAndRecallPrompts = async (metadata: unknown) => { - const results = await Promise.allSettled([ - handlers.positivePrompt.parse(metadata).then((positivePrompt) => { - if (!handlers.positivePrompt.recall) { - return; - } - handlers.positivePrompt?.recall(positivePrompt); - }), - handlers.negativePrompt.parse(metadata).then((negativePrompt) => { - if (!handlers.negativePrompt.recall) { - return; - } - handlers.negativePrompt?.recall(negativePrompt); - }), - handlers.sdxlPositiveStylePrompt.parse(metadata).then((sdxlPositiveStylePrompt) => { - if (!handlers.sdxlPositiveStylePrompt.recall) { - return; - } - handlers.sdxlPositiveStylePrompt?.recall(sdxlPositiveStylePrompt); - }), - handlers.sdxlNegativeStylePrompt.parse(metadata).then((sdxlNegativeStylePrompt) => { - if (!handlers.sdxlNegativeStylePrompt.recall) { - return; - } - handlers.sdxlNegativeStylePrompt?.recall(sdxlNegativeStylePrompt); - }), - ]); - if (results.some((result) => result.status === 'fulfilled')) { + const keysToRecall: (keyof typeof handlers)[] = [ + 'positivePrompt', + 'negativePrompt', + 'sdxlPositiveStylePrompt', + 'sdxlNegativeStylePrompt', + ]; + const recalled = await recallKeys(keysToRecall, metadata); + if (size(recalled) > 0) { parameterSetToast(t('metadata.allPrompts')); } }; export const parseAndRecallImageDimensions = async (metadata: unknown) => { - const results = await Promise.allSettled([ - handlers.width.parse(metadata).then((width) => { - if (!handlers.width.recall) { - return; - } - handlers.width?.recall(width); - }), - handlers.height.parse(metadata).then((height) => { - if (!handlers.height.recall) { - return; - } - handlers.height?.recall(height); - }), - ]); - if (results.some((result) => result.status === 'fulfilled')) { + const recalled = recallKeys(['width', 'height'], metadata); + if (size(recalled) > 0) { parameterSetToast(t('metadata.imageDimensions')); } }; @@ -438,28 +413,20 @@ export const parseAndRecallAllMetadata = async ( toControlLayers: boolean, skip: (keyof typeof handlers)[] = [] ) => { - const skipKeys = skip ?? []; + const skipKeys = deepClone(skip); if (toControlLayers) { skipKeys.push(...TO_CONTROL_LAYERS_SKIP_KEYS); } else { skipKeys.push(...NOT_TO_CONTROL_LAYERS_SKIP_KEYS); } - const results = await Promise.allSettled( - objectKeys(handlers) - .filter((key) => !skipKeys.includes(key)) - .map((key) => { - const { parse, recall } = handlers[key]; - return parse(metadata).then((value) => { - if (!recall) { - return; - } - /* @ts-expect-error The return type of parse and the input type of recall are guaranteed to be compatible. */ - recall(value); - }); - }) - ); - if (results.some((result) => result.status === 'fulfilled')) { + // We may need to take some further action depending on what was recalled. For example, we need to disable SDXL prompt + // concat if the negative or positive style prompt was set. Because the recalling is all async, we need to collect all + // results + const keysToRecall = objectKeys(handlers).filter((key) => !skipKeys.includes(key)); + const recalled = await recallKeys(keysToRecall, metadata); + + if (size(recalled) > 0) { toast({ id: 'PARAMETER_SET', title: t('toast.parametersSet'), @@ -473,3 +440,43 @@ export const parseAndRecallAllMetadata = async ( }); } }; + +/** + * Recalls a set of keys from metadata. + * Includes special handling for some metadata where recalling may have side effects. For example, recalling a "style" + * prompt that is different from the "positive" or "negative" prompt should disable prompt concatenation. + * @param keysToRecall An array of keys to recall. + * @param metadata The metadata to recall from + * @returns A promise that resolves to an object containing the recalled values. + */ +const recallKeys = async (keysToRecall: (keyof typeof handlers)[], metadata: unknown): Promise => { + const { dispatch } = getStore(); + const recalled: RecallResults = {}; + for (const key of keysToRecall) { + const { parse, recall } = handlers[key]; + if (!recall) { + continue; + } + try { + const value = await parse(metadata); + /* @ts-expect-error The return type of parse and the input type of recall are guaranteed to be compatible. */ + await recall(value); + recalled[key] = value; + } catch { + // no-op + } + } + + if ( + (recalled['sdxlPositiveStylePrompt'] && recalled['sdxlPositiveStylePrompt'] !== recalled['positivePrompt']) || + (recalled['sdxlNegativeStylePrompt'] && recalled['sdxlNegativeStylePrompt'] !== recalled['negativePrompt']) + ) { + // If we set the negative style prompt or positive style prompt, we should disable prompt concat + dispatch(shouldConcatPromptsChanged(false)); + } else { + // Otherwise, we should enable prompt concat + dispatch(shouldConcatPromptsChanged(true)); + } + + return recalled; +}; From 14372e3818da650ca4cc968adc873d7f8b667e88 Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Tue, 4 Jun 2024 08:33:42 +1000 Subject: [PATCH 053/110] fix(nodes): blend latents with weight=0 with DPMSolverSDEScheduler - Pass the seed from `latents_a` to the output latents. Fixed an issue where using `BlendLatentsInvocation` could result in different outputs during denoising even when the alpha or slerp weight was 0. ## Explanation `LatentsField` has an optional `seed` field. During denoising, if this `seed` field is not present, we **fall back to 0 for the seed**. The seed is used during denoising in a few ways: 1. Initializing the scheduler. The seed is used in two places in `invokeai/app/invocations/latent.py`. The `get_scheduler()` utility function has special handling for `DPMSolverSDEScheduler`, which appears to need a seed for deterministic outputs. `DenoiseLatentsInvocation.init_scheduler()` has special handling for schedulers that accept a generator - the generator needs to be seeded in a particular way. At the time of this commit, these are the Invoke-supported schedulers that need this seed: - DDIMScheduler - DDPMScheduler - DPMSolverMultistepScheduler - EulerAncestralDiscreteScheduler - EulerDiscreteScheduler - KDPM2AncestralDiscreteScheduler - LCMScheduler - TCDScheduler 2. Adding noise during inpainting. If a mask is used for denoising, and we are not using an inpainting model, we add noise to the unmasked area. If, for some reason, we have a mask but no noise, the seed is used to add noise. I wonder if we should instead assert that if a mask is provided, we also have noise. This is done in `invokeai/backend/stable_diffusion/diffusers_pipeline.py` in `StableDiffusionGeneratorPipeline.latents_from_embeddings()`. When we create noise to be used in denoising, we are expected to set `LatentsField.seed` to the seed used to create the noise. This introduces some awkwardness when we manipulate any "latents" that will be used for denoising. We have to pass the seed along for every operation. If the wrong seed or no seed is passed along, we can get unexpected outputs during denoising. One notable case relates to blending latents (slerping tensors). If we slerp two noise tensors (`LatentsField`s) _without_ passing along the seed from the source latents, when we denoise with a seed-dependent scheduler*, the schedulers use the fallback seed of 0 and we get the wrong output. This is most obvious when slerping with a weight of 0, in which case we expect the exact same output after denoising. *It looks like only the DPMSolver* schedulers are affected, but I haven't tested all of them. Passing the seed along in the output fixes this issue. --- invokeai/app/invocations/latent.py | 14 ++++++++++++-- 1 file changed, 12 insertions(+), 2 deletions(-) diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index c74dd8d55a..ede2443307 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -853,6 +853,16 @@ class DenoiseLatentsInvocation(BaseInvocation): # At some point, someone decided that schedulers that accept a generator should use the original seed with # all bits flipped. I don't know the original rationale for this, but now we must keep it like this for # reproducibility. + # + # These Invoke-supported schedulers accept a generator as of 2024-06-04: + # - DDIMScheduler + # - DDPMScheduler + # - DPMSolverMultistepScheduler + # - EulerAncestralDiscreteScheduler + # - EulerDiscreteScheduler + # - KDPM2AncestralDiscreteScheduler + # - LCMScheduler + # - TCDScheduler scheduler_step_kwargs.update({"generator": torch.Generator(device=device).manual_seed(seed ^ 0xFFFFFFFF)}) if isinstance(scheduler, TCDScheduler): scheduler_step_kwargs.update({"eta": 1.0}) @@ -1298,7 +1308,7 @@ class ImageToLatentsInvocation(BaseInvocation): title="Blend Latents", tags=["latents", "blend"], category="latents", - version="1.0.2", + version="1.0.3", ) class BlendLatentsInvocation(BaseInvocation): """Blend two latents using a given alpha. Latents must have same size.""" @@ -1377,7 +1387,7 @@ class BlendLatentsInvocation(BaseInvocation): TorchDevice.empty_cache() name = context.tensors.save(tensor=blended_latents) - return LatentsOutput.build(latents_name=name, latents=blended_latents) + return LatentsOutput.build(latents_name=name, latents=blended_latents, seed=self.latents_a.seed) # The Crop Latents node was copied from @skunkworxdark's implementation here: From c7546bc82e6ce4df40a904d82f6899eddeb8b653 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=D0=92=D0=B0=D1=81=D1=8F=D0=BD=D0=B0=D1=82=D0=BE=D1=80?= Date: Mon, 3 Jun 2024 20:41:54 +0200 Subject: [PATCH 054/110] translationBot(ui): update translation (Russian) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Currently translated at 100.0% (1261 of 1261 strings) translationBot(ui): update translation (Russian) Currently translated at 100.0% (1243 of 1243 strings) Co-authored-by: Васянатор Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/ru/ Translation: InvokeAI/Web UI --- invokeai/frontend/web/public/locales/ru.json | 90 +++++++++++++++++--- 1 file changed, 76 insertions(+), 14 deletions(-) diff --git a/invokeai/frontend/web/public/locales/ru.json b/invokeai/frontend/web/public/locales/ru.json index 03ff7eb706..2f7c711bf2 100644 --- a/invokeai/frontend/web/public/locales/ru.json +++ b/invokeai/frontend/web/public/locales/ru.json @@ -87,7 +87,11 @@ "viewing": "Просмотр", "editing": "Редактирование", "viewingDesc": "Просмотр изображений в режиме большой галереи", - "editingDesc": "Редактировать на холсте слоёв управления" + "editingDesc": "Редактировать на холсте слоёв управления", + "enabled": "Включено", + "disabled": "Отключено", + "comparingDesc": "Сравнение двух изображений", + "comparing": "Сравнение" }, "gallery": { "galleryImageSize": "Размер изображений", @@ -124,7 +128,23 @@ "bulkDownloadRequested": "Подготовка к скачиванию", "bulkDownloadRequestedDesc": "Ваш запрос на скачивание готовится. Это может занять несколько минут.", "bulkDownloadRequestFailed": "Возникла проблема при подготовке скачивания", - "alwaysShowImageSizeBadge": "Всегда показывать значок размера изображения" + "alwaysShowImageSizeBadge": "Всегда показывать значок размера изображения", + "openInViewer": "Открыть в просмотрщике", + "selectForCompare": "Выбрать для сравнения", + "hover": "Наведение", + "swapImages": "Поменять местами", + "stretchToFit": "Растягивание до нужного размера", + "exitCompare": "Выйти из сравнения", + "compareHelp4": "Нажмите Z или Esc для выхода.", + "compareImage": "Сравнить изображение", + "viewerImage": "Изображение просмотрщика", + "selectAnImageToCompare": "Выберите изображение для сравнения", + "slider": "Слайдер", + "sideBySide": "Бок о бок", + "compareOptions": "Варианты сравнения", + "compareHelp1": "Удерживайте Alt при нажатии на изображение в галерее или при помощи клавиш со стрелками, чтобы изменить сравниваемое изображение.", + "compareHelp2": "Нажмите M, чтобы переключиться между режимами сравнения.", + "compareHelp3": "Нажмите C, чтобы поменять местами сравниваемые изображения." }, "hotkeys": { "keyboardShortcuts": "Горячие клавиши", @@ -528,7 +548,20 @@ "missingFieldTemplate": "Отсутствует шаблон поля", "addingImagesTo": "Добавление изображений в", "invoke": "Создать", - "imageNotProcessedForControlAdapter": "Изображение адаптера контроля №{{number}} не обрабатывается" + "imageNotProcessedForControlAdapter": "Изображение адаптера контроля №{{number}} не обрабатывается", + "layer": { + "controlAdapterImageNotProcessed": "Изображение адаптера контроля не обработано", + "ipAdapterNoModelSelected": "IP адаптер не выбран", + "controlAdapterNoModelSelected": "не выбрана модель адаптера контроля", + "controlAdapterIncompatibleBaseModel": "несовместимая базовая модель адаптера контроля", + "controlAdapterNoImageSelected": "не выбрано изображение контрольного адаптера", + "initialImageNoImageSelected": "начальное изображение не выбрано", + "rgNoRegion": "регион не выбран", + "rgNoPromptsOrIPAdapters": "нет текстовых запросов или IP-адаптеров", + "ipAdapterIncompatibleBaseModel": "несовместимая базовая модель IP-адаптера", + "t2iAdapterIncompatibleDimensions": "Адаптер T2I требует, чтобы размеры изображения были кратны {{multiple}}", + "ipAdapterNoImageSelected": "изображение IP-адаптера не выбрано" + } }, "isAllowedToUpscale": { "useX2Model": "Изображение слишком велико для увеличения с помощью модели x4. Используйте модель x2", @@ -606,12 +639,12 @@ "connected": "Подключено к серверу", "canceled": "Обработка отменена", "uploadFailedInvalidUploadDesc": "Должно быть одно изображение в формате PNG или JPEG", - "parameterNotSet": "Параметр {{parameter}} не задан", - "parameterSet": "Параметр {{parameter}} задан", + "parameterNotSet": "Параметр не задан", + "parameterSet": "Параметр задан", "problemCopyingImage": "Не удается скопировать изображение", - "baseModelChangedCleared_one": "Базовая модель изменила, очистила или отключила {{count}} несовместимую подмодель", - "baseModelChangedCleared_few": "Базовая модель изменила, очистила или отключила {{count}} несовместимые подмодели", - "baseModelChangedCleared_many": "Базовая модель изменила, очистила или отключила {{count}} несовместимых подмоделей", + "baseModelChangedCleared_one": "Очищена или отключена {{count}} несовместимая подмодель", + "baseModelChangedCleared_few": "Очищены или отключены {{count}} несовместимые подмодели", + "baseModelChangedCleared_many": "Очищены или отключены {{count}} несовместимых подмоделей", "imageSavingFailed": "Не удалось сохранить изображение", "canvasSentControlnetAssets": "Холст отправлен в ControlNet и ресурсы", "problemCopyingCanvasDesc": "Невозможно экспортировать базовый слой", @@ -652,7 +685,17 @@ "resetInitialImage": "Сбросить начальное изображение", "prunedQueue": "Урезанная очередь", "modelImportCanceled": "Импорт модели отменен", - "parameters": "Параметры" + "parameters": "Параметры", + "parameterSetDesc": "Задан {{parameter}}", + "parameterNotSetDesc": "Невозможно задать {{parameter}}", + "baseModelChanged": "Базовая модель сменена", + "parameterNotSetDescWithMessage": "Не удалось задать {{parameter}}: {{message}}", + "parametersSet": "Параметры заданы", + "errorCopied": "Ошибка скопирована", + "sessionRef": "Сессия: {{sessionId}}", + "outOfMemoryError": "Ошибка нехватки памяти", + "outOfMemoryErrorDesc": "Ваши текущие настройки генерации превышают возможности системы. Пожалуйста, измените настройки и повторите попытку.", + "somethingWentWrong": "Что-то пошло не так" }, "tooltip": { "feature": { @@ -739,7 +782,8 @@ "loadMore": "Загрузить больше", "resetUI": "$t(accessibility.reset) интерфейс", "createIssue": "Сообщить о проблеме", - "about": "Об этом" + "about": "Об этом", + "submitSupportTicket": "Отправить тикет в службу поддержки" }, "nodes": { "zoomInNodes": "Увеличьте масштаб", @@ -832,7 +876,7 @@ "workflowName": "Название", "collection": "Коллекция", "unknownErrorValidatingWorkflow": "Неизвестная ошибка при проверке рабочего процесса", - "collectionFieldType": "Коллекция {{name}}", + "collectionFieldType": "{{name}} (Коллекция)", "workflowNotes": "Примечания", "string": "Строка", "unknownNodeType": "Неизвестный тип узла", @@ -848,7 +892,7 @@ "targetNodeDoesNotExist": "Недопустимое ребро: целевой/входной узел {{node}} не существует", "mismatchedVersion": "Недопустимый узел: узел {{node}} типа {{type}} имеет несоответствующую версию (попробовать обновить?)", "unknownFieldType": "$t(nodes.unknownField) тип: {{type}}", - "collectionOrScalarFieldType": "Коллекция | Скаляр {{name}}", + "collectionOrScalarFieldType": "{{name}} (Один или коллекция)", "betaDesc": "Этот вызов находится в бета-версии. Пока он не станет стабильным, в нем могут происходить изменения при обновлении приложений. Мы планируем поддерживать этот вызов в течение длительного времени.", "nodeVersion": "Версия узла", "loadingNodes": "Загрузка узлов...", @@ -870,7 +914,16 @@ "noFieldsViewMode": "В этом рабочем процессе нет выбранных полей для отображения. Просмотрите полный рабочий процесс для настройки значений.", "graph": "График", "showEdgeLabels": "Показать метки на ребрах", - "showEdgeLabelsHelp": "Показать метки на ребрах, указывающие на соединенные узлы" + "showEdgeLabelsHelp": "Показать метки на ребрах, указывающие на соединенные узлы", + "cannotMixAndMatchCollectionItemTypes": "Невозможно смешивать и сопоставлять типы элементов коллекции", + "missingNode": "Отсутствует узел вызова", + "missingInvocationTemplate": "Отсутствует шаблон вызова", + "missingFieldTemplate": "Отсутствующий шаблон поля", + "singleFieldType": "{{name}} (Один)", + "noGraph": "Нет графика", + "imageAccessError": "Невозможно найти изображение {{image_name}}, сбрасываем на значение по умолчанию", + "boardAccessError": "Невозможно найти доску {{board_id}}, сбрасываем на значение по умолчанию", + "modelAccessError": "Невозможно найти модель {{key}}, сброс на модель по умолчанию" }, "controlnet": { "amult": "a_mult", @@ -1441,7 +1494,16 @@ "clearQueueAlertDialog2": "Вы уверены, что хотите очистить очередь?", "item": "Элемент", "graphFailedToQueue": "Не удалось поставить график в очередь", - "openQueue": "Открыть очередь" + "openQueue": "Открыть очередь", + "prompts_one": "Запрос", + "prompts_few": "Запроса", + "prompts_many": "Запросов", + "iterations_one": "Итерация", + "iterations_few": "Итерации", + "iterations_many": "Итераций", + "generations_one": "Генерация", + "generations_few": "Генерации", + "generations_many": "Генераций" }, "sdxl": { "refinerStart": "Запуск доработчика", From 6bb1189c88aeea2254a55454064939be4ab7ece9 Mon Sep 17 00:00:00 2001 From: Riccardo Giovanetti Date: Mon, 3 Jun 2024 20:41:54 +0200 Subject: [PATCH 055/110] translationBot(ui): update translation (Italian) Currently translated at 98.5% (1243 of 1261 strings) translationBot(ui): update translation (Italian) Currently translated at 98.5% (1243 of 1261 strings) translationBot(ui): update translation (Italian) Currently translated at 98.5% (1225 of 1243 strings) translationBot(ui): update translation (Italian) Currently translated at 98.5% (1225 of 1243 strings) Co-authored-by: Riccardo Giovanetti Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/it/ Translation: InvokeAI/Web UI --- invokeai/frontend/web/public/locales/it.json | 94 +++++++++++++------- 1 file changed, 64 insertions(+), 30 deletions(-) diff --git a/invokeai/frontend/web/public/locales/it.json b/invokeai/frontend/web/public/locales/it.json index bd82dd9a5b..3c0079de59 100644 --- a/invokeai/frontend/web/public/locales/it.json +++ b/invokeai/frontend/web/public/locales/it.json @@ -45,7 +45,7 @@ "outputs": "Risultati", "data": "Dati", "somethingWentWrong": "Qualcosa è andato storto", - "copyError": "$t(gallery.copy) Errore", + "copyError": "Errore $t(gallery.copy)", "input": "Ingresso", "notInstalled": "Non $t(common.installed)", "unknownError": "Errore sconosciuto", @@ -85,7 +85,11 @@ "viewing": "Visualizza", "viewingDesc": "Rivedi le immagini in un'ampia vista della galleria", "editing": "Modifica", - "editingDesc": "Modifica nell'area Livelli di controllo" + "editingDesc": "Modifica nell'area Livelli di controllo", + "enabled": "Abilitato", + "disabled": "Disabilitato", + "comparingDesc": "Confronta due immagini", + "comparing": "Confronta" }, "gallery": { "galleryImageSize": "Dimensione dell'immagine", @@ -122,14 +126,30 @@ "bulkDownloadRequestedDesc": "La tua richiesta di download è in preparazione. L'operazione potrebbe richiedere alcuni istanti.", "bulkDownloadRequestFailed": "Problema durante la preparazione del download", "bulkDownloadFailed": "Scaricamento fallito", - "alwaysShowImageSizeBadge": "Mostra sempre le dimensioni dell'immagine" + "alwaysShowImageSizeBadge": "Mostra sempre le dimensioni dell'immagine", + "openInViewer": "Apri nel visualizzatore", + "selectForCompare": "Seleziona per il confronto", + "selectAnImageToCompare": "Seleziona un'immagine da confrontare", + "slider": "Cursore", + "sideBySide": "Fianco a Fianco", + "compareImage": "Immagine di confronto", + "viewerImage": "Immagine visualizzata", + "hover": "Al passaggio del mouse", + "swapImages": "Scambia le immagini", + "compareOptions": "Opzioni di confronto", + "stretchToFit": "Scala per adattare", + "exitCompare": "Esci dal confronto", + "compareHelp1": "Tieni premuto Alt mentre fai clic su un'immagine della galleria o usi i tasti freccia per cambiare l'immagine di confronto.", + "compareHelp2": "Premi M per scorrere le modalità di confronto.", + "compareHelp3": "Premi C per scambiare le immagini confrontate.", + "compareHelp4": "Premi Z o Esc per uscire." }, "hotkeys": { "keyboardShortcuts": "Tasti di scelta rapida", "appHotkeys": "Applicazione", "generalHotkeys": "Generale", "galleryHotkeys": "Galleria", - "unifiedCanvasHotkeys": "Tela Unificata", + "unifiedCanvasHotkeys": "Tela", "invoke": { "title": "Invoke", "desc": "Genera un'immagine" @@ -147,8 +167,8 @@ "desc": "Apre e chiude il pannello delle opzioni" }, "pinOptions": { - "title": "Appunta le opzioni", - "desc": "Blocca il pannello delle opzioni" + "title": "Fissa le opzioni", + "desc": "Fissa il pannello delle opzioni" }, "toggleGallery": { "title": "Attiva/disattiva galleria", @@ -332,14 +352,14 @@ "title": "Annulla e cancella" }, "resetOptionsAndGallery": { - "title": "Ripristina Opzioni e Galleria", - "desc": "Reimposta le opzioni e i pannelli della galleria" + "title": "Ripristina le opzioni e la galleria", + "desc": "Reimposta i pannelli delle opzioni e della galleria" }, "searchHotkeys": "Cerca tasti di scelta rapida", "noHotkeysFound": "Nessun tasto di scelta rapida trovato", "toggleOptionsAndGallery": { "desc": "Apre e chiude le opzioni e i pannelli della galleria", - "title": "Attiva/disattiva le Opzioni e la Galleria" + "title": "Attiva/disattiva le opzioni e la galleria" }, "clearSearch": "Cancella ricerca", "remixImage": { @@ -348,7 +368,7 @@ }, "toggleViewer": { "title": "Attiva/disattiva il visualizzatore di immagini", - "desc": "Passa dal Visualizzatore immagini all'area di lavoro per la scheda corrente." + "desc": "Passa dal visualizzatore immagini all'area di lavoro per la scheda corrente." } }, "modelManager": { @@ -378,7 +398,7 @@ "convertToDiffusers": "Converti in Diffusori", "convertToDiffusersHelpText2": "Questo processo sostituirà la voce in Gestione Modelli con la versione Diffusori dello stesso modello.", "convertToDiffusersHelpText4": "Questo è un processo una tantum. Potrebbero essere necessari circa 30-60 secondi a seconda delle specifiche del tuo computer.", - "convertToDiffusersHelpText5": "Assicurati di avere spazio su disco sufficiente. I modelli generalmente variano tra 2 GB e 7 GB di dimensioni.", + "convertToDiffusersHelpText5": "Assicurati di avere spazio su disco sufficiente. I modelli generalmente variano tra 2 GB e 7 GB in dimensione.", "convertToDiffusersHelpText6": "Vuoi convertire questo modello?", "modelConverted": "Modello convertito", "alpha": "Alpha", @@ -528,7 +548,7 @@ "layer": { "initialImageNoImageSelected": "Nessuna immagine iniziale selezionata", "t2iAdapterIncompatibleDimensions": "L'adattatore T2I richiede che la dimensione dell'immagine sia un multiplo di {{multiple}}", - "controlAdapterNoModelSelected": "Nessun modello di Adattatore di Controllo selezionato", + "controlAdapterNoModelSelected": "Nessun modello di adattatore di controllo selezionato", "controlAdapterIncompatibleBaseModel": "Il modello base dell'adattatore di controllo non è compatibile", "controlAdapterNoImageSelected": "Nessuna immagine dell'adattatore di controllo selezionata", "controlAdapterImageNotProcessed": "Immagine dell'adattatore di controllo non elaborata", @@ -606,25 +626,25 @@ "canvasMerged": "Tela unita", "sentToImageToImage": "Inviato a Generazione da immagine", "sentToUnifiedCanvas": "Inviato alla Tela", - "parametersNotSet": "Parametri non impostati", + "parametersNotSet": "Parametri non richiamati", "metadataLoadFailed": "Impossibile caricare i metadati", "serverError": "Errore del Server", - "connected": "Connesso al Server", + "connected": "Connesso al server", "canceled": "Elaborazione annullata", "uploadFailedInvalidUploadDesc": "Deve essere una singola immagine PNG o JPEG", - "parameterSet": "{{parameter}} impostato", - "parameterNotSet": "{{parameter}} non impostato", + "parameterSet": "Parametro richiamato", + "parameterNotSet": "Parametro non richiamato", "problemCopyingImage": "Impossibile copiare l'immagine", - "baseModelChangedCleared_one": "Il modello base è stato modificato, cancellato o disabilitato {{count}} sotto-modello incompatibile", - "baseModelChangedCleared_many": "Il modello base è stato modificato, cancellato o disabilitato {{count}} sotto-modelli incompatibili", - "baseModelChangedCleared_other": "Il modello base è stato modificato, cancellato o disabilitato {{count}} sotto-modelli incompatibili", + "baseModelChangedCleared_one": "Cancellato o disabilitato {{count}} sottomodello incompatibile", + "baseModelChangedCleared_many": "Cancellati o disabilitati {{count}} sottomodelli incompatibili", + "baseModelChangedCleared_other": "Cancellati o disabilitati {{count}} sottomodelli incompatibili", "imageSavingFailed": "Salvataggio dell'immagine non riuscito", "canvasSentControlnetAssets": "Tela inviata a ControlNet & Risorse", "problemCopyingCanvasDesc": "Impossibile copiare la tela", "loadedWithWarnings": "Flusso di lavoro caricato con avvisi", "canvasCopiedClipboard": "Tela copiata negli appunti", "maskSavedAssets": "Maschera salvata nelle risorse", - "problemDownloadingCanvas": "Problema durante il download della tela", + "problemDownloadingCanvas": "Problema durante lo scarico della tela", "problemMergingCanvas": "Problema nell'unione delle tele", "imageUploaded": "Immagine caricata", "addedToBoard": "Aggiunto alla bacheca", @@ -658,7 +678,17 @@ "problemDownloadingImage": "Impossibile scaricare l'immagine", "prunedQueue": "Coda ripulita", "modelImportCanceled": "Importazione del modello annullata", - "parameters": "Parametri" + "parameters": "Parametri", + "parameterSetDesc": "{{parameter}} richiamato", + "parameterNotSetDesc": "Impossibile richiamare {{parameter}}", + "parameterNotSetDescWithMessage": "Impossibile richiamare {{parameter}}: {{message}}", + "parametersSet": "Parametri richiamati", + "errorCopied": "Errore copiato", + "outOfMemoryError": "Errore di memoria esaurita", + "baseModelChanged": "Modello base modificato", + "sessionRef": "Sessione: {{sessionId}}", + "somethingWentWrong": "Qualcosa è andato storto", + "outOfMemoryErrorDesc": "Le impostazioni della generazione attuale superano la capacità del sistema. Modifica le impostazioni e riprova." }, "tooltip": { "feature": { @@ -674,7 +704,7 @@ "layer": "Livello", "base": "Base", "mask": "Maschera", - "maskingOptions": "Opzioni di mascheramento", + "maskingOptions": "Opzioni maschera", "enableMask": "Abilita maschera", "preserveMaskedArea": "Mantieni area mascherata", "clearMask": "Cancella maschera (Shift+C)", @@ -745,7 +775,8 @@ "mode": "Modalità", "resetUI": "$t(accessibility.reset) l'Interfaccia Utente", "createIssue": "Segnala un problema", - "about": "Informazioni" + "about": "Informazioni", + "submitSupportTicket": "Invia ticket di supporto" }, "nodes": { "zoomOutNodes": "Rimpicciolire", @@ -790,7 +821,7 @@ "workflowNotes": "Note", "versionUnknown": " Versione sconosciuta", "unableToValidateWorkflow": "Impossibile convalidare il flusso di lavoro", - "updateApp": "Aggiorna App", + "updateApp": "Aggiorna Applicazione", "unableToLoadWorkflow": "Impossibile caricare il flusso di lavoro", "updateNode": "Aggiorna nodo", "version": "Versione", @@ -882,11 +913,14 @@ "missingNode": "Nodo di invocazione mancante", "missingInvocationTemplate": "Modello di invocazione mancante", "missingFieldTemplate": "Modello di campo mancante", - "singleFieldType": "{{name}} (Singola)" + "singleFieldType": "{{name}} (Singola)", + "imageAccessError": "Impossibile trovare l'immagine {{image_name}}, ripristino delle impostazioni predefinite", + "boardAccessError": "Impossibile trovare la bacheca {{board_id}}, ripristino ai valori predefiniti", + "modelAccessError": "Impossibile trovare il modello {{key}}, ripristino ai valori predefiniti" }, "boards": { "autoAddBoard": "Aggiungi automaticamente bacheca", - "menuItemAutoAdd": "Aggiungi automaticamente a questa Bacheca", + "menuItemAutoAdd": "Aggiungi automaticamente a questa bacheca", "cancel": "Annulla", "addBoard": "Aggiungi Bacheca", "bottomMessage": "L'eliminazione di questa bacheca e delle sue immagini ripristinerà tutte le funzionalità che le stanno attualmente utilizzando.", @@ -898,7 +932,7 @@ "myBoard": "Bacheca", "searchBoard": "Cerca bacheche ...", "noMatching": "Nessuna bacheca corrispondente", - "selectBoard": "Seleziona una Bacheca", + "selectBoard": "Seleziona una bacheca", "uncategorized": "Non categorizzato", "downloadBoard": "Scarica la bacheca", "deleteBoardOnly": "solo la Bacheca", @@ -919,7 +953,7 @@ "control": "Controllo", "crop": "Ritaglia", "depthMidas": "Profondità (Midas)", - "detectResolution": "Rileva risoluzione", + "detectResolution": "Rileva la risoluzione", "controlMode": "Modalità di controllo", "cannyDescription": "Canny rilevamento bordi", "depthZoe": "Profondità (Zoe)", @@ -930,7 +964,7 @@ "showAdvanced": "Mostra opzioni Avanzate", "bgth": "Soglia rimozione sfondo", "importImageFromCanvas": "Importa immagine dalla Tela", - "lineartDescription": "Converte l'immagine in lineart", + "lineartDescription": "Converte l'immagine in linea", "importMaskFromCanvas": "Importa maschera dalla Tela", "hideAdvanced": "Nascondi opzioni avanzate", "resetControlImage": "Reimposta immagine di controllo", @@ -946,7 +980,7 @@ "pidiDescription": "Elaborazione immagini PIDI", "fill": "Riempie", "colorMapDescription": "Genera una mappa dei colori dall'immagine", - "lineartAnimeDescription": "Elaborazione lineart in stile anime", + "lineartAnimeDescription": "Elaborazione linea in stile anime", "imageResolution": "Risoluzione dell'immagine", "colorMap": "Colore", "lowThreshold": "Soglia inferiore", From 71fedd1a070d09cffc21b95a157f0b084c25ab32 Mon Sep 17 00:00:00 2001 From: Bruno Castillejo Date: Mon, 3 Jun 2024 20:41:54 +0200 Subject: [PATCH 056/110] translationBot(ui): update translation (Spanish) Currently translated at 34.3% (427 of 1243 strings) Co-authored-by: Bruno Castillejo Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/es/ Translation: InvokeAI/Web UI --- invokeai/frontend/web/public/locales/es.json | 56 ++++++++++++++++++-- 1 file changed, 52 insertions(+), 4 deletions(-) diff --git a/invokeai/frontend/web/public/locales/es.json b/invokeai/frontend/web/public/locales/es.json index 169bfdb066..b706c8de6d 100644 --- a/invokeai/frontend/web/public/locales/es.json +++ b/invokeai/frontend/web/public/locales/es.json @@ -6,7 +6,7 @@ "settingsLabel": "Ajustes", "img2img": "Imagen a Imagen", "unifiedCanvas": "Lienzo Unificado", - "nodes": "Editor del flujo de trabajo", + "nodes": "Flujos de trabajo", "upload": "Subir imagen", "load": "Cargar", "statusDisconnected": "Desconectado", @@ -14,7 +14,7 @@ "discordLabel": "Discord", "back": "Atrás", "loading": "Cargando", - "postprocessing": "Tratamiento posterior", + "postprocessing": "Postprocesado", "txt2img": "De texto a imagen", "accept": "Aceptar", "cancel": "Cancelar", @@ -42,7 +42,42 @@ "copy": "Copiar", "beta": "Beta", "on": "En", - "aboutDesc": "¿Utilizas Invoke para trabajar? Mira aquí:" + "aboutDesc": "¿Utilizas Invoke para trabajar? Mira aquí:", + "installed": "Instalado", + "green": "Verde", + "editor": "Editor", + "orderBy": "Ordenar por", + "file": "Archivo", + "goTo": "Ir a", + "imageFailedToLoad": "No se puede cargar la imagen", + "saveAs": "Guardar Como", + "somethingWentWrong": "Algo salió mal", + "nextPage": "Página Siguiente", + "selected": "Seleccionado", + "tab": "Tabulador", + "positivePrompt": "Prompt Positivo", + "negativePrompt": "Prompt Negativo", + "error": "Error", + "format": "formato", + "unknown": "Desconocido", + "input": "Entrada", + "nodeEditor": "Editor de nodos", + "template": "Plantilla", + "prevPage": "Página Anterior", + "red": "Rojo", + "alpha": "Transparencia", + "outputs": "Salidas", + "editing": "Editando", + "learnMore": "Aprende más", + "enabled": "Activado", + "disabled": "Desactivado", + "folder": "Carpeta", + "updated": "Actualizado", + "created": "Creado", + "save": "Guardar", + "unknownError": "Error Desconocido", + "blue": "Azul", + "viewingDesc": "Revisar imágenes en una vista de galería grande" }, "gallery": { "galleryImageSize": "Tamaño de la imagen", @@ -467,7 +502,8 @@ "about": "Acerca de", "createIssue": "Crear un problema", "resetUI": "Interfaz de usuario $t(accessibility.reset)", - "mode": "Modo" + "mode": "Modo", + "submitSupportTicket": "Enviar Ticket de Soporte" }, "nodes": { "zoomInNodes": "Acercar", @@ -543,5 +579,17 @@ "layers_one": "Capa", "layers_many": "Capas", "layers_other": "Capas" + }, + "controlnet": { + "crop": "Cortar", + "delete": "Eliminar", + "depthAnythingDescription": "Generación de mapa de profundidad usando la técnica de Depth Anything", + "duplicate": "Duplicar", + "colorMapDescription": "Genera un mapa de color desde la imagen", + "depthMidasDescription": "Generación de mapa de profundidad usando Midas", + "balanced": "Equilibrado", + "beginEndStepPercent": "Inicio / Final Porcentaje de pasos", + "detectResolution": "Detectar resolución", + "beginEndStepPercentShort": "Inicio / Final %" } } From 4af8699a007a18749079ab580e7ee8f18b7eef39 Mon Sep 17 00:00:00 2001 From: gallegonovato Date: Mon, 3 Jun 2024 20:41:55 +0200 Subject: [PATCH 057/110] translationBot(ui): update translation (Spanish) Currently translated at 34.3% (427 of 1243 strings) Co-authored-by: gallegonovato Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/es/ Translation: InvokeAI/Web UI --- invokeai/frontend/web/public/locales/es.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/invokeai/frontend/web/public/locales/es.json b/invokeai/frontend/web/public/locales/es.json index b706c8de6d..52ee3b5fe3 100644 --- a/invokeai/frontend/web/public/locales/es.json +++ b/invokeai/frontend/web/public/locales/es.json @@ -586,7 +586,7 @@ "depthAnythingDescription": "Generación de mapa de profundidad usando la técnica de Depth Anything", "duplicate": "Duplicar", "colorMapDescription": "Genera un mapa de color desde la imagen", - "depthMidasDescription": "Generación de mapa de profundidad usando Midas", + "depthMidasDescription": "Crea un mapa de profundidad con Midas", "balanced": "Equilibrado", "beginEndStepPercent": "Inicio / Final Porcentaje de pasos", "detectResolution": "Detectar resolución", From 2903060154452534424fc80b8c9bf6e64eab68ec Mon Sep 17 00:00:00 2001 From: Ettore Atalan Date: Mon, 3 Jun 2024 20:41:55 +0200 Subject: [PATCH 058/110] translationBot(ui): update translation (German) Currently translated at 67.0% (834 of 1243 strings) Co-authored-by: Ettore Atalan Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/de/ Translation: InvokeAI/Web UI --- invokeai/frontend/web/public/locales/de.json | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/invokeai/frontend/web/public/locales/de.json b/invokeai/frontend/web/public/locales/de.json index 1db283aabd..2da27264a1 100644 --- a/invokeai/frontend/web/public/locales/de.json +++ b/invokeai/frontend/web/public/locales/de.json @@ -1021,7 +1021,8 @@ "float": "Kommazahlen", "enum": "Aufzählung", "fullyContainNodes": "Vollständig ausgewählte Nodes auswählen", - "editMode": "Im Workflow-Editor bearbeiten" + "editMode": "Im Workflow-Editor bearbeiten", + "resetToDefaultValue": "Auf Standardwert zurücksetzen" }, "hrf": { "enableHrf": "Korrektur für hohe Auflösungen", From 669d92d8db8773030fa44fa24ef8690342c19d6f Mon Sep 17 00:00:00 2001 From: hugoalh Date: Mon, 3 Jun 2024 20:41:55 +0200 Subject: [PATCH 059/110] translationBot(ui): update translation (Chinese (Traditional)) Currently translated at 14.1% (179 of 1261 strings) Co-authored-by: hugoalh Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/zh_Hant/ Translation: InvokeAI/Web UI --- .../frontend/web/public/locales/zh_Hant.json | 232 +++++++++++++++++- 1 file changed, 227 insertions(+), 5 deletions(-) diff --git a/invokeai/frontend/web/public/locales/zh_Hant.json b/invokeai/frontend/web/public/locales/zh_Hant.json index 454ae4c983..7748947478 100644 --- a/invokeai/frontend/web/public/locales/zh_Hant.json +++ b/invokeai/frontend/web/public/locales/zh_Hant.json @@ -1,6 +1,6 @@ { "common": { - "nodes": "節點", + "nodes": "工作流程", "img2img": "圖片轉圖片", "statusDisconnected": "已中斷連線", "back": "返回", @@ -11,17 +11,239 @@ "reportBugLabel": "回報錯誤", "githubLabel": "GitHub", "hotkeysLabel": "快捷鍵", - "languagePickerLabel": "切換語言", + "languagePickerLabel": "語言", "unifiedCanvas": "統一畫布", "cancel": "取消", - "txt2img": "文字轉圖片" + "txt2img": "文字轉圖片", + "controlNet": "ControlNet", + "advanced": "進階", + "folder": "資料夾", + "installed": "已安裝", + "accept": "接受", + "goTo": "前往", + "input": "輸入", + "random": "隨機", + "selected": "已選擇", + "communityLabel": "社群", + "loading": "載入中", + "delete": "刪除", + "copy": "複製", + "error": "錯誤", + "file": "檔案", + "format": "格式", + "imageFailedToLoad": "無法載入圖片" }, "accessibility": { "invokeProgressBar": "Invoke 進度條", "uploadImage": "上傳圖片", - "reset": "重設", + "reset": "重置", "nextImage": "下一張圖片", "previousImage": "上一張圖片", - "menu": "選單" + "menu": "選單", + "loadMore": "載入更多", + "about": "關於", + "createIssue": "建立問題", + "resetUI": "$t(accessibility.reset) 介面", + "submitSupportTicket": "提交支援工單", + "mode": "模式" + }, + "boards": { + "loading": "載入中…", + "movingImagesToBoard_other": "正在移動 {{count}} 張圖片至板上：", + "move": "移動", + "uncategorized": "未分類", + "cancel": "取消" + }, + "metadata": { + "workflow": "工作流程", + "steps": "步數", + "model": "模型", + "seed": "種子", + "vae": "VAE", + "seamless": "無縫", + "metadata": "元數據", + "width": "寬度", + "height": "高度" + }, + "accordions": { + "control": { + "title": "控制" + }, + "compositing": { + "title": "合成" + }, + "advanced": { + "title": "進階", + "options": "$t(accordions.advanced.title) 選項" + } + }, + "hotkeys": { + "nodesHotkeys": "節點", + "cancel": { + "title": "取消" + }, + "generalHotkeys": "一般", + "keyboardShortcuts": "快捷鍵", + "appHotkeys": "應用程式" + }, + "modelManager": { + "advanced": "進階", + "allModels": "全部模型", + "variant": "變體", + "config": "配置", + "model": "模型", + "selected": "已選擇", + "huggingFace": "HuggingFace", + "install": "安裝", + "metadata": "元數據", + "delete": "刪除", + "description": "描述", + "cancel": "取消", + "convert": "轉換", + "manual": "手動", + "none": "無", + "name": "名稱", + "load": "載入", + "height": "高度", + "width": "寬度", + "search": "搜尋", + "vae": "VAE", + "settings": "設定" + }, + "controlnet": { + "mlsd": "M-LSD", + "canny": "Canny", + "duplicate": "重複", + "none": "無", + "pidi": "PIDI", + "h": "H", + "balanced": "平衡", + "crop": "裁切", + "processor": "處理器", + "control": "控制", + "f": "F", + "lineart": "線條藝術", + "w": "W", + "hed": "HED", + "delete": "刪除" + }, + "queue": { + "queue": "佇列", + "canceled": "已取消", + "failed": "已失敗", + "completed": "已完成", + "cancel": "取消", + "session": "工作階段", + "batch": "批量", + "item": "項目", + "completedIn": "完成於", + "notReady": "無法排隊" + }, + "parameters": { + "cancel": { + "cancel": "取消" + }, + "height": "高度", + "type": "類型", + "symmetry": "對稱性", + "images": "圖片", + "width": "寬度", + "coherenceMode": "模式", + "seed": "種子", + "general": "一般", + "strength": "強度", + "steps": "步數", + "info": "資訊" + }, + "settings": { + "beta": "Beta", + "developer": "開發者", + "general": "一般", + "models": "模型" + }, + "popovers": { + "paramModel": { + "heading": "模型" + }, + "compositingCoherenceMode": { + "heading": "模式" + }, + "paramSteps": { + "heading": "步數" + }, + "controlNetProcessor": { + "heading": "處理器" + }, + "paramVAE": { + "heading": "VAE" + }, + "paramHeight": { + "heading": "高度" + }, + "paramSeed": { + "heading": "種子" + }, + "paramWidth": { + "heading": "寬度" + }, + "refinerSteps": { + "heading": "步數" + } + }, + "unifiedCanvas": { + "undo": "復原", + "mask": "遮罩", + "eraser": "橡皮擦", + "antialiasing": "抗鋸齒", + "redo": "重做", + "layer": "圖層", + "accept": "接受", + "brush": "刷子", + "move": "移動", + "brushSize": "大小" + }, + "nodes": { + "workflowName": "名稱", + "notes": "註釋", + "workflowVersion": "版本", + "workflowNotes": "註釋", + "executionStateError": "錯誤", + "unableToUpdateNodes_other": "無法更新 {{count}} 個節點", + "integer": "整數", + "workflow": "工作流程", + "enum": "枚舉", + "edit": "編輯", + "string": "字串", + "workflowTags": "標籤", + "node": "節點", + "boolean": "布林值", + "workflowAuthor": "作者", + "version": "版本", + "executionStateCompleted": "已完成", + "edge": "邊緣", + "versionUnknown": " 版本未知" + }, + "sdxl": { + "steps": "步數", + "loading": "載入中…", + "refiner": "精煉器" + }, + "gallery": { + "copy": "複製", + "download": "下載", + "loading": "載入中" + }, + "ui": { + "tabs": { + "models": "模型", + "queueTab": "$t(ui.tabs.queue) $t(common.tab)", + "queue": "佇列" + } + }, + "models": { + "loading": "載入中" + }, + "workflows": { + "name": "名稱" } } From ff01ceae996713dae371ab322db8a32854f0cf34 Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Tue, 4 Jun 2024 23:58:27 +1000 Subject: [PATCH 060/110] Update invokeai_version.py --- invokeai/version/invokeai_version.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/invokeai/version/invokeai_version.py b/invokeai/version/invokeai_version.py index 6e997e12f5..9b575128e6 100644 --- a/invokeai/version/invokeai_version.py +++ b/invokeai/version/invokeai_version.py @@ -1 +1 @@ -__version__ = "4.2.3" +__version__ = "4.2.4" From 52aac954c097bad45553a50c286b21f2f1566d6f Mon Sep 17 00:00:00 2001 From: jstnlowe Date: Tue, 4 Jun 2024 19:10:04 -0400 Subject: [PATCH 061/110] Prefixed JSON filenames with the image UUID #6469 --- .../gallery/components/ImageMetadataViewer/DataViewer.tsx | 3 ++- .../components/ImageMetadataViewer/ImageMetadataViewer.tsx | 4 ++-- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/DataViewer.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/DataViewer.tsx index 2cbf93b899..2a0b8bed9f 100644 --- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/DataViewer.tsx +++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/DataViewer.tsx @@ -32,8 +32,9 @@ const DataViewer = (props: Props) => { const handleDownload = useCallback(() => { const blob = new Blob([dataString]); const a = document.createElement('a'); + const imageName = fileName ? fileName.replace('.png', '') : null; a.href = URL.createObjectURL(blob); - a.download = `${fileName || label}.json`; + a.download = imageName ? `${ imageName }_${ label }.json` : `${ label }.json`; document.body.appendChild(a); a.click(); a.remove(); diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataViewer.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataViewer.tsx index 46121f9724..0eda298bb9 100644 --- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataViewer.tsx +++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataViewer.tsx @@ -68,14 +68,14 @@ const ImageMetadataViewer = ({ image }: ImageMetadataViewerProps) => { {metadata ? ( - + ) : ( )} {image ? ( - + ) : ( )} From b2e005f6b5200d061fcfdd37a2f960f1f33f700b Mon Sep 17 00:00:00 2001 From: jstnlowe Date: Tue, 4 Jun 2024 19:27:37 -0400 Subject: [PATCH 062/110] Just realized we might want the same change made for the Graph JSON --- .../ImageMetadataViewer/ImageMetadataGraphTabContent.tsx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataGraphTabContent.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataGraphTabContent.tsx index 9f7cac4a3e..01674fa293 100644 --- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataGraphTabContent.tsx +++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataGraphTabContent.tsx @@ -28,7 +28,7 @@ const ImageMetadataGraphTabContent = ({ image }: Props) => { return ; } - return ; + return ; }; export default memo(ImageMetadataGraphTabContent); From 37b1f21bcf1a2651002e303f2d10d28af5b54041 Mon Sep 17 00:00:00 2001 From: jstnlowe Date: Tue, 4 Jun 2024 19:29:47 -0400 Subject: [PATCH 063/110] ... and the workflow --- .../ImageMetadataViewer/ImageMetadataWorkflowTabContent.tsx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataWorkflowTabContent.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataWorkflowTabContent.tsx index fe4ce3e701..a15f66321f 100644 --- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataWorkflowTabContent.tsx +++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataWorkflowTabContent.tsx @@ -28,7 +28,7 @@ const ImageMetadataWorkflowTabContent = ({ image }: Props) => { return ; } - return ; + return ; }; export default memo(ImageMetadataWorkflowTabContent); From 9cba0dfac98e97a6ae3874ed14817610750a6b81 Mon Sep 17 00:00:00 2001 From: jstnlowe Date: Tue, 4 Jun 2024 20:41:18 -0400 Subject: [PATCH 064/110] Providing fileName string directly to DataViewer as suggested --- .../gallery/components/ImageMetadataViewer/DataViewer.tsx | 3 +-- .../ImageMetadataViewer/ImageMetadataGraphTabContent.tsx | 2 +- .../components/ImageMetadataViewer/ImageMetadataViewer.tsx | 4 ++-- .../ImageMetadataViewer/ImageMetadataWorkflowTabContent.tsx | 2 +- 4 files changed, 5 insertions(+), 6 deletions(-) diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/DataViewer.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/DataViewer.tsx index 2a0b8bed9f..24808efa49 100644 --- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/DataViewer.tsx +++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/DataViewer.tsx @@ -32,9 +32,8 @@ const DataViewer = (props: Props) => { const handleDownload = useCallback(() => { const blob = new Blob([dataString]); const a = document.createElement('a'); - const imageName = fileName ? fileName.replace('.png', '') : null; a.href = URL.createObjectURL(blob); - a.download = imageName ? `${ imageName }_${ label }.json` : `${ label }.json`; + a.download = `${ fileName || label }.json`; document.body.appendChild(a); a.click(); a.remove(); diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataGraphTabContent.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataGraphTabContent.tsx index 01674fa293..d9353edbef 100644 --- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataGraphTabContent.tsx +++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataGraphTabContent.tsx @@ -28,7 +28,7 @@ const ImageMetadataGraphTabContent = ({ image }: Props) => { return ; } - return ; + return ; }; export default memo(ImageMetadataGraphTabContent); diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataViewer.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataViewer.tsx index 0eda298bb9..a2a36357f3 100644 --- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataViewer.tsx +++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataViewer.tsx @@ -68,14 +68,14 @@ const ImageMetadataViewer = ({ image }: ImageMetadataViewerProps) => { {metadata ? ( - + ) : ( )} {image ? ( - + ) : ( )} diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataWorkflowTabContent.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataWorkflowTabContent.tsx index a15f66321f..e549d95f29 100644 --- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataWorkflowTabContent.tsx +++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataWorkflowTabContent.tsx @@ -28,7 +28,7 @@ const ImageMetadataWorkflowTabContent = ({ image }: Props) => { return ; } - return ; + return ; }; export default memo(ImageMetadataWorkflowTabContent); From 848ca79da80ddc46861d391c32907c35c4822e40 Mon Sep 17 00:00:00 2001 From: jstnlowe Date: Tue, 4 Jun 2024 21:13:09 -0400 Subject: [PATCH 065/110] Changed translated labels to static suffixes, cleanup. --- .../components/ImageMetadataViewer/DataViewer.tsx | 2 +- .../ImageMetadataGraphTabContent.tsx | 4 +++- .../ImageMetadataViewer/ImageMetadataViewer.tsx | 12 ++++++++++-- .../ImageMetadataWorkflowTabContent.tsx | 8 +++++++- 4 files changed, 21 insertions(+), 5 deletions(-) diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/DataViewer.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/DataViewer.tsx index 24808efa49..2cbf93b899 100644 --- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/DataViewer.tsx +++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/DataViewer.tsx @@ -33,7 +33,7 @@ const DataViewer = (props: Props) => { const blob = new Blob([dataString]); const a = document.createElement('a'); a.href = URL.createObjectURL(blob); - a.download = `${ fileName || label }.json`; + a.download = `${fileName || label}.json`; document.body.appendChild(a); a.click(); a.remove(); diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataGraphTabContent.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataGraphTabContent.tsx index d9353edbef..b5b81d1e6f 100644 --- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataGraphTabContent.tsx +++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataGraphTabContent.tsx @@ -28,7 +28,9 @@ const ImageMetadataGraphTabContent = ({ image }: Props) => { return ; } - return ; + return ( + + ); }; export default memo(ImageMetadataGraphTabContent); diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataViewer.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataViewer.tsx index a2a36357f3..aa50498848 100644 --- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataViewer.tsx +++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataViewer.tsx @@ -68,14 +68,22 @@ const ImageMetadataViewer = ({ image }: ImageMetadataViewerProps) => { {metadata ? ( - + ) : ( )} {image ? ( - + ) : ( )} diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataWorkflowTabContent.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataWorkflowTabContent.tsx index e549d95f29..9c224d6190 100644 --- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataWorkflowTabContent.tsx +++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataWorkflowTabContent.tsx @@ -28,7 +28,13 @@ const ImageMetadataWorkflowTabContent = ({ image }: Props) => { return ; } - return ; + return ( + + ); }; export default memo(ImageMetadataWorkflowTabContent); From 311e44ad191848df6d5991e84d0e00165b2e5df8 Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Tue, 4 Jun 2024 17:39:47 +1000 Subject: [PATCH 066/110] tidy(ui): clean up control layers renderers, docstrings --- .../components/StageComponent.tsx | 3 +- .../controlLayers/util/getLayerBlobs.ts | 3 +- .../features/controlLayers/util/renderers.ts | 466 +++++++++++------- 3 files changed, 282 insertions(+), 190 deletions(-) diff --git a/invokeai/frontend/web/src/features/controlLayers/components/StageComponent.tsx b/invokeai/frontend/web/src/features/controlLayers/components/StageComponent.tsx index 08956e73dc..f7588746c2 100644 --- a/invokeai/frontend/web/src/features/controlLayers/components/StageComponent.tsx +++ b/invokeai/frontend/web/src/features/controlLayers/components/StageComponent.tsx @@ -18,6 +18,7 @@ import { debouncedRenderers, renderers as normalRenderers } from 'features/contr import Konva from 'konva'; import type { IRect } from 'konva/lib/types'; import { memo, useCallback, useLayoutEffect, useMemo, useState } from 'react'; +import { getImageDTO } from 'services/api/endpoints/images'; import { useDevicePixelRatio } from 'use-device-pixel-ratio'; import { v4 as uuidv4 } from 'uuid'; @@ -160,7 +161,7 @@ const useStageRenderer = ( useLayoutEffect(() => { log.trace('Rendering layers'); - renderers.renderLayers(stage, state.layers, state.globalMaskLayerOpacity, tool, onLayerPosChanged); + renderers.renderLayers(stage, state.layers, state.globalMaskLayerOpacity, tool, getImageDTO, onLayerPosChanged); }, [ stage, state.layers, diff --git a/invokeai/frontend/web/src/features/controlLayers/util/getLayerBlobs.ts b/invokeai/frontend/web/src/features/controlLayers/util/getLayerBlobs.ts index 2ad3e0c90c..9e5fbfc258 100644 --- a/invokeai/frontend/web/src/features/controlLayers/util/getLayerBlobs.ts +++ b/invokeai/frontend/web/src/features/controlLayers/util/getLayerBlobs.ts @@ -4,6 +4,7 @@ import { blobToDataURL } from 'features/canvas/util/blobToDataURL'; import { isRegionalGuidanceLayer, RG_LAYER_NAME } from 'features/controlLayers/store/controlLayersSlice'; import { renderers } from 'features/controlLayers/util/renderers'; import Konva from 'konva'; +import { getImageDTO } from 'services/api/endpoints/images'; import { assert } from 'tsafe'; /** @@ -22,7 +23,7 @@ export const getRegionalPromptLayerBlobs = async ( const reduxLayers = layers.filter(isRegionalGuidanceLayer); const container = document.createElement('div'); const stage = new Konva.Stage({ container, width, height }); - renderers.renderLayers(stage, reduxLayers, 1, 'brush'); + renderers.renderLayers(stage, reduxLayers, 1, 'brush', getImageDTO); const konvaLayers = stage.find(`.${RG_LAYER_NAME}`); const blobs: Record = {}; diff --git a/invokeai/frontend/web/src/features/controlLayers/util/renderers.ts b/invokeai/frontend/web/src/features/controlLayers/util/renderers.ts index 79933e6b00..eb1b6afb22 100644 --- a/invokeai/frontend/web/src/features/controlLayers/util/renderers.ts +++ b/invokeai/frontend/web/src/features/controlLayers/util/renderers.ts @@ -1,4 +1,3 @@ -import { getStore } from 'app/store/nanostores/store'; import { rgbaColorToString, rgbColorToString } from 'features/canvas/util/colorToString'; import { getScaledFlooredCursorPosition, snapPosToStage } from 'features/controlLayers/hooks/mouseEventHooks'; import { @@ -46,7 +45,7 @@ import Konva from 'konva'; import type { IRect, Vector2d } from 'konva/lib/types'; import { debounce } from 'lodash-es'; import type { RgbColor } from 'react-colorful'; -import { imagesApi } from 'services/api/endpoints/images'; +import type { ImageDTO } from 'services/api/types'; import { assert } from 'tsafe'; import { v4 as uuidv4 } from 'uuid'; @@ -57,26 +56,31 @@ const BRUSH_BORDER_OUTER_COLOR = 'rgba(255,255,255,0.8)'; export const STAGE_BG_DATAURL = 'data:image/png;base64,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'; -const mapId = (object: { id: string }) => object.id; +const mapId = (object: { id: string }): string => object.id; -const selectRenderableLayers = (n: Konva.Node) => +/** + * Konva selection callback to select all renderable layers. This includes RG, CA and II layers. + */ +const selectRenderableLayers = (n: Konva.Node): boolean => n.name() === RG_LAYER_NAME || n.name() === CA_LAYER_NAME || n.name() === INITIAL_IMAGE_LAYER_NAME; -const selectVectorMaskObjects = (node: Konva.Node) => { +/** + * Konva selection callback to select RG mask objects. This includes lines and rects. + */ +const selectVectorMaskObjects = (node: Konva.Node): boolean => { return node.name() === RG_LAYER_LINE_NAME || node.name() === RG_LAYER_RECT_NAME; }; /** - * Creates the brush preview layer. - * @param stage The konva stage to render on. - * @returns The brush preview layer. + * Creates the singleton tool preview layer and all its objects. + * @param stage The konva stage */ -const createToolPreviewLayer = (stage: Konva.Stage) => { +const createToolPreviewLayer = (stage: Konva.Stage): Konva.Layer => { // Initialize the brush preview layer & add to the stage const toolPreviewLayer = new Konva.Layer({ id: TOOL_PREVIEW_LAYER_ID, visible: false, listening: false }); stage.add(toolPreviewLayer); - // Add handlers to show/hide the brush preview layer + // Add handlers to show/hide the tool preview layer as the mouse enters/leaves the stage stage.on('mousemove', (e) => { const tool = $tool.get(); e.target @@ -121,7 +125,7 @@ const createToolPreviewLayer = (stage: Konva.Stage) => { brushPreviewGroup.add(brushPreviewBorderOuter); toolPreviewLayer.add(brushPreviewGroup); - // Create the rect preview + // Create the rect preview - this is a rectangle drawn from the last mouse down position to the current cursor position const rectPreview = new Konva.Rect({ id: TOOL_PREVIEW_RECT_ID, listening: false, stroke: 'white', strokeWidth: 1 }); toolPreviewLayer.add(rectPreview); @@ -130,12 +134,14 @@ const createToolPreviewLayer = (stage: Konva.Stage) => { /** * Renders the brush preview for the selected tool. - * @param stage The konva stage to render on. - * @param tool The selected tool. - * @param color The selected layer's color. - * @param cursorPos The cursor position. - * @param lastMouseDownPos The position of the last mouse down event - used for the rect tool. - * @param brushSize The brush size. + * @param stage The konva stage + * @param tool The selected tool + * @param color The selected layer's color + * @param selectedLayerType The selected layer's type + * @param globalMaskLayerOpacity The global mask layer opacity + * @param cursorPos The cursor position + * @param lastMouseDownPos The position of the last mouse down event - used for the rect tool + * @param brushSize The brush size */ const renderToolPreview = ( stage: Konva.Stage, @@ -146,7 +152,7 @@ const renderToolPreview = ( cursorPos: Vector2d | null, lastMouseDownPos: Vector2d | null, brushSize: number -) => { +): void => { const layerCount = stage.find(selectRenderableLayers).length; // Update the stage's pointer style if (layerCount === 0) { @@ -162,7 +168,7 @@ const renderToolPreview = ( // Move rect gets a crosshair stage.container().style.cursor = 'crosshair'; } else { - // Else we use the brush preview + // Else we hide the native cursor and use the konva-rendered brush preview stage.container().style.cursor = 'none'; } @@ -227,28 +233,29 @@ const renderToolPreview = ( }; /** - * Creates a vector mask layer. - * @param stage The konva stage to attach the layer to. - * @param reduxLayer The redux layer to create the konva layer from. - * @param onLayerPosChanged Callback for when the layer's position changes. + * Creates a regional guidance layer. + * @param stage The konva stage + * @param layerState The regional guidance layer state + * @param onLayerPosChanged Callback for when the layer's position changes */ -const createRegionalGuidanceLayer = ( +const createRGLayer = ( stage: Konva.Stage, - reduxLayer: RegionalGuidanceLayer, + layerState: RegionalGuidanceLayer, onLayerPosChanged?: (layerId: string, x: number, y: number) => void -) => { +): Konva.Layer => { // This layer hasn't been added to the konva state yet const konvaLayer = new Konva.Layer({ - id: reduxLayer.id, + id: layerState.id, name: RG_LAYER_NAME, draggable: true, dragDistance: 0, }); - // Create a `dragmove` listener for this layer + // When a drag on the layer finishes, update the layer's position in state. During the drag, konva handles changing + // the position - we do not need to call this on the `dragmove` event. if (onLayerPosChanged) { konvaLayer.on('dragend', function (e) { - onLayerPosChanged(reduxLayer.id, Math.floor(e.target.x()), Math.floor(e.target.y())); + onLayerPosChanged(layerState.id, Math.floor(e.target.x()), Math.floor(e.target.y())); }); } @@ -258,7 +265,7 @@ const createRegionalGuidanceLayer = ( if (!cursorPos) { return this.getAbsolutePosition(); } - // Prevent the user from dragging the layer out of the stage bounds. + // Prevent the user from dragging the layer out of the stage bounds by constaining the cursor position to the stage bounds if ( cursorPos.x < 0 || cursorPos.x > stage.width() / stage.scaleX() || @@ -272,7 +279,7 @@ const createRegionalGuidanceLayer = ( // The object group holds all of the layer's objects (e.g. lines and rects) const konvaObjectGroup = new Konva.Group({ - id: getRGLayerObjectGroupId(reduxLayer.id, uuidv4()), + id: getRGLayerObjectGroupId(layerState.id, uuidv4()), name: RG_LAYER_OBJECT_GROUP_NAME, listening: false, }); @@ -284,47 +291,51 @@ const createRegionalGuidanceLayer = ( }; /** - * Creates a konva line from a redux vector mask line. - * @param reduxObject The redux object to create the konva line from. - * @param konvaGroup The konva group to add the line to. + * Creates a konva line from a vector mask line. + * @param vectorMaskLine The vector mask line state + * @param layerObjectGroup The konva layer's object group to add the line to */ -const createVectorMaskLine = (reduxObject: VectorMaskLine, konvaGroup: Konva.Group): Konva.Line => { - const vectorMaskLine = new Konva.Line({ - id: reduxObject.id, - key: reduxObject.id, +const createVectorMaskLine = (vectorMaskLine: VectorMaskLine, layerObjectGroup: Konva.Group): Konva.Line => { + const konvaLine = new Konva.Line({ + id: vectorMaskLine.id, + key: vectorMaskLine.id, name: RG_LAYER_LINE_NAME, - strokeWidth: reduxObject.strokeWidth, + strokeWidth: vectorMaskLine.strokeWidth, tension: 0, lineCap: 'round', lineJoin: 'round', shadowForStrokeEnabled: false, - globalCompositeOperation: reduxObject.tool === 'brush' ? 'source-over' : 'destination-out', + globalCompositeOperation: vectorMaskLine.tool === 'brush' ? 'source-over' : 'destination-out', listening: false, }); - konvaGroup.add(vectorMaskLine); - return vectorMaskLine; + layerObjectGroup.add(konvaLine); + return konvaLine; }; /** - * Creates a konva rect from a redux vector mask rect. - * @param reduxObject The redux object to create the konva rect from. - * @param konvaGroup The konva group to add the rect to. + * Creates a konva rect from a vector mask rect. + * @param vectorMaskRect The vector mask rect state + * @param layerObjectGroup The konva layer's object group to add the line to */ -const createVectorMaskRect = (reduxObject: VectorMaskRect, konvaGroup: Konva.Group): Konva.Rect => { - const vectorMaskRect = new Konva.Rect({ - id: reduxObject.id, - key: reduxObject.id, +const createVectorMaskRect = (vectorMaskRect: VectorMaskRect, layerObjectGroup: Konva.Group): Konva.Rect => { + const konvaRect = new Konva.Rect({ + id: vectorMaskRect.id, + key: vectorMaskRect.id, name: RG_LAYER_RECT_NAME, - x: reduxObject.x, - y: reduxObject.y, - width: reduxObject.width, - height: reduxObject.height, + x: vectorMaskRect.x, + y: vectorMaskRect.y, + width: vectorMaskRect.width, + height: vectorMaskRect.height, listening: false, }); - konvaGroup.add(vectorMaskRect); - return vectorMaskRect; + layerObjectGroup.add(konvaRect); + return konvaRect; }; +/** + * Creates the "compositing rect" for a layer. + * @param konvaLayer The konva layer + */ const createCompositingRect = (konvaLayer: Konva.Layer): Konva.Rect => { const compositingRect = new Konva.Rect({ name: COMPOSITING_RECT_NAME, listening: false }); konvaLayer.add(compositingRect); @@ -332,41 +343,41 @@ const createCompositingRect = (konvaLayer: Konva.Layer): Konva.Rect => { }; /** - * Renders a vector mask layer. - * @param stage The konva stage to render on. - * @param reduxLayer The redux vector mask layer to render. - * @param reduxLayerIndex The index of the layer in the redux store. - * @param globalMaskLayerOpacity The opacity of the global mask layer. - * @param tool The current tool. + * Renders a regional guidance layer. + * @param stage The konva stage + * @param layerState The regional guidance layer state + * @param globalMaskLayerOpacity The global mask layer opacity + * @param tool The current tool + * @param onLayerPosChanged Callback for when the layer's position changes */ -const renderRegionalGuidanceLayer = ( +const renderRGLayer = ( stage: Konva.Stage, - reduxLayer: RegionalGuidanceLayer, + layerState: RegionalGuidanceLayer, globalMaskLayerOpacity: number, tool: Tool, onLayerPosChanged?: (layerId: string, x: number, y: number) => void ): void => { const konvaLayer = - stage.findOne(`#${reduxLayer.id}`) ?? - createRegionalGuidanceLayer(stage, reduxLayer, onLayerPosChanged); + stage.findOne(`#${layerState.id}`) ?? createRGLayer(stage, layerState, onLayerPosChanged); // Update the layer's position and listening state konvaLayer.setAttrs({ listening: tool === 'move', // The layer only listens when using the move tool - otherwise the stage is handling mouse events - x: Math.floor(reduxLayer.x), - y: Math.floor(reduxLayer.y), + x: Math.floor(layerState.x), + y: Math.floor(layerState.y), }); // Convert the color to a string, stripping the alpha - the object group will handle opacity. - const rgbColor = rgbColorToString(reduxLayer.previewColor); + const rgbColor = rgbColorToString(layerState.previewColor); const konvaObjectGroup = konvaLayer.findOne(`.${RG_LAYER_OBJECT_GROUP_NAME}`); - assert(konvaObjectGroup, `Object group not found for layer ${reduxLayer.id}`); + assert(konvaObjectGroup, `Object group not found for layer ${layerState.id}`); // We use caching to handle "global" layer opacity, but caching is expensive and we should only do it when required. let groupNeedsCache = false; - const objectIds = reduxLayer.maskObjects.map(mapId); + const objectIds = layerState.maskObjects.map(mapId); + // Destroy any objects that are no longer in the redux state for (const objectNode of konvaObjectGroup.find(selectVectorMaskObjects)) { if (!objectIds.includes(objectNode.id())) { objectNode.destroy(); @@ -374,15 +385,15 @@ const renderRegionalGuidanceLayer = ( } } - for (const reduxObject of reduxLayer.maskObjects) { - if (reduxObject.type === 'vector_mask_line') { + for (const maskObject of layerState.maskObjects) { + if (maskObject.type === 'vector_mask_line') { const vectorMaskLine = - stage.findOne(`#${reduxObject.id}`) ?? createVectorMaskLine(reduxObject, konvaObjectGroup); + stage.findOne(`#${maskObject.id}`) ?? createVectorMaskLine(maskObject, konvaObjectGroup); // Only update the points if they have changed. The point values are never mutated, they are only added to the // array, so checking the length is sufficient to determine if we need to re-cache. - if (vectorMaskLine.points().length !== reduxObject.points.length) { - vectorMaskLine.points(reduxObject.points); + if (vectorMaskLine.points().length !== maskObject.points.length) { + vectorMaskLine.points(maskObject.points); groupNeedsCache = true; } // Only update the color if it has changed. @@ -390,9 +401,9 @@ const renderRegionalGuidanceLayer = ( vectorMaskLine.stroke(rgbColor); groupNeedsCache = true; } - } else if (reduxObject.type === 'vector_mask_rect') { + } else if (maskObject.type === 'vector_mask_rect') { const konvaObject = - stage.findOne(`#${reduxObject.id}`) ?? createVectorMaskRect(reduxObject, konvaObjectGroup); + stage.findOne(`#${maskObject.id}`) ?? createVectorMaskRect(maskObject, konvaObjectGroup); // Only update the color if it has changed. if (konvaObject.fill() !== rgbColor) { @@ -403,8 +414,8 @@ const renderRegionalGuidanceLayer = ( } // Only update layer visibility if it has changed. - if (konvaLayer.visible() !== reduxLayer.isEnabled) { - konvaLayer.visible(reduxLayer.isEnabled); + if (konvaLayer.visible() !== layerState.isEnabled) { + konvaLayer.visible(layerState.isEnabled); groupNeedsCache = true; } @@ -428,7 +439,7 @@ const renderRegionalGuidanceLayer = ( * Instead, with the special handling, the effect is as if you drew all the shapes at 100% opacity, flattened them to * a single raster image, and _then_ applied the 50% opacity. */ - if (reduxLayer.isSelected && tool !== 'move') { + if (layerState.isSelected && tool !== 'move') { // We must clear the cache first so Konva will re-draw the group with the new compositing rect if (konvaObjectGroup.isCached()) { konvaObjectGroup.clearCache(); @@ -438,7 +449,7 @@ const renderRegionalGuidanceLayer = ( compositingRect.setAttrs({ // The rect should be the size of the layer - use the fast method if we don't have a pixel-perfect bbox already - ...(!reduxLayer.bboxNeedsUpdate && reduxLayer.bbox ? reduxLayer.bbox : getLayerBboxFast(konvaLayer)), + ...(!layerState.bboxNeedsUpdate && layerState.bbox ? layerState.bbox : getLayerBboxFast(konvaLayer)), fill: rgbColor, opacity: globalMaskLayerOpacity, // Draw this rect only where there are non-transparent pixels under it (e.g. the mask shapes) @@ -459,9 +470,14 @@ const renderRegionalGuidanceLayer = ( } }; -const createInitialImageLayer = (stage: Konva.Stage, reduxLayer: InitialImageLayer): Konva.Layer => { +/** + * Creates an initial image konva layer. + * @param stage The konva stage + * @param layerState The initial image layer state + */ +const createIILayer = (stage: Konva.Stage, layerState: InitialImageLayer): Konva.Layer => { const konvaLayer = new Konva.Layer({ - id: reduxLayer.id, + id: layerState.id, name: INITIAL_IMAGE_LAYER_NAME, imageSmoothingEnabled: true, listening: false, @@ -470,20 +486,27 @@ const createInitialImageLayer = (stage: Konva.Stage, reduxLayer: InitialImageLay return konvaLayer; }; -const createInitialImageLayerImage = (konvaLayer: Konva.Layer, image: HTMLImageElement): Konva.Image => { +/** + * Creates the konva image for an initial image layer. + * @param konvaLayer The konva layer + * @param imageEl The image element + */ +const createIILayerImage = (konvaLayer: Konva.Layer, imageEl: HTMLImageElement): Konva.Image => { const konvaImage = new Konva.Image({ name: INITIAL_IMAGE_LAYER_IMAGE_NAME, - image, + image: imageEl, }); konvaLayer.add(konvaImage); return konvaImage; }; -const updateInitialImageLayerImageAttrs = ( - stage: Konva.Stage, - konvaImage: Konva.Image, - reduxLayer: InitialImageLayer -) => { +/** + * Updates an initial image layer's attributes (width, height, opacity, visibility). + * @param stage The konva stage + * @param konvaImage The konva image + * @param layerState The initial image layer state + */ +const updateIILayerImageAttrs = (stage: Konva.Stage, konvaImage: Konva.Image, layerState: InitialImageLayer): void => { // Konva erroneously reports NaN for width and height when the stage is hidden. This causes errors when caching, // but it doesn't seem to break anything. // TODO(psyche): Investigate and report upstream. @@ -492,46 +515,55 @@ const updateInitialImageLayerImageAttrs = ( if ( konvaImage.width() !== newWidth || konvaImage.height() !== newHeight || - konvaImage.visible() !== reduxLayer.isEnabled + konvaImage.visible() !== layerState.isEnabled ) { konvaImage.setAttrs({ - opacity: reduxLayer.opacity, + opacity: layerState.opacity, scaleX: 1, scaleY: 1, width: stage.width() / stage.scaleX(), height: stage.height() / stage.scaleY(), - visible: reduxLayer.isEnabled, + visible: layerState.isEnabled, }); } - if (konvaImage.opacity() !== reduxLayer.opacity) { - konvaImage.opacity(reduxLayer.opacity); + if (konvaImage.opacity() !== layerState.opacity) { + konvaImage.opacity(layerState.opacity); } }; -const updateInitialImageLayerImageSource = async ( +/** + * Update an initial image layer's image source when the image changes. + * @param stage The konva stage + * @param konvaLayer The konva layer + * @param layerState The initial image layer state + * @param getImageDTO A function to retrieve an image DTO from the server, used to update the image source + */ +const updateIILayerImageSource = async ( stage: Konva.Stage, konvaLayer: Konva.Layer, - reduxLayer: InitialImageLayer -) => { - if (reduxLayer.image) { - const imageName = reduxLayer.image.name; - const req = getStore().dispatch(imagesApi.endpoints.getImageDTO.initiate(imageName)); - const imageDTO = await req.unwrap(); - req.unsubscribe(); + layerState: InitialImageLayer, + getImageDTO: (imageName: string) => Promise +): Promise => { + if (layerState.image) { + const imageName = layerState.image.name; + const imageDTO = await getImageDTO(imageName); + if (!imageDTO) { + return; + } const imageEl = new Image(); - const imageId = getIILayerImageId(reduxLayer.id, imageName); + const imageId = getIILayerImageId(layerState.id, imageName); imageEl.onload = () => { // Find the existing image or create a new one - must find using the name, bc the id may have just changed const konvaImage = konvaLayer.findOne(`.${INITIAL_IMAGE_LAYER_IMAGE_NAME}`) ?? - createInitialImageLayerImage(konvaLayer, imageEl); + createIILayerImage(konvaLayer, imageEl); // Update the image's attributes konvaImage.setAttrs({ id: imageId, image: imageEl, }); - updateInitialImageLayerImageAttrs(stage, konvaImage, reduxLayer); + updateIILayerImageAttrs(stage, konvaImage, layerState); imageEl.id = imageId; }; imageEl.src = imageDTO.image_url; @@ -540,14 +572,24 @@ const updateInitialImageLayerImageSource = async ( } }; -const renderInitialImageLayer = (stage: Konva.Stage, reduxLayer: InitialImageLayer) => { - const konvaLayer = stage.findOne(`#${reduxLayer.id}`) ?? createInitialImageLayer(stage, reduxLayer); +/** + * Renders an initial image layer. + * @param stage The konva stage + * @param layerState The initial image layer state + * @param getImageDTO A function to retrieve an image DTO from the server, used to update the image source + */ +const renderIILayer = ( + stage: Konva.Stage, + layerState: InitialImageLayer, + getImageDTO: (imageName: string) => Promise +): void => { + const konvaLayer = stage.findOne(`#${layerState.id}`) ?? createIILayer(stage, layerState); const konvaImage = konvaLayer.findOne(`.${INITIAL_IMAGE_LAYER_IMAGE_NAME}`); const canvasImageSource = konvaImage?.image(); let imageSourceNeedsUpdate = false; if (canvasImageSource instanceof HTMLImageElement) { - const image = reduxLayer.image; - if (image && canvasImageSource.id !== getCALayerImageId(reduxLayer.id, image.name)) { + const image = layerState.image; + if (image && canvasImageSource.id !== getCALayerImageId(layerState.id, image.name)) { imageSourceNeedsUpdate = true; } else if (!image) { imageSourceNeedsUpdate = true; @@ -557,15 +599,20 @@ const renderInitialImageLayer = (stage: Konva.Stage, reduxLayer: InitialImageLay } if (imageSourceNeedsUpdate) { - updateInitialImageLayerImageSource(stage, konvaLayer, reduxLayer); + updateIILayerImageSource(stage, konvaLayer, layerState, getImageDTO); } else if (konvaImage) { - updateInitialImageLayerImageAttrs(stage, konvaImage, reduxLayer); + updateIILayerImageAttrs(stage, konvaImage, layerState); } }; -const createControlNetLayer = (stage: Konva.Stage, reduxLayer: ControlAdapterLayer): Konva.Layer => { +/** + * Creates a control adapter layer. + * @param stage The konva stage + * @param layerState The control adapter layer state + */ +const createCALayer = (stage: Konva.Stage, layerState: ControlAdapterLayer): Konva.Layer => { const konvaLayer = new Konva.Layer({ - id: reduxLayer.id, + id: layerState.id, name: CA_LAYER_NAME, imageSmoothingEnabled: true, listening: false, @@ -574,39 +621,53 @@ const createControlNetLayer = (stage: Konva.Stage, reduxLayer: ControlAdapterLay return konvaLayer; }; -const createControlNetLayerImage = (konvaLayer: Konva.Layer, image: HTMLImageElement): Konva.Image => { +/** + * Creates a control adapter layer image. + * @param konvaLayer The konva layer + * @param imageEl The image element + */ +const createCALayerImage = (konvaLayer: Konva.Layer, imageEl: HTMLImageElement): Konva.Image => { const konvaImage = new Konva.Image({ name: CA_LAYER_IMAGE_NAME, - image, + image: imageEl, }); konvaLayer.add(konvaImage); return konvaImage; }; -const updateControlNetLayerImageSource = async ( +/** + * Updates the image source for a control adapter layer. This includes loading the image from the server and updating the konva image. + * @param stage The konva stage + * @param konvaLayer The konva layer + * @param layerState The control adapter layer state + * @param getImageDTO A function to retrieve an image DTO from the server, used to update the image source + */ +const updateCALayerImageSource = async ( stage: Konva.Stage, konvaLayer: Konva.Layer, - reduxLayer: ControlAdapterLayer -) => { - const image = reduxLayer.controlAdapter.processedImage ?? reduxLayer.controlAdapter.image; + layerState: ControlAdapterLayer, + getImageDTO: (imageName: string) => Promise +): Promise => { + const image = layerState.controlAdapter.processedImage ?? layerState.controlAdapter.image; if (image) { const imageName = image.name; - const req = getStore().dispatch(imagesApi.endpoints.getImageDTO.initiate(imageName)); - const imageDTO = await req.unwrap(); - req.unsubscribe(); + const imageDTO = await getImageDTO(imageName); + if (!imageDTO) { + return; + } const imageEl = new Image(); - const imageId = getCALayerImageId(reduxLayer.id, imageName); + const imageId = getCALayerImageId(layerState.id, imageName); imageEl.onload = () => { // Find the existing image or create a new one - must find using the name, bc the id may have just changed const konvaImage = - konvaLayer.findOne(`.${CA_LAYER_IMAGE_NAME}`) ?? createControlNetLayerImage(konvaLayer, imageEl); + konvaLayer.findOne(`.${CA_LAYER_IMAGE_NAME}`) ?? createCALayerImage(konvaLayer, imageEl); // Update the image's attributes konvaImage.setAttrs({ id: imageId, image: imageEl, }); - updateControlNetLayerImageAttrs(stage, konvaImage, reduxLayer); + updateCALayerImageAttrs(stage, konvaImage, layerState); // Must cache after this to apply the filters konvaImage.cache(); imageEl.id = imageId; @@ -617,11 +678,17 @@ const updateControlNetLayerImageSource = async ( } }; -const updateControlNetLayerImageAttrs = ( +/** + * Updates the image attributes for a control adapter layer's image (width, height, visibility, opacity, filters). + * @param stage The konva stage + * @param konvaImage The konva image + * @param layerState The control adapter layer state + */ +const updateCALayerImageAttrs = ( stage: Konva.Stage, konvaImage: Konva.Image, - reduxLayer: ControlAdapterLayer -) => { + layerState: ControlAdapterLayer +): void => { let needsCache = false; // Konva erroneously reports NaN for width and height when the stage is hidden. This causes errors when caching, // but it doesn't seem to break anything. @@ -632,36 +699,47 @@ const updateControlNetLayerImageAttrs = ( if ( konvaImage.width() !== newWidth || konvaImage.height() !== newHeight || - konvaImage.visible() !== reduxLayer.isEnabled || - hasFilter !== reduxLayer.isFilterEnabled + konvaImage.visible() !== layerState.isEnabled || + hasFilter !== layerState.isFilterEnabled ) { konvaImage.setAttrs({ - opacity: reduxLayer.opacity, + opacity: layerState.opacity, scaleX: 1, scaleY: 1, width: stage.width() / stage.scaleX(), height: stage.height() / stage.scaleY(), - visible: reduxLayer.isEnabled, - filters: reduxLayer.isFilterEnabled ? [LightnessToAlphaFilter] : [], + visible: layerState.isEnabled, + filters: layerState.isFilterEnabled ? [LightnessToAlphaFilter] : [], }); needsCache = true; } - if (konvaImage.opacity() !== reduxLayer.opacity) { - konvaImage.opacity(reduxLayer.opacity); + if (konvaImage.opacity() !== layerState.opacity) { + konvaImage.opacity(layerState.opacity); } if (needsCache) { konvaImage.cache(); } }; -const renderControlNetLayer = (stage: Konva.Stage, reduxLayer: ControlAdapterLayer) => { - const konvaLayer = stage.findOne(`#${reduxLayer.id}`) ?? createControlNetLayer(stage, reduxLayer); +/** + * Renders a control adapter layer. If the layer doesn't already exist, it is created. Otherwise, the layer is updated + * with the current image source and attributes. + * @param stage The konva stage + * @param layerState The control adapter layer state + * @param getImageDTO A function to retrieve an image DTO from the server, used to update the image source + */ +const renderCALayer = ( + stage: Konva.Stage, + layerState: ControlAdapterLayer, + getImageDTO: (imageName: string) => Promise +): void => { + const konvaLayer = stage.findOne(`#${layerState.id}`) ?? createCALayer(stage, layerState); const konvaImage = konvaLayer.findOne(`.${CA_LAYER_IMAGE_NAME}`); const canvasImageSource = konvaImage?.image(); let imageSourceNeedsUpdate = false; if (canvasImageSource instanceof HTMLImageElement) { - const image = reduxLayer.controlAdapter.processedImage ?? reduxLayer.controlAdapter.image; - if (image && canvasImageSource.id !== getCALayerImageId(reduxLayer.id, image.name)) { + const image = layerState.controlAdapter.processedImage ?? layerState.controlAdapter.image; + if (image && canvasImageSource.id !== getCALayerImageId(layerState.id, image.name)) { imageSourceNeedsUpdate = true; } else if (!image) { imageSourceNeedsUpdate = true; @@ -671,44 +749,46 @@ const renderControlNetLayer = (stage: Konva.Stage, reduxLayer: ControlAdapterLay } if (imageSourceNeedsUpdate) { - updateControlNetLayerImageSource(stage, konvaLayer, reduxLayer); + updateCALayerImageSource(stage, konvaLayer, layerState, getImageDTO); } else if (konvaImage) { - updateControlNetLayerImageAttrs(stage, konvaImage, reduxLayer); + updateCALayerImageAttrs(stage, konvaImage, layerState); } }; /** * Renders the layers on the stage. - * @param stage The konva stage to render on. - * @param reduxLayers Array of the layers from the redux store. - * @param layerOpacity The opacity of the layer. - * @param onLayerPosChanged Callback for when the layer's position changes. This is optional to allow for offscreen rendering. - * @returns + * @param stage The konva stage + * @param layerStates Array of all layer states + * @param globalMaskLayerOpacity The global mask layer opacity + * @param tool The current tool + * @param getImageDTO A function to retrieve an image DTO from the server, used to update the image source + * @param onLayerPosChanged Callback for when the layer's position changes */ const renderLayers = ( stage: Konva.Stage, - reduxLayers: Layer[], + layerStates: Layer[], globalMaskLayerOpacity: number, tool: Tool, + getImageDTO: (imageName: string) => Promise, onLayerPosChanged?: (layerId: string, x: number, y: number) => void -) => { - const reduxLayerIds = reduxLayers.filter(isRenderableLayer).map(mapId); +): void => { + const layerIds = layerStates.filter(isRenderableLayer).map(mapId); // Remove un-rendered layers for (const konvaLayer of stage.find(selectRenderableLayers)) { - if (!reduxLayerIds.includes(konvaLayer.id())) { + if (!layerIds.includes(konvaLayer.id())) { konvaLayer.destroy(); } } - for (const reduxLayer of reduxLayers) { - if (isRegionalGuidanceLayer(reduxLayer)) { - renderRegionalGuidanceLayer(stage, reduxLayer, globalMaskLayerOpacity, tool, onLayerPosChanged); + for (const layer of layerStates) { + if (isRegionalGuidanceLayer(layer)) { + renderRGLayer(stage, layer, globalMaskLayerOpacity, tool, onLayerPosChanged); } - if (isControlAdapterLayer(reduxLayer)) { - renderControlNetLayer(stage, reduxLayer); + if (isControlAdapterLayer(layer)) { + renderCALayer(stage, layer, getImageDTO); } - if (isInitialImageLayer(reduxLayer)) { - renderInitialImageLayer(stage, reduxLayer); + if (isInitialImageLayer(layer)) { + renderIILayer(stage, layer, getImageDTO); } // IP Adapter layers are not rendered } @@ -716,13 +796,12 @@ const renderLayers = ( /** * Creates a bounding box rect for a layer. - * @param reduxLayer The redux layer to create the bounding box for. - * @param konvaLayer The konva layer to attach the bounding box to. - * @param onBboxMouseDown Callback for when the bounding box is clicked. + * @param layerState The layer state for the layer to create the bounding box for + * @param konvaLayer The konva layer to attach the bounding box to */ -const createBboxRect = (reduxLayer: Layer, konvaLayer: Konva.Layer) => { +const createBboxRect = (layerState: Layer, konvaLayer: Konva.Layer): Konva.Rect => { const rect = new Konva.Rect({ - id: getLayerBboxId(reduxLayer.id), + id: getLayerBboxId(layerState.id), name: LAYER_BBOX_NAME, strokeWidth: 1, visible: false, @@ -733,12 +812,12 @@ const createBboxRect = (reduxLayer: Layer, konvaLayer: Konva.Layer) => { /** * Renders the bounding boxes for the layers. - * @param stage The konva stage to render on - * @param reduxLayers An array of all redux layers to draw bboxes for + * @param stage The konva stage + * @param layerStates An array of layers to draw bboxes for * @param tool The current tool * @returns */ -const renderBboxes = (stage: Konva.Stage, reduxLayers: Layer[], tool: Tool) => { +const renderBboxes = (stage: Konva.Stage, layerStates: Layer[], tool: Tool): void => { // Hide all bboxes so they don't interfere with getClientRect for (const bboxRect of stage.find(`.${LAYER_BBOX_NAME}`)) { bboxRect.visible(false); @@ -749,39 +828,39 @@ const renderBboxes = (stage: Konva.Stage, reduxLayers: Layer[], tool: Tool) => { return; } - for (const reduxLayer of reduxLayers.filter(isRegionalGuidanceLayer)) { - if (!reduxLayer.bbox) { + for (const layer of layerStates.filter(isRegionalGuidanceLayer)) { + if (!layer.bbox) { continue; } - const konvaLayer = stage.findOne(`#${reduxLayer.id}`); - assert(konvaLayer, `Layer ${reduxLayer.id} not found in stage`); + const konvaLayer = stage.findOne(`#${layer.id}`); + assert(konvaLayer, `Layer ${layer.id} not found in stage`); - const bboxRect = konvaLayer.findOne(`.${LAYER_BBOX_NAME}`) ?? createBboxRect(reduxLayer, konvaLayer); + const bboxRect = konvaLayer.findOne(`.${LAYER_BBOX_NAME}`) ?? createBboxRect(layer, konvaLayer); bboxRect.setAttrs({ - visible: !reduxLayer.bboxNeedsUpdate, - listening: reduxLayer.isSelected, - x: reduxLayer.bbox.x, - y: reduxLayer.bbox.y, - width: reduxLayer.bbox.width, - height: reduxLayer.bbox.height, - stroke: reduxLayer.isSelected ? BBOX_SELECTED_STROKE : '', + visible: !layer.bboxNeedsUpdate, + listening: layer.isSelected, + x: layer.bbox.x, + y: layer.bbox.y, + width: layer.bbox.width, + height: layer.bbox.height, + stroke: layer.isSelected ? BBOX_SELECTED_STROKE : '', }); } }; /** * Calculates the bbox of each regional guidance layer. Only calculates if the mask has changed. - * @param stage The konva stage to render on. - * @param reduxLayers An array of redux layers to calculate bboxes for + * @param stage The konva stage + * @param layerStates An array of layers to calculate bboxes for * @param onBboxChanged Callback for when the bounding box changes */ const updateBboxes = ( stage: Konva.Stage, - reduxLayers: Layer[], + layerStates: Layer[], onBboxChanged: (layerId: string, bbox: IRect | null) => void -) => { - for (const rgLayer of reduxLayers.filter(isRegionalGuidanceLayer)) { +): void => { + for (const rgLayer of layerStates.filter(isRegionalGuidanceLayer)) { const konvaLayer = stage.findOne(`#${rgLayer.id}`); assert(konvaLayer, `Layer ${rgLayer.id} not found in stage`); // We only need to recalculate the bbox if the layer has changed @@ -808,7 +887,7 @@ const updateBboxes = ( /** * Creates the background layer for the stage. - * @param stage The konva stage to render on + * @param stage The konva stage */ const createBackgroundLayer = (stage: Konva.Stage): Konva.Layer => { const layer = new Konva.Layer({ @@ -835,11 +914,11 @@ const createBackgroundLayer = (stage: Konva.Stage): Konva.Layer => { /** * Renders the background layer for the stage. - * @param stage The konva stage to render on + * @param stage The konva stage * @param width The unscaled width of the canvas * @param height The unscaled height of the canvas */ -const renderBackground = (stage: Konva.Stage, width: number, height: number) => { +const renderBackground = (stage: Konva.Stage, width: number, height: number): void => { const layer = stage.findOne(`#${BACKGROUND_LAYER_ID}`) ?? createBackgroundLayer(stage); const background = layer.findOne(`#${BACKGROUND_RECT_ID}`); @@ -880,6 +959,10 @@ const arrangeLayers = (stage: Konva.Stage, layerIds: string[]): void => { stage.findOne(`#${TOOL_PREVIEW_LAYER_ID}`)?.zIndex(nextZIndex++); }; +/** + * Creates the "no layers" fallback layer + * @param stage The konva stage + */ const createNoLayersMessageLayer = (stage: Konva.Stage): Konva.Layer => { const noLayersMessageLayer = new Konva.Layer({ id: NO_LAYERS_MESSAGE_LAYER_ID, @@ -901,7 +984,14 @@ const createNoLayersMessageLayer = (stage: Konva.Stage): Konva.Layer => { return noLayersMessageLayer; }; -const renderNoLayersMessage = (stage: Konva.Stage, layerCount: number, width: number, height: number) => { +/** + * Renders the "no layers" message when there are no layers to render + * @param stage The konva stage + * @param layerCount The current number of layers + * @param width The target width of the text + * @param height The target height of the text + */ +const renderNoLayersMessage = (stage: Konva.Stage, layerCount: number, width: number, height: number): void => { const noLayersMessageLayer = stage.findOne(`#${NO_LAYERS_MESSAGE_LAYER_ID}`) ?? createNoLayersMessageLayer(stage); if (layerCount === 0) { @@ -942,7 +1032,7 @@ export const debouncedRenderers = { * This is useful for edge maps and other masks, to make the black areas transparent. * @param imageData The image data to apply the filter to */ -const LightnessToAlphaFilter = (imageData: ImageData) => { +const LightnessToAlphaFilter = (imageData: ImageData): void => { const len = imageData.data.length / 4; for (let i = 0; i < len; i++) { const r = imageData.data[i * 4 + 0] as number; From 1823e446ac54560931d615e69fbdd5800452932c Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Tue, 4 Jun 2024 19:32:48 +1000 Subject: [PATCH 067/110] fix(ui): conditionally render CL preview This fixes an issue where it sometimes gets out of sync, and fixes some konva errors. --- .../features/controlLayers/store/controlLayersSlice.ts | 1 + .../components/ImageSize/AspectRatioCanvasPreview.tsx | 9 +++++++++ .../ImageSettingsAccordion/ImageSizeLinear.tsx | 5 +---- .../ui/components/ParametersPanelTextToImage.tsx | 3 +++ 4 files changed, 14 insertions(+), 4 deletions(-) diff --git a/invokeai/frontend/web/src/features/controlLayers/store/controlLayersSlice.ts b/invokeai/frontend/web/src/features/controlLayers/store/controlLayersSlice.ts index 5fa8cc3dfb..91ed278398 100644 --- a/invokeai/frontend/web/src/features/controlLayers/store/controlLayersSlice.ts +++ b/invokeai/frontend/web/src/features/controlLayers/store/controlLayersSlice.ts @@ -887,6 +887,7 @@ export const $isDrawing = atom(false); export const $lastMouseDownPos = atom(null); export const $tool = atom('brush'); export const $lastCursorPos = atom(null); +export const $isPreviewVisible = atom(true); // IDs for singleton Konva layers and objects export const TOOL_PREVIEW_LAYER_ID = 'tool_preview_layer'; diff --git a/invokeai/frontend/web/src/features/parameters/components/ImageSize/AspectRatioCanvasPreview.tsx b/invokeai/frontend/web/src/features/parameters/components/ImageSize/AspectRatioCanvasPreview.tsx index 00fa10c0c5..08b591f9b1 100644 --- a/invokeai/frontend/web/src/features/parameters/components/ImageSize/AspectRatioCanvasPreview.tsx +++ b/invokeai/frontend/web/src/features/parameters/components/ImageSize/AspectRatioCanvasPreview.tsx @@ -1,8 +1,17 @@ import { Flex } from '@invoke-ai/ui-library'; +import { useStore } from '@nanostores/react'; import { StageComponent } from 'features/controlLayers/components/StageComponent'; +import { $isPreviewVisible } from 'features/controlLayers/store/controlLayersSlice'; +import { AspectRatioIconPreview } from 'features/parameters/components/ImageSize/AspectRatioIconPreview'; import { memo } from 'react'; export const AspectRatioCanvasPreview = memo(() => { + const isPreviewVisible = useStore($isPreviewVisible); + + if (!isPreviewVisible) { + return ; + } + return ( diff --git a/invokeai/frontend/web/src/features/settingsAccordions/components/ImageSettingsAccordion/ImageSizeLinear.tsx b/invokeai/frontend/web/src/features/settingsAccordions/components/ImageSettingsAccordion/ImageSizeLinear.tsx index ddf4997a16..3c8f274ecb 100644 --- a/invokeai/frontend/web/src/features/settingsAccordions/components/ImageSettingsAccordion/ImageSizeLinear.tsx +++ b/invokeai/frontend/web/src/features/settingsAccordions/components/ImageSettingsAccordion/ImageSizeLinear.tsx @@ -3,15 +3,12 @@ import { aspectRatioChanged, heightChanged, widthChanged } from 'features/contro import { ParamHeight } from 'features/parameters/components/Core/ParamHeight'; import { ParamWidth } from 'features/parameters/components/Core/ParamWidth'; import { AspectRatioCanvasPreview } from 'features/parameters/components/ImageSize/AspectRatioCanvasPreview'; -import { AspectRatioIconPreview } from 'features/parameters/components/ImageSize/AspectRatioIconPreview'; import { ImageSize } from 'features/parameters/components/ImageSize/ImageSize'; import type { AspectRatioState } from 'features/parameters/components/ImageSize/types'; -import { activeTabNameSelector } from 'features/ui/store/uiSelectors'; import { memo, useCallback } from 'react'; export const ImageSizeLinear = memo(() => { const dispatch = useAppDispatch(); - const tab = useAppSelector(activeTabNameSelector); const width = useAppSelector((s) => s.controlLayers.present.size.width); const height = useAppSelector((s) => s.controlLayers.present.size.height); const aspectRatioState = useAppSelector((s) => s.controlLayers.present.size.aspectRatio); @@ -50,7 +47,7 @@ export const ImageSizeLinear = memo(() => { aspectRatioState={aspectRatioState} heightComponent={} widthComponent={} - previewComponent={tab === 'generation' ? : } + previewComponent={} onChangeAspectRatioState={onChangeAspectRatioState} onChangeWidth={onChangeWidth} onChangeHeight={onChangeHeight} diff --git a/invokeai/frontend/web/src/features/ui/components/ParametersPanelTextToImage.tsx b/invokeai/frontend/web/src/features/ui/components/ParametersPanelTextToImage.tsx index b78d5dce9a..3c58a08e4c 100644 --- a/invokeai/frontend/web/src/features/ui/components/ParametersPanelTextToImage.tsx +++ b/invokeai/frontend/web/src/features/ui/components/ParametersPanelTextToImage.tsx @@ -3,6 +3,7 @@ import { Box, Flex, Tab, TabList, TabPanel, TabPanels, Tabs } from '@invoke-ai/u import { useAppDispatch, useAppSelector } from 'app/store/storeHooks'; import { overlayScrollbarsParams } from 'common/components/OverlayScrollbars/constants'; import { ControlLayersPanelContent } from 'features/controlLayers/components/ControlLayersPanelContent'; +import { $isPreviewVisible } from 'features/controlLayers/store/controlLayersSlice'; import { isImageViewerOpenChanged } from 'features/gallery/store/gallerySlice'; import { Prompts } from 'features/parameters/components/Prompts/Prompts'; import QueueControls from 'features/queue/components/QueueControls'; @@ -53,6 +54,7 @@ const ParametersPanelTextToImage = () => { if (i === 1) { dispatch(isImageViewerOpenChanged(false)); } + $isPreviewVisible.set(i === 0); }, [dispatch] ); @@ -66,6 +68,7 @@ const ParametersPanelTextToImage = () => { {isSDXL ? : } Date: Tue, 4 Jun 2024 23:55:24 +1000 Subject: [PATCH 068/110] refactor(ui): generalize stage event handlers Create intermediary nanostores for values required by the event handlers. This allows the event handlers to be purely imperative, with no reactivity: instead of recreating/setting the handlers when a dependent piece of state changes, we use nanostores' imperative API to access dependent state. For example, some handlers depend on brush size. If we used the standard declarative `useSelector` API, we'd need to recreate the event handler callback each time the brush size changed. This can be costly. An intermediate `$brushSize` nanostore is set in a `useLayoutEffect()`, which responds to changes to the redux store. Then, in the event handler, we use the imperative API to access the brush size: `$brushSize.get()`. This change allows the event handler logic to be shared with the pending canvas v2, and also more easily tested. It's a noticeable perf improvement, too, especially when changing brush size. --- .../components/StageComponent.tsx | 101 ++++++- .../controlLayers/hooks/mouseEventHooks.ts | 233 ---------------- .../controlLayers/store/controlLayersSlice.ts | 19 +- .../src/features/controlLayers/store/types.ts | 5 + .../features/controlLayers/util/renderers.ts | 257 ++++++++++++++++-- 5 files changed, 342 insertions(+), 273 deletions(-) delete mode 100644 invokeai/frontend/web/src/features/controlLayers/hooks/mouseEventHooks.ts diff --git a/invokeai/frontend/web/src/features/controlLayers/components/StageComponent.tsx b/invokeai/frontend/web/src/features/controlLayers/components/StageComponent.tsx index f7588746c2..39204e7055 100644 --- a/invokeai/frontend/web/src/features/controlLayers/components/StageComponent.tsx +++ b/invokeai/frontend/web/src/features/controlLayers/components/StageComponent.tsx @@ -4,19 +4,38 @@ import { createSelector } from '@reduxjs/toolkit'; import { logger } from 'app/logging/logger'; import { createMemoizedSelector } from 'app/store/createMemoizedSelector'; import { useAppDispatch, useAppSelector } from 'app/store/storeHooks'; -import { useMouseEvents } from 'features/controlLayers/hooks/mouseEventHooks'; import { + $brushSize, + $brushSpacingPx, + $isDrawing, + $lastAddedPoint, $lastCursorPos, $lastMouseDownPos, + $selectedLayerId, + $selectedLayerType, + $shouldInvertBrushSizeScrollDirection, $tool, + BRUSH_SPACING_PCT, + brushSizeChanged, isRegionalGuidanceLayer, layerBboxChanged, layerTranslated, + MAX_BRUSH_SPACING_PX, + MIN_BRUSH_SPACING_PX, + rgLayerLineAdded, + rgLayerPointsAdded, + rgLayerRectAdded, selectControlLayersSlice, } from 'features/controlLayers/store/controlLayersSlice'; -import { debouncedRenderers, renderers as normalRenderers } from 'features/controlLayers/util/renderers'; +import type { AddLineArg, AddPointToLineArg, AddRectArg } from 'features/controlLayers/store/types'; +import { + debouncedRenderers, + renderers as normalRenderers, + setStageEventHandlers, +} from 'features/controlLayers/util/renderers'; import Konva from 'konva'; import type { IRect } from 'konva/lib/types'; +import { clamp } from 'lodash-es'; import { memo, useCallback, useLayoutEffect, useMemo, useState } from 'react'; import { getImageDTO } from 'services/api/endpoints/images'; import { useDevicePixelRatio } from 'use-device-pixel-ratio'; @@ -48,7 +67,6 @@ const useStageRenderer = ( const dispatch = useAppDispatch(); const state = useAppSelector((s) => s.controlLayers.present); const tool = useStore($tool); - const mouseEventHandlers = useMouseEvents(); const lastCursorPos = useStore($lastCursorPos); const lastMouseDownPos = useStore($lastMouseDownPos); const selectedLayerIdColor = useAppSelector(selectSelectedLayerColor); @@ -57,6 +75,26 @@ const useStageRenderer = ( const layerCount = useMemo(() => state.layers.length, [state.layers]); const renderers = useMemo(() => (asPreview ? debouncedRenderers : normalRenderers), [asPreview]); const dpr = useDevicePixelRatio({ round: false }); + const shouldInvertBrushSizeScrollDirection = useAppSelector((s) => s.canvas.shouldInvertBrushSizeScrollDirection); + const brushSpacingPx = useMemo( + () => clamp(state.brushSize / BRUSH_SPACING_PCT, MIN_BRUSH_SPACING_PX, MAX_BRUSH_SPACING_PX), + [state.brushSize] + ); + + useLayoutEffect(() => { + $brushSize.set(state.brushSize); + $brushSpacingPx.set(brushSpacingPx); + $selectedLayerId.set(state.selectedLayerId); + $selectedLayerType.set(selectedLayerType); + $shouldInvertBrushSizeScrollDirection.set(shouldInvertBrushSizeScrollDirection); + }, [ + brushSpacingPx, + selectedLayerIdColor, + selectedLayerType, + shouldInvertBrushSizeScrollDirection, + state.brushSize, + state.selectedLayerId, + ]); const onLayerPosChanged = useCallback( (layerId: string, x: number, y: number) => { @@ -72,6 +110,31 @@ const useStageRenderer = ( [dispatch] ); + const onRGLayerLineAdded = useCallback( + (arg: AddLineArg) => { + dispatch(rgLayerLineAdded(arg)); + }, + [dispatch] + ); + const onRGLayerPointAddedToLine = useCallback( + (arg: AddPointToLineArg) => { + dispatch(rgLayerPointsAdded(arg)); + }, + [dispatch] + ); + const onRGLayerRectAdded = useCallback( + (arg: AddRectArg) => { + dispatch(rgLayerRectAdded(arg)); + }, + [dispatch] + ); + const onBrushSizeChanged = useCallback( + (size: number) => { + dispatch(brushSizeChanged(size)); + }, + [dispatch] + ); + useLayoutEffect(() => { log.trace('Initializing stage'); if (!container) { @@ -89,21 +152,29 @@ const useStageRenderer = ( if (asPreview) { return; } - stage.on('mousedown', mouseEventHandlers.onMouseDown); - stage.on('mouseup', mouseEventHandlers.onMouseUp); - stage.on('mousemove', mouseEventHandlers.onMouseMove); - stage.on('mouseleave', mouseEventHandlers.onMouseLeave); - stage.on('wheel', mouseEventHandlers.onMouseWheel); + const cleanup = setStageEventHandlers({ + stage, + $tool, + $isDrawing, + $lastMouseDownPos, + $lastCursorPos, + $lastAddedPoint, + $brushSize, + $brushSpacingPx, + $selectedLayerId, + $selectedLayerType, + $shouldInvertBrushSizeScrollDirection, + onRGLayerLineAdded, + onRGLayerPointAddedToLine, + onRGLayerRectAdded, + onBrushSizeChanged, + }); return () => { - log.trace('Cleaning up stage listeners'); - stage.off('mousedown', mouseEventHandlers.onMouseDown); - stage.off('mouseup', mouseEventHandlers.onMouseUp); - stage.off('mousemove', mouseEventHandlers.onMouseMove); - stage.off('mouseleave', mouseEventHandlers.onMouseLeave); - stage.off('wheel', mouseEventHandlers.onMouseWheel); + log.trace('Removing stage listeners'); + cleanup(); }; - }, [stage, asPreview, mouseEventHandlers]); + }, [asPreview, onBrushSizeChanged, onRGLayerLineAdded, onRGLayerPointAddedToLine, onRGLayerRectAdded, stage]); useLayoutEffect(() => { log.trace('Updating stage dimensions'); diff --git a/invokeai/frontend/web/src/features/controlLayers/hooks/mouseEventHooks.ts b/invokeai/frontend/web/src/features/controlLayers/hooks/mouseEventHooks.ts deleted file mode 100644 index 514e8c35ff..0000000000 --- a/invokeai/frontend/web/src/features/controlLayers/hooks/mouseEventHooks.ts +++ /dev/null @@ -1,233 +0,0 @@ -import { $ctrl, $meta } from '@invoke-ai/ui-library'; -import { useStore } from '@nanostores/react'; -import { useAppDispatch, useAppSelector } from 'app/store/storeHooks'; -import { calculateNewBrushSize } from 'features/canvas/hooks/useCanvasZoom'; -import { - $isDrawing, - $lastCursorPos, - $lastMouseDownPos, - $tool, - brushSizeChanged, - rgLayerLineAdded, - rgLayerPointsAdded, - rgLayerRectAdded, -} from 'features/controlLayers/store/controlLayersSlice'; -import type Konva from 'konva'; -import type { KonvaEventObject } from 'konva/lib/Node'; -import type { Vector2d } from 'konva/lib/types'; -import { clamp } from 'lodash-es'; -import { useCallback, useMemo, useRef } from 'react'; - -const getIsFocused = (stage: Konva.Stage) => { - return stage.container().contains(document.activeElement); -}; -const getIsMouseDown = (e: KonvaEventObject) => e.evt.buttons === 1; - -const SNAP_PX = 10; - -export const snapPosToStage = (pos: Vector2d, stage: Konva.Stage) => { - const snappedPos = { ...pos }; - // Get the normalized threshold for snapping to the edge of the stage - const thresholdX = SNAP_PX / stage.scaleX(); - const thresholdY = SNAP_PX / stage.scaleY(); - const stageWidth = stage.width() / stage.scaleX(); - const stageHeight = stage.height() / stage.scaleY(); - // Snap to the edge of the stage if within threshold - if (pos.x - thresholdX < 0) { - snappedPos.x = 0; - } else if (pos.x + thresholdX > stageWidth) { - snappedPos.x = Math.floor(stageWidth); - } - if (pos.y - thresholdY < 0) { - snappedPos.y = 0; - } else if (pos.y + thresholdY > stageHeight) { - snappedPos.y = Math.floor(stageHeight); - } - return snappedPos; -}; - -export const getScaledFlooredCursorPosition = (stage: Konva.Stage) => { - const pointerPosition = stage.getPointerPosition(); - const stageTransform = stage.getAbsoluteTransform().copy(); - if (!pointerPosition) { - return; - } - const scaledCursorPosition = stageTransform.invert().point(pointerPosition); - return { - x: Math.floor(scaledCursorPosition.x), - y: Math.floor(scaledCursorPosition.y), - }; -}; - -const syncCursorPos = (stage: Konva.Stage): Vector2d | null => { - const pos = getScaledFlooredCursorPosition(stage); - if (!pos) { - return null; - } - $lastCursorPos.set(pos); - return pos; -}; - -const BRUSH_SPACING_PCT = 10; -const MIN_BRUSH_SPACING_PX = 5; -const MAX_BRUSH_SPACING_PX = 15; - -export const useMouseEvents = () => { - const dispatch = useAppDispatch(); - const selectedLayerId = useAppSelector((s) => s.controlLayers.present.selectedLayerId); - const selectedLayerType = useAppSelector((s) => { - const selectedLayer = s.controlLayers.present.layers.find((l) => l.id === s.controlLayers.present.selectedLayerId); - if (!selectedLayer) { - return null; - } - return selectedLayer.type; - }); - const tool = useStore($tool); - const lastCursorPosRef = useRef<[number, number] | null>(null); - const shouldInvertBrushSizeScrollDirection = useAppSelector((s) => s.canvas.shouldInvertBrushSizeScrollDirection); - const brushSize = useAppSelector((s) => s.controlLayers.present.brushSize); - const brushSpacingPx = useMemo( - () => clamp(brushSize / BRUSH_SPACING_PCT, MIN_BRUSH_SPACING_PX, MAX_BRUSH_SPACING_PX), - [brushSize] - ); - - const onMouseDown = useCallback( - (e: KonvaEventObject) => { - const stage = e.target.getStage(); - if (!stage) { - return; - } - const pos = syncCursorPos(stage); - if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') { - return; - } - if (tool === 'brush' || tool === 'eraser') { - dispatch( - rgLayerLineAdded({ - layerId: selectedLayerId, - points: [pos.x, pos.y, pos.x, pos.y], - tool, - }) - ); - $isDrawing.set(true); - $lastMouseDownPos.set(pos); - } else if (tool === 'rect') { - $lastMouseDownPos.set(snapPosToStage(pos, stage)); - } - }, - [dispatch, selectedLayerId, selectedLayerType, tool] - ); - - const onMouseUp = useCallback( - (e: KonvaEventObject) => { - const stage = e.target.getStage(); - if (!stage) { - return; - } - const pos = $lastCursorPos.get(); - if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') { - return; - } - const lastPos = $lastMouseDownPos.get(); - const tool = $tool.get(); - if (lastPos && selectedLayerId && tool === 'rect') { - const snappedPos = snapPosToStage(pos, stage); - dispatch( - rgLayerRectAdded({ - layerId: selectedLayerId, - rect: { - x: Math.min(snappedPos.x, lastPos.x), - y: Math.min(snappedPos.y, lastPos.y), - width: Math.abs(snappedPos.x - lastPos.x), - height: Math.abs(snappedPos.y - lastPos.y), - }, - }) - ); - } - $isDrawing.set(false); - $lastMouseDownPos.set(null); - }, - [dispatch, selectedLayerId, selectedLayerType] - ); - - const onMouseMove = useCallback( - (e: KonvaEventObject) => { - const stage = e.target.getStage(); - if (!stage) { - return; - } - const pos = syncCursorPos(stage); - if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') { - return; - } - if (getIsFocused(stage) && getIsMouseDown(e) && (tool === 'brush' || tool === 'eraser')) { - if ($isDrawing.get()) { - // Continue the last line - if (lastCursorPosRef.current) { - // Dispatching redux events impacts perf substantially - using brush spacing keeps dispatches to a reasonable number - if (Math.hypot(lastCursorPosRef.current[0] - pos.x, lastCursorPosRef.current[1] - pos.y) < brushSpacingPx) { - return; - } - } - lastCursorPosRef.current = [pos.x, pos.y]; - dispatch(rgLayerPointsAdded({ layerId: selectedLayerId, point: lastCursorPosRef.current })); - } else { - // Start a new line - dispatch(rgLayerLineAdded({ layerId: selectedLayerId, points: [pos.x, pos.y, pos.x, pos.y], tool })); - } - $isDrawing.set(true); - } - }, - [brushSpacingPx, dispatch, selectedLayerId, selectedLayerType, tool] - ); - - const onMouseLeave = useCallback( - (e: KonvaEventObject) => { - const stage = e.target.getStage(); - if (!stage) { - return; - } - const pos = syncCursorPos(stage); - $isDrawing.set(false); - $lastCursorPos.set(null); - $lastMouseDownPos.set(null); - if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') { - return; - } - if (getIsFocused(stage) && getIsMouseDown(e) && (tool === 'brush' || tool === 'eraser')) { - dispatch(rgLayerPointsAdded({ layerId: selectedLayerId, point: [pos.x, pos.y] })); - } - }, - [selectedLayerId, selectedLayerType, tool, dispatch] - ); - - const onMouseWheel = useCallback( - (e: KonvaEventObject) => { - e.evt.preventDefault(); - - if (selectedLayerType !== 'regional_guidance_layer' || (tool !== 'brush' && tool !== 'eraser')) { - return; - } - // checking for ctrl key is pressed or not, - // so that brush size can be controlled using ctrl + scroll up/down - - // Invert the delta if the property is set to true - let delta = e.evt.deltaY; - if (shouldInvertBrushSizeScrollDirection) { - delta = -delta; - } - - if ($ctrl.get() || $meta.get()) { - dispatch(brushSizeChanged(calculateNewBrushSize(brushSize, delta))); - } - }, - [selectedLayerType, tool, shouldInvertBrushSizeScrollDirection, dispatch, brushSize] - ); - - const handlers = useMemo( - () => ({ onMouseDown, onMouseUp, onMouseMove, onMouseLeave, onMouseWheel }), - [onMouseDown, onMouseUp, onMouseMove, onMouseLeave, onMouseWheel] - ); - - return handlers; -}; diff --git a/invokeai/frontend/web/src/features/controlLayers/store/controlLayersSlice.ts b/invokeai/frontend/web/src/features/controlLayers/store/controlLayersSlice.ts index 91ed278398..e298c429c9 100644 --- a/invokeai/frontend/web/src/features/controlLayers/store/controlLayersSlice.ts +++ b/invokeai/frontend/web/src/features/controlLayers/store/controlLayersSlice.ts @@ -36,6 +36,9 @@ import { assert } from 'tsafe'; import { v4 as uuidv4 } from 'uuid'; import type { + AddLineArg, + AddPointToLineArg, + AddRectArg, ControlAdapterLayer, ControlLayersState, DrawingTool, @@ -492,11 +495,11 @@ export const controlLayersSlice = createSlice({ layer.bboxNeedsUpdate = true; layer.uploadedMaskImage = null; }, - prepare: (payload: { layerId: string; points: [number, number, number, number]; tool: DrawingTool }) => ({ + prepare: (payload: AddLineArg) => ({ payload: { ...payload, lineUuid: uuidv4() }, }), }, - rgLayerPointsAdded: (state, action: PayloadAction<{ layerId: string; point: [number, number] }>) => { + rgLayerPointsAdded: (state, action: PayloadAction) => { const { layerId, point } = action.payload; const layer = selectRGLayerOrThrow(state, layerId); const lastLine = layer.maskObjects.findLast(isLine); @@ -529,7 +532,7 @@ export const controlLayersSlice = createSlice({ layer.bboxNeedsUpdate = true; layer.uploadedMaskImage = null; }, - prepare: (payload: { layerId: string; rect: IRect }) => ({ payload: { ...payload, rectUuid: uuidv4() } }), + prepare: (payload: AddRectArg) => ({ payload: { ...payload, rectUuid: uuidv4() } }), }, rgLayerMaskImageUploaded: (state, action: PayloadAction<{ layerId: string; imageDTO: ImageDTO }>) => { const { layerId, imageDTO } = action.payload; @@ -888,6 +891,16 @@ export const $lastMouseDownPos = atom(null); export const $tool = atom('brush'); export const $lastCursorPos = atom(null); export const $isPreviewVisible = atom(true); +export const $lastAddedPoint = atom(null); +export const $brushSize = atom(0); +export const $brushSpacingPx = atom(0); +export const $selectedLayerId = atom(null); +export const $selectedLayerType = atom(null); +export const $shouldInvertBrushSizeScrollDirection = atom(false); + +export const BRUSH_SPACING_PCT = 10; +export const MIN_BRUSH_SPACING_PX = 5; +export const MAX_BRUSH_SPACING_PX = 15; // IDs for singleton Konva layers and objects export const TOOL_PREVIEW_LAYER_ID = 'tool_preview_layer'; diff --git a/invokeai/frontend/web/src/features/controlLayers/store/types.ts b/invokeai/frontend/web/src/features/controlLayers/store/types.ts index 771e5060e1..bd86a8aa20 100644 --- a/invokeai/frontend/web/src/features/controlLayers/store/types.ts +++ b/invokeai/frontend/web/src/features/controlLayers/store/types.ts @@ -17,6 +17,7 @@ import { zParameterPositivePrompt, zParameterStrength, } from 'features/parameters/types/parameterSchemas'; +import type { IRect } from 'konva/lib/types'; import { z } from 'zod'; const zTool = z.enum(['brush', 'eraser', 'move', 'rect']); @@ -129,3 +130,7 @@ export type ControlLayersState = { aspectRatio: AspectRatioState; }; }; + +export type AddLineArg = { layerId: string; points: [number, number, number, number]; tool: DrawingTool }; +export type AddPointToLineArg = { layerId: string; point: [number, number] }; +export type AddRectArg = { layerId: string; rect: IRect }; diff --git a/invokeai/frontend/web/src/features/controlLayers/util/renderers.ts b/invokeai/frontend/web/src/features/controlLayers/util/renderers.ts index eb1b6afb22..592cf01826 100644 --- a/invokeai/frontend/web/src/features/controlLayers/util/renderers.ts +++ b/invokeai/frontend/web/src/features/controlLayers/util/renderers.ts @@ -1,7 +1,6 @@ +import { calculateNewBrushSize } from 'features/canvas/hooks/useCanvasZoom'; import { rgbaColorToString, rgbColorToString } from 'features/canvas/util/colorToString'; -import { getScaledFlooredCursorPosition, snapPosToStage } from 'features/controlLayers/hooks/mouseEventHooks'; import { - $tool, BACKGROUND_LAYER_ID, BACKGROUND_RECT_ID, CA_LAYER_IMAGE_NAME, @@ -31,6 +30,9 @@ import { TOOL_PREVIEW_RECT_ID, } from 'features/controlLayers/store/controlLayersSlice'; import type { + AddLineArg, + AddPointToLineArg, + AddRectArg, ControlAdapterLayer, InitialImageLayer, Layer, @@ -42,8 +44,10 @@ import type { import { getLayerBboxFast, getLayerBboxPixels } from 'features/controlLayers/util/bbox'; import { t } from 'i18next'; import Konva from 'konva'; +import type { KonvaEventObject } from 'konva/lib/Node'; import type { IRect, Vector2d } from 'konva/lib/types'; import { debounce } from 'lodash-es'; +import type { WritableAtom } from 'nanostores'; import type { RgbColor } from 'react-colorful'; import type { ImageDTO } from 'services/api/types'; import { assert } from 'tsafe'; @@ -71,6 +75,46 @@ const selectVectorMaskObjects = (node: Konva.Node): boolean => { return node.name() === RG_LAYER_LINE_NAME || node.name() === RG_LAYER_RECT_NAME; }; +const getIsFocused = (stage: Konva.Stage) => { + return stage.container().contains(document.activeElement); +}; +const getIsMouseDown = (e: KonvaEventObject) => e.evt.buttons === 1; + +const SNAP_PX = 10; + +const snapPosToStage = (pos: Vector2d, stage: Konva.Stage) => { + const snappedPos = { ...pos }; + // Get the normalized threshold for snapping to the edge of the stage + const thresholdX = SNAP_PX / stage.scaleX(); + const thresholdY = SNAP_PX / stage.scaleY(); + const stageWidth = stage.width() / stage.scaleX(); + const stageHeight = stage.height() / stage.scaleY(); + // Snap to the edge of the stage if within threshold + if (pos.x - thresholdX < 0) { + snappedPos.x = 0; + } else if (pos.x + thresholdX > stageWidth) { + snappedPos.x = Math.floor(stageWidth); + } + if (pos.y - thresholdY < 0) { + snappedPos.y = 0; + } else if (pos.y + thresholdY > stageHeight) { + snappedPos.y = Math.floor(stageHeight); + } + return snappedPos; +}; + +const getScaledFlooredCursorPosition = (stage: Konva.Stage) => { + const pointerPosition = stage.getPointerPosition(); + const stageTransform = stage.getAbsoluteTransform().copy(); + if (!pointerPosition) { + return; + } + const scaledCursorPosition = stageTransform.invert().point(pointerPosition); + return { + x: Math.floor(scaledCursorPosition.x), + y: Math.floor(scaledCursorPosition.y), + }; +}; /** * Creates the singleton tool preview layer and all its objects. * @param stage The konva stage @@ -80,25 +124,6 @@ const createToolPreviewLayer = (stage: Konva.Stage): Konva.Layer => { const toolPreviewLayer = new Konva.Layer({ id: TOOL_PREVIEW_LAYER_ID, visible: false, listening: false }); stage.add(toolPreviewLayer); - // Add handlers to show/hide the tool preview layer as the mouse enters/leaves the stage - stage.on('mousemove', (e) => { - const tool = $tool.get(); - e.target - .getStage() - ?.findOne(`#${TOOL_PREVIEW_LAYER_ID}`) - ?.visible(tool === 'brush' || tool === 'eraser'); - }); - stage.on('mouseleave', (e) => { - e.target.getStage()?.findOne(`#${TOOL_PREVIEW_LAYER_ID}`)?.visible(false); - }); - stage.on('mouseenter', (e) => { - const tool = $tool.get(); - e.target - .getStage() - ?.findOne(`#${TOOL_PREVIEW_LAYER_ID}`) - ?.visible(tool === 'brush' || tool === 'eraser'); - }); - // Create the brush preview group & circles const brushPreviewGroup = new Konva.Group({ id: TOOL_PREVIEW_BRUSH_GROUP_ID }); const brushPreviewFill = new Konva.Circle({ @@ -974,7 +999,7 @@ const createNoLayersMessageLayer = (stage: Konva.Stage): Konva.Layer => { y: 0, align: 'center', verticalAlign: 'middle', - text: t('controlLayers.noLayersAdded'), + text: t('controlLayers.noLayersAdded', 'No Layers Added'), fontFamily: '"Inter Variable", sans-serif', fontStyle: '600', fill: 'white', @@ -1005,6 +1030,194 @@ const renderNoLayersMessage = (stage: Konva.Stage, layerCount: number, width: nu } }; +type SetStageEventHandlersArg = { + stage: Konva.Stage; + $tool: WritableAtom; + $isDrawing: WritableAtom; + $lastMouseDownPos: WritableAtom; + $lastCursorPos: WritableAtom; + $lastAddedPoint: WritableAtom; + $brushSize: WritableAtom; + $brushSpacingPx: WritableAtom; + $selectedLayerId: WritableAtom; + $selectedLayerType: WritableAtom; + $shouldInvertBrushSizeScrollDirection: WritableAtom; + onRGLayerLineAdded: (arg: AddLineArg) => void; + onRGLayerPointAddedToLine: (arg: AddPointToLineArg) => void; + onRGLayerRectAdded: (arg: AddRectArg) => void; + onBrushSizeChanged: (size: number) => void; +}; + +export const setStageEventHandlers = ({ + stage, + $tool, + $isDrawing, + $lastMouseDownPos, + $lastCursorPos, + $lastAddedPoint, + $brushSize, + $brushSpacingPx, + $selectedLayerId, + $selectedLayerType, + $shouldInvertBrushSizeScrollDirection, + onRGLayerLineAdded, + onRGLayerPointAddedToLine, + onRGLayerRectAdded, + onBrushSizeChanged, +}: SetStageEventHandlersArg): (() => void) => { + const syncCursorPos = (stage: Konva.Stage) => { + const pos = getScaledFlooredCursorPosition(stage); + if (!pos) { + return null; + } + $lastCursorPos.set(pos); + return pos; + }; + + stage.on('mouseenter', (e) => { + const stage = e.target.getStage(); + if (!stage) { + return; + } + const tool = $tool.get(); + stage.findOne(`#${TOOL_PREVIEW_LAYER_ID}`)?.visible(tool === 'brush' || tool === 'eraser'); + }); + + stage.on('mousedown', (e) => { + const stage = e.target.getStage(); + if (!stage) { + return; + } + const tool = $tool.get(); + const pos = syncCursorPos(stage); + const selectedLayerId = $selectedLayerId.get(); + const selectedLayerType = $selectedLayerType.get(); + if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') { + return; + } + if (tool === 'brush' || tool === 'eraser') { + onRGLayerLineAdded({ + layerId: selectedLayerId, + points: [pos.x, pos.y, pos.x, pos.y], + tool, + }); + $isDrawing.set(true); + $lastMouseDownPos.set(pos); + } else if (tool === 'rect') { + $lastMouseDownPos.set(snapPosToStage(pos, stage)); + } + }); + + stage.on('mouseup', (e) => { + const stage = e.target.getStage(); + if (!stage) { + return; + } + const pos = $lastCursorPos.get(); + const selectedLayerId = $selectedLayerId.get(); + const selectedLayerType = $selectedLayerType.get(); + + if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') { + return; + } + const lastPos = $lastMouseDownPos.get(); + const tool = $tool.get(); + if (lastPos && selectedLayerId && tool === 'rect') { + const snappedPos = snapPosToStage(pos, stage); + onRGLayerRectAdded({ + layerId: selectedLayerId, + rect: { + x: Math.min(snappedPos.x, lastPos.x), + y: Math.min(snappedPos.y, lastPos.y), + width: Math.abs(snappedPos.x - lastPos.x), + height: Math.abs(snappedPos.y - lastPos.y), + }, + }); + } + $isDrawing.set(false); + $lastMouseDownPos.set(null); + }); + + stage.on('mousemove', (e) => { + const stage = e.target.getStage(); + if (!stage) { + return; + } + const tool = $tool.get(); + const pos = syncCursorPos(stage); + const selectedLayerId = $selectedLayerId.get(); + const selectedLayerType = $selectedLayerType.get(); + + stage.findOne(`#${TOOL_PREVIEW_LAYER_ID}`)?.visible(tool === 'brush' || tool === 'eraser'); + + if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') { + return; + } + if (getIsFocused(stage) && getIsMouseDown(e) && (tool === 'brush' || tool === 'eraser')) { + if ($isDrawing.get()) { + // Continue the last line + const lastAddedPoint = $lastAddedPoint.get(); + if (lastAddedPoint) { + // Dispatching redux events impacts perf substantially - using brush spacing keeps dispatches to a reasonable number + if (Math.hypot(lastAddedPoint.x - pos.x, lastAddedPoint.y - pos.y) < $brushSpacingPx.get()) { + return; + } + } + $lastAddedPoint.set({ x: pos.x, y: pos.y }); + onRGLayerPointAddedToLine({ layerId: selectedLayerId, point: [pos.x, pos.y] }); + } else { + // Start a new line + onRGLayerLineAdded({ layerId: selectedLayerId, points: [pos.x, pos.y, pos.x, pos.y], tool }); + } + $isDrawing.set(true); + } + }); + + stage.on('mouseleave', (e) => { + const stage = e.target.getStage(); + if (!stage) { + return; + } + const pos = syncCursorPos(stage); + $isDrawing.set(false); + $lastCursorPos.set(null); + $lastMouseDownPos.set(null); + const selectedLayerId = $selectedLayerId.get(); + const selectedLayerType = $selectedLayerType.get(); + const tool = $tool.get(); + + stage.findOne(`#${TOOL_PREVIEW_LAYER_ID}`)?.visible(false); + + if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') { + return; + } + if (getIsFocused(stage) && getIsMouseDown(e) && (tool === 'brush' || tool === 'eraser')) { + onRGLayerPointAddedToLine({ layerId: selectedLayerId, point: [pos.x, pos.y] }); + } + }); + + stage.on('wheel', (e) => { + e.evt.preventDefault(); + const selectedLayerType = $selectedLayerType.get(); + const tool = $tool.get(); + if (selectedLayerType !== 'regional_guidance_layer' || (tool !== 'brush' && tool !== 'eraser')) { + return; + } + + // Invert the delta if the property is set to true + let delta = e.evt.deltaY; + if ($shouldInvertBrushSizeScrollDirection.get()) { + delta = -delta; + } + + if (e.evt.ctrlKey || e.evt.metaKey) { + onBrushSizeChanged(calculateNewBrushSize($brushSize.get(), delta)); + } + }); + + return () => stage.off('mousedown mouseup mousemove mouseenter mouseleave wheel'); +}; + export const renderers = { renderToolPreview, renderLayers, From 1c5c3cdbd6459ef5b4034eed92c6aec59ad1a299 Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Wed, 5 Jun 2024 14:40:44 +1000 Subject: [PATCH 069/110] tidy(ui): organize control layers konva logic - More comments, docstrings - Move things into saner, less-coupled locations --- .../components/StageComponent.tsx | 11 +- .../controlLayers/{util => konva}/bbox.ts | 15 +- .../features/controlLayers/konva/constants.ts | 36 +++ .../features/controlLayers/konva/events.ts | 201 +++++++++++++ .../features/controlLayers/konva/filters.ts | 21 ++ .../features/controlLayers/konva/naming.ts | 38 +++ .../{util => konva}/renderers.ts | 279 +----------------- .../src/features/controlLayers/konva/util.ts | 67 +++++ .../controlLayers/store/controlLayersSlice.ts | 51 +--- .../controlLayers/util/getLayerBlobs.ts | 67 ----- .../ImageViewer/ImageComparisonHover.tsx | 4 +- .../ImageViewer/ImageComparisonSlider.tsx | 4 +- .../web/src/features/metadata/util/parsers.ts | 2 +- .../src/features/metadata/util/recallers.ts | 4 +- .../util/graph/generation/addControlLayers.ts | 72 ++++- 15 files changed, 481 insertions(+), 391 deletions(-) rename invokeai/frontend/web/src/features/controlLayers/{util => konva}/bbox.ts (94%) create mode 100644 invokeai/frontend/web/src/features/controlLayers/konva/constants.ts create mode 100644 invokeai/frontend/web/src/features/controlLayers/konva/events.ts create mode 100644 invokeai/frontend/web/src/features/controlLayers/konva/filters.ts create mode 100644 invokeai/frontend/web/src/features/controlLayers/konva/naming.ts rename invokeai/frontend/web/src/features/controlLayers/{util => konva}/renderers.ts (76%) create mode 100644 invokeai/frontend/web/src/features/controlLayers/konva/util.ts delete mode 100644 invokeai/frontend/web/src/features/controlLayers/util/getLayerBlobs.ts diff --git a/invokeai/frontend/web/src/features/controlLayers/components/StageComponent.tsx b/invokeai/frontend/web/src/features/controlLayers/components/StageComponent.tsx index 39204e7055..9226abf207 100644 --- a/invokeai/frontend/web/src/features/controlLayers/components/StageComponent.tsx +++ b/invokeai/frontend/web/src/features/controlLayers/components/StageComponent.tsx @@ -4,6 +4,9 @@ import { createSelector } from '@reduxjs/toolkit'; import { logger } from 'app/logging/logger'; import { createMemoizedSelector } from 'app/store/createMemoizedSelector'; import { useAppDispatch, useAppSelector } from 'app/store/storeHooks'; +import { BRUSH_SPACING_PCT, MAX_BRUSH_SPACING_PX, MIN_BRUSH_SPACING_PX } from 'features/controlLayers/konva/constants'; +import { setStageEventHandlers } from 'features/controlLayers/konva/events'; +import { debouncedRenderers, renderers as normalRenderers } from 'features/controlLayers/konva/renderers'; import { $brushSize, $brushSpacingPx, @@ -15,24 +18,16 @@ import { $selectedLayerType, $shouldInvertBrushSizeScrollDirection, $tool, - BRUSH_SPACING_PCT, brushSizeChanged, isRegionalGuidanceLayer, layerBboxChanged, layerTranslated, - MAX_BRUSH_SPACING_PX, - MIN_BRUSH_SPACING_PX, rgLayerLineAdded, rgLayerPointsAdded, rgLayerRectAdded, selectControlLayersSlice, } from 'features/controlLayers/store/controlLayersSlice'; import type { AddLineArg, AddPointToLineArg, AddRectArg } from 'features/controlLayers/store/types'; -import { - debouncedRenderers, - renderers as normalRenderers, - setStageEventHandlers, -} from 'features/controlLayers/util/renderers'; import Konva from 'konva'; import type { IRect } from 'konva/lib/types'; import { clamp } from 'lodash-es'; diff --git a/invokeai/frontend/web/src/features/controlLayers/util/bbox.ts b/invokeai/frontend/web/src/features/controlLayers/konva/bbox.ts similarity index 94% rename from invokeai/frontend/web/src/features/controlLayers/util/bbox.ts rename to invokeai/frontend/web/src/features/controlLayers/konva/bbox.ts index 3b037863c9..505998cb39 100644 --- a/invokeai/frontend/web/src/features/controlLayers/util/bbox.ts +++ b/invokeai/frontend/web/src/features/controlLayers/konva/bbox.ts @@ -1,11 +1,10 @@ import openBase64ImageInTab from 'common/util/openBase64ImageInTab'; import { imageDataToDataURL } from 'features/canvas/util/blobToDataURL'; -import { RG_LAYER_OBJECT_GROUP_NAME } from 'features/controlLayers/store/controlLayersSlice'; import Konva from 'konva'; import type { IRect } from 'konva/lib/types'; import { assert } from 'tsafe'; -const GET_CLIENT_RECT_CONFIG = { skipTransform: true }; +import { RG_LAYER_OBJECT_GROUP_NAME } from './naming'; type Extents = { minX: number; @@ -14,10 +13,13 @@ type Extents = { maxY: number; }; +const GET_CLIENT_RECT_CONFIG = { skipTransform: true }; + +//#region getImageDataBbox /** * Get the bounding box of an image. * @param imageData The ImageData object to get the bounding box of. - * @returns The minimum and maximum x and y values of the image's bounding box. + * @returns The minimum and maximum x and y values of the image's bounding box, or null if the image has no pixels. */ const getImageDataBbox = (imageData: ImageData): Extents | null => { const { data, width, height } = imageData; @@ -51,7 +53,9 @@ const getImageDataBbox = (imageData: ImageData): Extents | null => { return isEmpty ? null : { minX, minY, maxX, maxY }; }; +//#endregion +//#region getIsolatedRGLayerClone /** * Clones a regional guidance konva layer onto an offscreen stage/canvas. This allows the pixel data for a given layer * to be captured, manipulated or analyzed without interference from other layers. @@ -88,7 +92,9 @@ const getIsolatedRGLayerClone = (layer: Konva.Layer): { stageClone: Konva.Stage; return { stageClone, layerClone }; }; +//#endregion +//#region getLayerBboxPixels /** * Get the bounding box of a regional prompt konva layer. This function has special handling for regional prompt layers. * @param layer The konva layer to get the bounding box of. @@ -137,7 +143,9 @@ export const getLayerBboxPixels = (layer: Konva.Layer, preview: boolean = false) return correctedLayerBbox; }; +//#endregion +//#region getLayerBboxFast /** * Get the bounding box of a konva layer. This function is faster than `getLayerBboxPixels` but less accurate. It * should only be used when there are no eraser strokes or shapes in the layer. @@ -153,3 +161,4 @@ export const getLayerBboxFast = (layer: Konva.Layer): IRect => { height: Math.floor(bbox.height), }; }; +//#endregion diff --git a/invokeai/frontend/web/src/features/controlLayers/konva/constants.ts b/invokeai/frontend/web/src/features/controlLayers/konva/constants.ts new file mode 100644 index 0000000000..27bfc8b731 --- /dev/null +++ b/invokeai/frontend/web/src/features/controlLayers/konva/constants.ts @@ -0,0 +1,36 @@ +/** + * A transparency checker pattern image. + * This is invokeai/frontend/web/public/assets/images/transparent_bg.png as a dataURL + */ +export const TRANSPARENCY_CHECKER_PATTERN = + 'data:image/png;base64,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'; + +/** + * The color of a bounding box stroke when its object is selected. + */ +export const BBOX_SELECTED_STROKE = 'rgba(78, 190, 255, 1)'; + +/** + * The inner border color for the brush preview. + */ +export const BRUSH_BORDER_INNER_COLOR = 'rgba(0,0,0,1)'; + +/** + * The outer border color for the brush preview. + */ +export const BRUSH_BORDER_OUTER_COLOR = 'rgba(255,255,255,0.8)'; + +/** + * The target spacing of individual points of brush strokes, as a percentage of the brush size. + */ +export const BRUSH_SPACING_PCT = 10; + +/** + * The minimum brush spacing in pixels. + */ +export const MIN_BRUSH_SPACING_PX = 5; + +/** + * The maximum brush spacing in pixels. + */ +export const MAX_BRUSH_SPACING_PX = 15; diff --git a/invokeai/frontend/web/src/features/controlLayers/konva/events.ts b/invokeai/frontend/web/src/features/controlLayers/konva/events.ts new file mode 100644 index 0000000000..8b130e940f --- /dev/null +++ b/invokeai/frontend/web/src/features/controlLayers/konva/events.ts @@ -0,0 +1,201 @@ +import { calculateNewBrushSize } from 'features/canvas/hooks/useCanvasZoom'; +import { + getIsFocused, + getIsMouseDown, + getScaledFlooredCursorPosition, + snapPosToStage, +} from 'features/controlLayers/konva/util'; +import type { AddLineArg, AddPointToLineArg, AddRectArg, Layer, Tool } from 'features/controlLayers/store/types'; +import type Konva from 'konva'; +import type { Vector2d } from 'konva/lib/types'; +import type { WritableAtom } from 'nanostores'; + +import { TOOL_PREVIEW_LAYER_ID } from './naming'; + +type SetStageEventHandlersArg = { + stage: Konva.Stage; + $tool: WritableAtom; + $isDrawing: WritableAtom; + $lastMouseDownPos: WritableAtom; + $lastCursorPos: WritableAtom; + $lastAddedPoint: WritableAtom; + $brushSize: WritableAtom; + $brushSpacingPx: WritableAtom; + $selectedLayerId: WritableAtom; + $selectedLayerType: WritableAtom; + $shouldInvertBrushSizeScrollDirection: WritableAtom; + onRGLayerLineAdded: (arg: AddLineArg) => void; + onRGLayerPointAddedToLine: (arg: AddPointToLineArg) => void; + onRGLayerRectAdded: (arg: AddRectArg) => void; + onBrushSizeChanged: (size: number) => void; +}; + +const syncCursorPos = (stage: Konva.Stage, $lastCursorPos: WritableAtom) => { + const pos = getScaledFlooredCursorPosition(stage); + if (!pos) { + return null; + } + $lastCursorPos.set(pos); + return pos; +}; + +export const setStageEventHandlers = ({ + stage, + $tool, + $isDrawing, + $lastMouseDownPos, + $lastCursorPos, + $lastAddedPoint, + $brushSize, + $brushSpacingPx, + $selectedLayerId, + $selectedLayerType, + $shouldInvertBrushSizeScrollDirection, + onRGLayerLineAdded, + onRGLayerPointAddedToLine, + onRGLayerRectAdded, + onBrushSizeChanged, +}: SetStageEventHandlersArg): (() => void) => { + stage.on('mouseenter', (e) => { + const stage = e.target.getStage(); + if (!stage) { + return; + } + const tool = $tool.get(); + stage.findOne(`#${TOOL_PREVIEW_LAYER_ID}`)?.visible(tool === 'brush' || tool === 'eraser'); + }); + + stage.on('mousedown', (e) => { + const stage = e.target.getStage(); + if (!stage) { + return; + } + const tool = $tool.get(); + const pos = syncCursorPos(stage, $lastCursorPos); + const selectedLayerId = $selectedLayerId.get(); + const selectedLayerType = $selectedLayerType.get(); + if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') { + return; + } + if (tool === 'brush' || tool === 'eraser') { + onRGLayerLineAdded({ + layerId: selectedLayerId, + points: [pos.x, pos.y, pos.x, pos.y], + tool, + }); + $isDrawing.set(true); + $lastMouseDownPos.set(pos); + } else if (tool === 'rect') { + $lastMouseDownPos.set(snapPosToStage(pos, stage)); + } + }); + + stage.on('mouseup', (e) => { + const stage = e.target.getStage(); + if (!stage) { + return; + } + const pos = $lastCursorPos.get(); + const selectedLayerId = $selectedLayerId.get(); + const selectedLayerType = $selectedLayerType.get(); + + if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') { + return; + } + const lastPos = $lastMouseDownPos.get(); + const tool = $tool.get(); + if (lastPos && selectedLayerId && tool === 'rect') { + const snappedPos = snapPosToStage(pos, stage); + onRGLayerRectAdded({ + layerId: selectedLayerId, + rect: { + x: Math.min(snappedPos.x, lastPos.x), + y: Math.min(snappedPos.y, lastPos.y), + width: Math.abs(snappedPos.x - lastPos.x), + height: Math.abs(snappedPos.y - lastPos.y), + }, + }); + } + $isDrawing.set(false); + $lastMouseDownPos.set(null); + }); + + stage.on('mousemove', (e) => { + const stage = e.target.getStage(); + if (!stage) { + return; + } + const tool = $tool.get(); + const pos = syncCursorPos(stage, $lastCursorPos); + const selectedLayerId = $selectedLayerId.get(); + const selectedLayerType = $selectedLayerType.get(); + + stage.findOne(`#${TOOL_PREVIEW_LAYER_ID}`)?.visible(tool === 'brush' || tool === 'eraser'); + + if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') { + return; + } + if (getIsFocused(stage) && getIsMouseDown(e) && (tool === 'brush' || tool === 'eraser')) { + if ($isDrawing.get()) { + // Continue the last line + const lastAddedPoint = $lastAddedPoint.get(); + if (lastAddedPoint) { + // Dispatching redux events impacts perf substantially - using brush spacing keeps dispatches to a reasonable number + if (Math.hypot(lastAddedPoint.x - pos.x, lastAddedPoint.y - pos.y) < $brushSpacingPx.get()) { + return; + } + } + $lastAddedPoint.set({ x: pos.x, y: pos.y }); + onRGLayerPointAddedToLine({ layerId: selectedLayerId, point: [pos.x, pos.y] }); + } else { + // Start a new line + onRGLayerLineAdded({ layerId: selectedLayerId, points: [pos.x, pos.y, pos.x, pos.y], tool }); + } + $isDrawing.set(true); + } + }); + + stage.on('mouseleave', (e) => { + const stage = e.target.getStage(); + if (!stage) { + return; + } + const pos = syncCursorPos(stage, $lastCursorPos); + $isDrawing.set(false); + $lastCursorPos.set(null); + $lastMouseDownPos.set(null); + const selectedLayerId = $selectedLayerId.get(); + const selectedLayerType = $selectedLayerType.get(); + const tool = $tool.get(); + + stage.findOne(`#${TOOL_PREVIEW_LAYER_ID}`)?.visible(false); + + if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') { + return; + } + if (getIsFocused(stage) && getIsMouseDown(e) && (tool === 'brush' || tool === 'eraser')) { + onRGLayerPointAddedToLine({ layerId: selectedLayerId, point: [pos.x, pos.y] }); + } + }); + + stage.on('wheel', (e) => { + e.evt.preventDefault(); + const selectedLayerType = $selectedLayerType.get(); + const tool = $tool.get(); + if (selectedLayerType !== 'regional_guidance_layer' || (tool !== 'brush' && tool !== 'eraser')) { + return; + } + + // Invert the delta if the property is set to true + let delta = e.evt.deltaY; + if ($shouldInvertBrushSizeScrollDirection.get()) { + delta = -delta; + } + + if (e.evt.ctrlKey || e.evt.metaKey) { + onBrushSizeChanged(calculateNewBrushSize($brushSize.get(), delta)); + } + }); + + return () => stage.off('mousedown mouseup mousemove mouseenter mouseleave wheel'); +}; diff --git a/invokeai/frontend/web/src/features/controlLayers/konva/filters.ts b/invokeai/frontend/web/src/features/controlLayers/konva/filters.ts new file mode 100644 index 0000000000..2fcdf4ce60 --- /dev/null +++ b/invokeai/frontend/web/src/features/controlLayers/konva/filters.ts @@ -0,0 +1,21 @@ +/** + * Konva filters + * https://konvajs.org/docs/filters/Custom_Filter.html + */ + +/** + * Calculates the lightness (HSL) of a given pixel and sets the alpha channel to that value. + * This is useful for edge maps and other masks, to make the black areas transparent. + * @param imageData The image data to apply the filter to + */ +export const LightnessToAlphaFilter = (imageData: ImageData): void => { + const len = imageData.data.length / 4; + for (let i = 0; i < len; i++) { + const r = imageData.data[i * 4 + 0] as number; + const g = imageData.data[i * 4 + 1] as number; + const b = imageData.data[i * 4 + 2] as number; + const cMin = Math.min(r, g, b); + const cMax = Math.max(r, g, b); + imageData.data[i * 4 + 3] = (cMin + cMax) / 2; + } +}; diff --git a/invokeai/frontend/web/src/features/controlLayers/konva/naming.ts b/invokeai/frontend/web/src/features/controlLayers/konva/naming.ts new file mode 100644 index 0000000000..354719c836 --- /dev/null +++ b/invokeai/frontend/web/src/features/controlLayers/konva/naming.ts @@ -0,0 +1,38 @@ +/** + * This file contains IDs, names, and ID getters for konva layers and objects. + */ + +// IDs for singleton Konva layers and objects +export const TOOL_PREVIEW_LAYER_ID = 'tool_preview_layer'; +export const TOOL_PREVIEW_BRUSH_GROUP_ID = 'tool_preview_layer.brush_group'; +export const TOOL_PREVIEW_BRUSH_FILL_ID = 'tool_preview_layer.brush_fill'; +export const TOOL_PREVIEW_BRUSH_BORDER_INNER_ID = 'tool_preview_layer.brush_border_inner'; +export const TOOL_PREVIEW_BRUSH_BORDER_OUTER_ID = 'tool_preview_layer.brush_border_outer'; +export const TOOL_PREVIEW_RECT_ID = 'tool_preview_layer.rect'; +export const BACKGROUND_LAYER_ID = 'background_layer'; +export const BACKGROUND_RECT_ID = 'background_layer.rect'; +export const NO_LAYERS_MESSAGE_LAYER_ID = 'no_layers_message'; + +// Names for Konva layers and objects (comparable to CSS classes) +export const CA_LAYER_NAME = 'control_adapter_layer'; +export const CA_LAYER_IMAGE_NAME = 'control_adapter_layer.image'; +export const RG_LAYER_NAME = 'regional_guidance_layer'; +export const RG_LAYER_LINE_NAME = 'regional_guidance_layer.line'; +export const RG_LAYER_OBJECT_GROUP_NAME = 'regional_guidance_layer.object_group'; +export const RG_LAYER_RECT_NAME = 'regional_guidance_layer.rect'; +export const INITIAL_IMAGE_LAYER_ID = 'singleton_initial_image_layer'; +export const INITIAL_IMAGE_LAYER_NAME = 'initial_image_layer'; +export const INITIAL_IMAGE_LAYER_IMAGE_NAME = 'initial_image_layer.image'; +export const LAYER_BBOX_NAME = 'layer.bbox'; +export const COMPOSITING_RECT_NAME = 'compositing-rect'; + +// Getters for non-singleton layer and object IDs +export const getRGLayerId = (layerId: string) => `${RG_LAYER_NAME}_${layerId}`; +export const getRGLayerLineId = (layerId: string, lineId: string) => `${layerId}.line_${lineId}`; +export const getRGLayerRectId = (layerId: string, lineId: string) => `${layerId}.rect_${lineId}`; +export const getRGLayerObjectGroupId = (layerId: string, groupId: string) => `${layerId}.objectGroup_${groupId}`; +export const getLayerBboxId = (layerId: string) => `${layerId}.bbox`; +export const getCALayerId = (layerId: string) => `control_adapter_layer_${layerId}`; +export const getCALayerImageId = (layerId: string, imageName: string) => `${layerId}.image_${imageName}`; +export const getIILayerImageId = (layerId: string, imageName: string) => `${layerId}.image_${imageName}`; +export const getIPALayerId = (layerId: string) => `ip_adapter_layer_${layerId}`; diff --git a/invokeai/frontend/web/src/features/controlLayers/util/renderers.ts b/invokeai/frontend/web/src/features/controlLayers/konva/renderers.ts similarity index 76% rename from invokeai/frontend/web/src/features/controlLayers/util/renderers.ts rename to invokeai/frontend/web/src/features/controlLayers/konva/renderers.ts index 592cf01826..f521c77ed4 100644 --- a/invokeai/frontend/web/src/features/controlLayers/util/renderers.ts +++ b/invokeai/frontend/web/src/features/controlLayers/konva/renderers.ts @@ -1,5 +1,6 @@ -import { calculateNewBrushSize } from 'features/canvas/hooks/useCanvasZoom'; import { rgbaColorToString, rgbColorToString } from 'features/canvas/util/colorToString'; +import { getLayerBboxFast, getLayerBboxPixels } from 'features/controlLayers/konva/bbox'; +import { LightnessToAlphaFilter } from 'features/controlLayers/konva/filters'; import { BACKGROUND_LAYER_ID, BACKGROUND_RECT_ID, @@ -12,10 +13,6 @@ import { getRGLayerObjectGroupId, INITIAL_IMAGE_LAYER_IMAGE_NAME, INITIAL_IMAGE_LAYER_NAME, - isControlAdapterLayer, - isInitialImageLayer, - isRegionalGuidanceLayer, - isRenderableLayer, LAYER_BBOX_NAME, NO_LAYERS_MESSAGE_LAYER_ID, RG_LAYER_LINE_NAME, @@ -28,11 +25,15 @@ import { TOOL_PREVIEW_BRUSH_GROUP_ID, TOOL_PREVIEW_LAYER_ID, TOOL_PREVIEW_RECT_ID, +} from 'features/controlLayers/konva/naming'; +import { getScaledFlooredCursorPosition, snapPosToStage } from 'features/controlLayers/konva/util'; +import { + isControlAdapterLayer, + isInitialImageLayer, + isRegionalGuidanceLayer, + isRenderableLayer, } from 'features/controlLayers/store/controlLayersSlice'; import type { - AddLineArg, - AddPointToLineArg, - AddRectArg, ControlAdapterLayer, InitialImageLayer, Layer, @@ -41,24 +42,21 @@ import type { VectorMaskLine, VectorMaskRect, } from 'features/controlLayers/store/types'; -import { getLayerBboxFast, getLayerBboxPixels } from 'features/controlLayers/util/bbox'; import { t } from 'i18next'; import Konva from 'konva'; -import type { KonvaEventObject } from 'konva/lib/Node'; import type { IRect, Vector2d } from 'konva/lib/types'; import { debounce } from 'lodash-es'; -import type { WritableAtom } from 'nanostores'; import type { RgbColor } from 'react-colorful'; import type { ImageDTO } from 'services/api/types'; import { assert } from 'tsafe'; import { v4 as uuidv4 } from 'uuid'; -const BBOX_SELECTED_STROKE = 'rgba(78, 190, 255, 1)'; -const BRUSH_BORDER_INNER_COLOR = 'rgba(0,0,0,1)'; -const BRUSH_BORDER_OUTER_COLOR = 'rgba(255,255,255,0.8)'; -// This is invokeai/frontend/web/public/assets/images/transparent_bg.png as a dataURL -export const STAGE_BG_DATAURL = - 'data:image/png;base64,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'; +import { + BBOX_SELECTED_STROKE, + BRUSH_BORDER_INNER_COLOR, + BRUSH_BORDER_OUTER_COLOR, + TRANSPARENCY_CHECKER_PATTERN, +} from './constants'; const mapId = (object: { id: string }): string => object.id; @@ -75,46 +73,6 @@ const selectVectorMaskObjects = (node: Konva.Node): boolean => { return node.name() === RG_LAYER_LINE_NAME || node.name() === RG_LAYER_RECT_NAME; }; -const getIsFocused = (stage: Konva.Stage) => { - return stage.container().contains(document.activeElement); -}; -const getIsMouseDown = (e: KonvaEventObject) => e.evt.buttons === 1; - -const SNAP_PX = 10; - -const snapPosToStage = (pos: Vector2d, stage: Konva.Stage) => { - const snappedPos = { ...pos }; - // Get the normalized threshold for snapping to the edge of the stage - const thresholdX = SNAP_PX / stage.scaleX(); - const thresholdY = SNAP_PX / stage.scaleY(); - const stageWidth = stage.width() / stage.scaleX(); - const stageHeight = stage.height() / stage.scaleY(); - // Snap to the edge of the stage if within threshold - if (pos.x - thresholdX < 0) { - snappedPos.x = 0; - } else if (pos.x + thresholdX > stageWidth) { - snappedPos.x = Math.floor(stageWidth); - } - if (pos.y - thresholdY < 0) { - snappedPos.y = 0; - } else if (pos.y + thresholdY > stageHeight) { - snappedPos.y = Math.floor(stageHeight); - } - return snappedPos; -}; - -const getScaledFlooredCursorPosition = (stage: Konva.Stage) => { - const pointerPosition = stage.getPointerPosition(); - const stageTransform = stage.getAbsoluteTransform().copy(); - if (!pointerPosition) { - return; - } - const scaledCursorPosition = stageTransform.invert().point(pointerPosition); - return { - x: Math.floor(scaledCursorPosition.x), - y: Math.floor(scaledCursorPosition.y), - }; -}; /** * Creates the singleton tool preview layer and all its objects. * @param stage The konva stage @@ -933,7 +891,7 @@ const createBackgroundLayer = (stage: Konva.Stage): Konva.Layer => { image.onload = () => { background.fillPatternImage(image); }; - image.src = STAGE_BG_DATAURL; + image.src = TRANSPARENCY_CHECKER_PATTERN; return layer; }; @@ -1030,194 +988,6 @@ const renderNoLayersMessage = (stage: Konva.Stage, layerCount: number, width: nu } }; -type SetStageEventHandlersArg = { - stage: Konva.Stage; - $tool: WritableAtom; - $isDrawing: WritableAtom; - $lastMouseDownPos: WritableAtom; - $lastCursorPos: WritableAtom; - $lastAddedPoint: WritableAtom; - $brushSize: WritableAtom; - $brushSpacingPx: WritableAtom; - $selectedLayerId: WritableAtom; - $selectedLayerType: WritableAtom; - $shouldInvertBrushSizeScrollDirection: WritableAtom; - onRGLayerLineAdded: (arg: AddLineArg) => void; - onRGLayerPointAddedToLine: (arg: AddPointToLineArg) => void; - onRGLayerRectAdded: (arg: AddRectArg) => void; - onBrushSizeChanged: (size: number) => void; -}; - -export const setStageEventHandlers = ({ - stage, - $tool, - $isDrawing, - $lastMouseDownPos, - $lastCursorPos, - $lastAddedPoint, - $brushSize, - $brushSpacingPx, - $selectedLayerId, - $selectedLayerType, - $shouldInvertBrushSizeScrollDirection, - onRGLayerLineAdded, - onRGLayerPointAddedToLine, - onRGLayerRectAdded, - onBrushSizeChanged, -}: SetStageEventHandlersArg): (() => void) => { - const syncCursorPos = (stage: Konva.Stage) => { - const pos = getScaledFlooredCursorPosition(stage); - if (!pos) { - return null; - } - $lastCursorPos.set(pos); - return pos; - }; - - stage.on('mouseenter', (e) => { - const stage = e.target.getStage(); - if (!stage) { - return; - } - const tool = $tool.get(); - stage.findOne(`#${TOOL_PREVIEW_LAYER_ID}`)?.visible(tool === 'brush' || tool === 'eraser'); - }); - - stage.on('mousedown', (e) => { - const stage = e.target.getStage(); - if (!stage) { - return; - } - const tool = $tool.get(); - const pos = syncCursorPos(stage); - const selectedLayerId = $selectedLayerId.get(); - const selectedLayerType = $selectedLayerType.get(); - if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') { - return; - } - if (tool === 'brush' || tool === 'eraser') { - onRGLayerLineAdded({ - layerId: selectedLayerId, - points: [pos.x, pos.y, pos.x, pos.y], - tool, - }); - $isDrawing.set(true); - $lastMouseDownPos.set(pos); - } else if (tool === 'rect') { - $lastMouseDownPos.set(snapPosToStage(pos, stage)); - } - }); - - stage.on('mouseup', (e) => { - const stage = e.target.getStage(); - if (!stage) { - return; - } - const pos = $lastCursorPos.get(); - const selectedLayerId = $selectedLayerId.get(); - const selectedLayerType = $selectedLayerType.get(); - - if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') { - return; - } - const lastPos = $lastMouseDownPos.get(); - const tool = $tool.get(); - if (lastPos && selectedLayerId && tool === 'rect') { - const snappedPos = snapPosToStage(pos, stage); - onRGLayerRectAdded({ - layerId: selectedLayerId, - rect: { - x: Math.min(snappedPos.x, lastPos.x), - y: Math.min(snappedPos.y, lastPos.y), - width: Math.abs(snappedPos.x - lastPos.x), - height: Math.abs(snappedPos.y - lastPos.y), - }, - }); - } - $isDrawing.set(false); - $lastMouseDownPos.set(null); - }); - - stage.on('mousemove', (e) => { - const stage = e.target.getStage(); - if (!stage) { - return; - } - const tool = $tool.get(); - const pos = syncCursorPos(stage); - const selectedLayerId = $selectedLayerId.get(); - const selectedLayerType = $selectedLayerType.get(); - - stage.findOne(`#${TOOL_PREVIEW_LAYER_ID}`)?.visible(tool === 'brush' || tool === 'eraser'); - - if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') { - return; - } - if (getIsFocused(stage) && getIsMouseDown(e) && (tool === 'brush' || tool === 'eraser')) { - if ($isDrawing.get()) { - // Continue the last line - const lastAddedPoint = $lastAddedPoint.get(); - if (lastAddedPoint) { - // Dispatching redux events impacts perf substantially - using brush spacing keeps dispatches to a reasonable number - if (Math.hypot(lastAddedPoint.x - pos.x, lastAddedPoint.y - pos.y) < $brushSpacingPx.get()) { - return; - } - } - $lastAddedPoint.set({ x: pos.x, y: pos.y }); - onRGLayerPointAddedToLine({ layerId: selectedLayerId, point: [pos.x, pos.y] }); - } else { - // Start a new line - onRGLayerLineAdded({ layerId: selectedLayerId, points: [pos.x, pos.y, pos.x, pos.y], tool }); - } - $isDrawing.set(true); - } - }); - - stage.on('mouseleave', (e) => { - const stage = e.target.getStage(); - if (!stage) { - return; - } - const pos = syncCursorPos(stage); - $isDrawing.set(false); - $lastCursorPos.set(null); - $lastMouseDownPos.set(null); - const selectedLayerId = $selectedLayerId.get(); - const selectedLayerType = $selectedLayerType.get(); - const tool = $tool.get(); - - stage.findOne(`#${TOOL_PREVIEW_LAYER_ID}`)?.visible(false); - - if (!pos || !selectedLayerId || selectedLayerType !== 'regional_guidance_layer') { - return; - } - if (getIsFocused(stage) && getIsMouseDown(e) && (tool === 'brush' || tool === 'eraser')) { - onRGLayerPointAddedToLine({ layerId: selectedLayerId, point: [pos.x, pos.y] }); - } - }); - - stage.on('wheel', (e) => { - e.evt.preventDefault(); - const selectedLayerType = $selectedLayerType.get(); - const tool = $tool.get(); - if (selectedLayerType !== 'regional_guidance_layer' || (tool !== 'brush' && tool !== 'eraser')) { - return; - } - - // Invert the delta if the property is set to true - let delta = e.evt.deltaY; - if ($shouldInvertBrushSizeScrollDirection.get()) { - delta = -delta; - } - - if (e.evt.ctrlKey || e.evt.metaKey) { - onBrushSizeChanged(calculateNewBrushSize($brushSize.get(), delta)); - } - }); - - return () => stage.off('mousedown mouseup mousemove mouseenter mouseleave wheel'); -}; - export const renderers = { renderToolPreview, renderLayers, @@ -1239,20 +1009,3 @@ export const debouncedRenderers = { arrangeLayers: debounce(arrangeLayers, DEBOUNCE_MS), updateBboxes: debounce(updateBboxes, DEBOUNCE_MS), }; - -/** - * Calculates the lightness (HSL) of a given pixel and sets the alpha channel to that value. - * This is useful for edge maps and other masks, to make the black areas transparent. - * @param imageData The image data to apply the filter to - */ -const LightnessToAlphaFilter = (imageData: ImageData): void => { - const len = imageData.data.length / 4; - for (let i = 0; i < len; i++) { - const r = imageData.data[i * 4 + 0] as number; - const g = imageData.data[i * 4 + 1] as number; - const b = imageData.data[i * 4 + 2] as number; - const cMin = Math.min(r, g, b); - const cMax = Math.max(r, g, b); - imageData.data[i * 4 + 3] = (cMin + cMax) / 2; - } -}; diff --git a/invokeai/frontend/web/src/features/controlLayers/konva/util.ts b/invokeai/frontend/web/src/features/controlLayers/konva/util.ts new file mode 100644 index 0000000000..29f81fb799 --- /dev/null +++ b/invokeai/frontend/web/src/features/controlLayers/konva/util.ts @@ -0,0 +1,67 @@ +import type Konva from 'konva'; +import type { KonvaEventObject } from 'konva/lib/Node'; +import type { Vector2d } from 'konva/lib/types'; + +//#region getScaledFlooredCursorPosition +/** + * Gets the scaled and floored cursor position on the stage. If the cursor is not currently over the stage, returns null. + * @param stage The konva stage + */ +export const getScaledFlooredCursorPosition = (stage: Konva.Stage): Vector2d | null => { + const pointerPosition = stage.getPointerPosition(); + const stageTransform = stage.getAbsoluteTransform().copy(); + if (!pointerPosition) { + return null; + } + const scaledCursorPosition = stageTransform.invert().point(pointerPosition); + return { + x: Math.floor(scaledCursorPosition.x), + y: Math.floor(scaledCursorPosition.y), + }; +}; +//#endregion + +//#region snapPosToStage +/** + * Snaps a position to the edge of the stage if within a threshold of the edge + * @param pos The position to snap + * @param stage The konva stage + * @param snapPx The snap threshold in pixels + */ +export const snapPosToStage = (pos: Vector2d, stage: Konva.Stage, snapPx = 10): Vector2d => { + const snappedPos = { ...pos }; + // Get the normalized threshold for snapping to the edge of the stage + const thresholdX = snapPx / stage.scaleX(); + const thresholdY = snapPx / stage.scaleY(); + const stageWidth = stage.width() / stage.scaleX(); + const stageHeight = stage.height() / stage.scaleY(); + // Snap to the edge of the stage if within threshold + if (pos.x - thresholdX < 0) { + snappedPos.x = 0; + } else if (pos.x + thresholdX > stageWidth) { + snappedPos.x = Math.floor(stageWidth); + } + if (pos.y - thresholdY < 0) { + snappedPos.y = 0; + } else if (pos.y + thresholdY > stageHeight) { + snappedPos.y = Math.floor(stageHeight); + } + return snappedPos; +}; +//#endregion + +//#region getIsMouseDown +/** + * Checks if the left mouse button is currently pressed + * @param e The konva event + */ +export const getIsMouseDown = (e: KonvaEventObject): boolean => e.evt.buttons === 1; +//#endregion + +//#region getIsFocused +/** + * Checks if the stage is currently focused + * @param stage The konva stage + */ +export const getIsFocused = (stage: Konva.Stage): boolean => stage.container().contains(document.activeElement); +//#endregion diff --git a/invokeai/frontend/web/src/features/controlLayers/store/controlLayersSlice.ts b/invokeai/frontend/web/src/features/controlLayers/store/controlLayersSlice.ts index e298c429c9..8d6a6ecfd9 100644 --- a/invokeai/frontend/web/src/features/controlLayers/store/controlLayersSlice.ts +++ b/invokeai/frontend/web/src/features/controlLayers/store/controlLayersSlice.ts @@ -4,6 +4,14 @@ import type { PersistConfig, RootState } from 'app/store/store'; import { moveBackward, moveForward, moveToBack, moveToFront } from 'common/util/arrayUtils'; import { deepClone } from 'common/util/deepClone'; import { roundDownToMultiple } from 'common/util/roundDownToMultiple'; +import { + getCALayerId, + getIPALayerId, + getRGLayerId, + getRGLayerLineId, + getRGLayerRectId, + INITIAL_IMAGE_LAYER_ID, +} from 'features/controlLayers/konva/naming'; import type { CLIPVisionModelV2, ControlModeV2, @@ -886,57 +894,22 @@ const migrateControlLayersState = (state: any): any => { return state; }; +// Ephemeral interaction state export const $isDrawing = atom(false); export const $lastMouseDownPos = atom(null); export const $tool = atom('brush'); export const $lastCursorPos = atom(null); export const $isPreviewVisible = atom(true); export const $lastAddedPoint = atom(null); + +// Some nanostores that are manually synced to redux state to provide imperative access +// TODO(psyche): This is a hack, figure out another way to handle this... export const $brushSize = atom(0); export const $brushSpacingPx = atom(0); export const $selectedLayerId = atom(null); export const $selectedLayerType = atom(null); export const $shouldInvertBrushSizeScrollDirection = atom(false); -export const BRUSH_SPACING_PCT = 10; -export const MIN_BRUSH_SPACING_PX = 5; -export const MAX_BRUSH_SPACING_PX = 15; - -// IDs for singleton Konva layers and objects -export const TOOL_PREVIEW_LAYER_ID = 'tool_preview_layer'; -export const TOOL_PREVIEW_BRUSH_GROUP_ID = 'tool_preview_layer.brush_group'; -export const TOOL_PREVIEW_BRUSH_FILL_ID = 'tool_preview_layer.brush_fill'; -export const TOOL_PREVIEW_BRUSH_BORDER_INNER_ID = 'tool_preview_layer.brush_border_inner'; -export const TOOL_PREVIEW_BRUSH_BORDER_OUTER_ID = 'tool_preview_layer.brush_border_outer'; -export const TOOL_PREVIEW_RECT_ID = 'tool_preview_layer.rect'; -export const BACKGROUND_LAYER_ID = 'background_layer'; -export const BACKGROUND_RECT_ID = 'background_layer.rect'; -export const NO_LAYERS_MESSAGE_LAYER_ID = 'no_layers_message'; - -// Names (aka classes) for Konva layers and objects -export const CA_LAYER_NAME = 'control_adapter_layer'; -export const CA_LAYER_IMAGE_NAME = 'control_adapter_layer.image'; -export const RG_LAYER_NAME = 'regional_guidance_layer'; -export const RG_LAYER_LINE_NAME = 'regional_guidance_layer.line'; -export const RG_LAYER_OBJECT_GROUP_NAME = 'regional_guidance_layer.object_group'; -export const RG_LAYER_RECT_NAME = 'regional_guidance_layer.rect'; -export const INITIAL_IMAGE_LAYER_ID = 'singleton_initial_image_layer'; -export const INITIAL_IMAGE_LAYER_NAME = 'initial_image_layer'; -export const INITIAL_IMAGE_LAYER_IMAGE_NAME = 'initial_image_layer.image'; -export const LAYER_BBOX_NAME = 'layer.bbox'; -export const COMPOSITING_RECT_NAME = 'compositing-rect'; - -// Getters for non-singleton layer and object IDs -export const getRGLayerId = (layerId: string) => `${RG_LAYER_NAME}_${layerId}`; -const getRGLayerLineId = (layerId: string, lineId: string) => `${layerId}.line_${lineId}`; -const getRGLayerRectId = (layerId: string, lineId: string) => `${layerId}.rect_${lineId}`; -export const getRGLayerObjectGroupId = (layerId: string, groupId: string) => `${layerId}.objectGroup_${groupId}`; -export const getLayerBboxId = (layerId: string) => `${layerId}.bbox`; -export const getCALayerId = (layerId: string) => `control_adapter_layer_${layerId}`; -export const getCALayerImageId = (layerId: string, imageName: string) => `${layerId}.image_${imageName}`; -export const getIILayerImageId = (layerId: string, imageName: string) => `${layerId}.image_${imageName}`; -export const getIPALayerId = (layerId: string) => `ip_adapter_layer_${layerId}`; - export const controlLayersPersistConfig: PersistConfig = { name: controlLayersSlice.name, initialState: initialControlLayersState, diff --git a/invokeai/frontend/web/src/features/controlLayers/util/getLayerBlobs.ts b/invokeai/frontend/web/src/features/controlLayers/util/getLayerBlobs.ts deleted file mode 100644 index 9e5fbfc258..0000000000 --- a/invokeai/frontend/web/src/features/controlLayers/util/getLayerBlobs.ts +++ /dev/null @@ -1,67 +0,0 @@ -import { getStore } from 'app/store/nanostores/store'; -import openBase64ImageInTab from 'common/util/openBase64ImageInTab'; -import { blobToDataURL } from 'features/canvas/util/blobToDataURL'; -import { isRegionalGuidanceLayer, RG_LAYER_NAME } from 'features/controlLayers/store/controlLayersSlice'; -import { renderers } from 'features/controlLayers/util/renderers'; -import Konva from 'konva'; -import { getImageDTO } from 'services/api/endpoints/images'; -import { assert } from 'tsafe'; - -/** - * Get the blobs of all regional prompt layers. Only visible layers are returned. - * @param layerIds The IDs of the layers to get blobs for. If not provided, all regional prompt layers are used. - * @param preview Whether to open a new tab displaying each layer. - * @returns A map of layer IDs to blobs. - */ -export const getRegionalPromptLayerBlobs = async ( - layerIds?: string[], - preview: boolean = false -): Promise> => { - const state = getStore().getState(); - const { layers } = state.controlLayers.present; - const { width, height } = state.controlLayers.present.size; - const reduxLayers = layers.filter(isRegionalGuidanceLayer); - const container = document.createElement('div'); - const stage = new Konva.Stage({ container, width, height }); - renderers.renderLayers(stage, reduxLayers, 1, 'brush', getImageDTO); - - const konvaLayers = stage.find(`.${RG_LAYER_NAME}`); - const blobs: Record = {}; - - // First remove all layers - for (const layer of konvaLayers) { - layer.remove(); - } - - // Next render each layer to a blob - for (const layer of konvaLayers) { - if (layerIds && !layerIds.includes(layer.id())) { - continue; - } - const reduxLayer = reduxLayers.find((l) => l.id === layer.id()); - assert(reduxLayer, `Redux layer ${layer.id()} not found`); - stage.add(layer); - const blob = await new Promise((resolve) => { - stage.toBlob({ - callback: (blob) => { - assert(blob, 'Blob is null'); - resolve(blob); - }, - }); - }); - - if (preview) { - const base64 = await blobToDataURL(blob); - openBase64ImageInTab([ - { - base64, - caption: `${reduxLayer.id}: ${reduxLayer.positivePrompt} / ${reduxLayer.negativePrompt}`, - }, - ]); - } - layer.remove(); - blobs[layer.id()] = blob; - } - - return blobs; -}; diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageViewer/ImageComparisonHover.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageViewer/ImageComparisonHover.tsx index a02e94b547..9bff769cf0 100644 --- a/invokeai/frontend/web/src/features/gallery/components/ImageViewer/ImageComparisonHover.tsx +++ b/invokeai/frontend/web/src/features/gallery/components/ImageViewer/ImageComparisonHover.tsx @@ -3,7 +3,7 @@ import { useAppSelector } from 'app/store/storeHooks'; import { useBoolean } from 'common/hooks/useBoolean'; import { preventDefault } from 'common/util/stopPropagation'; import type { Dimensions } from 'features/canvas/store/canvasTypes'; -import { STAGE_BG_DATAURL } from 'features/controlLayers/util/renderers'; +import { TRANSPARENCY_CHECKER_PATTERN } from 'features/controlLayers/konva/constants'; import { ImageComparisonLabel } from 'features/gallery/components/ImageViewer/ImageComparisonLabel'; import { memo, useMemo, useRef } from 'react'; @@ -78,7 +78,7 @@ export const ImageComparisonHover = memo(({ firstImage, secondImage, containerDi left={0} right={0} bottom={0} - backgroundImage={STAGE_BG_DATAURL} + backgroundImage={TRANSPARENCY_CHECKER_PATTERN} backgroundRepeat="repeat" opacity={0.2} /> diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageViewer/ImageComparisonSlider.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageViewer/ImageComparisonSlider.tsx index 8972af7d4f..3cdf7c48d5 100644 --- a/invokeai/frontend/web/src/features/gallery/components/ImageViewer/ImageComparisonSlider.tsx +++ b/invokeai/frontend/web/src/features/gallery/components/ImageViewer/ImageComparisonSlider.tsx @@ -2,7 +2,7 @@ import { Box, Flex, Icon, Image } from '@invoke-ai/ui-library'; import { useAppSelector } from 'app/store/storeHooks'; import { preventDefault } from 'common/util/stopPropagation'; import type { Dimensions } from 'features/canvas/store/canvasTypes'; -import { STAGE_BG_DATAURL } from 'features/controlLayers/util/renderers'; +import { TRANSPARENCY_CHECKER_PATTERN } from 'features/controlLayers/konva/constants'; import { ImageComparisonLabel } from 'features/gallery/components/ImageViewer/ImageComparisonLabel'; import { memo, useCallback, useEffect, useMemo, useRef, useState } from 'react'; import { PiCaretLeftBold, PiCaretRightBold } from 'react-icons/pi'; @@ -120,7 +120,7 @@ export const ImageComparisonSlider = memo(({ firstImage, secondImage, containerD left={0} right={0} bottom={0} - backgroundImage={STAGE_BG_DATAURL} + backgroundImage={TRANSPARENCY_CHECKER_PATTERN} backgroundRepeat="repeat" opacity={0.2} /> diff --git a/invokeai/frontend/web/src/features/metadata/util/parsers.ts b/invokeai/frontend/web/src/features/metadata/util/parsers.ts index 0757d2e8db..78d569f987 100644 --- a/invokeai/frontend/web/src/features/metadata/util/parsers.ts +++ b/invokeai/frontend/web/src/features/metadata/util/parsers.ts @@ -4,7 +4,7 @@ import { initialT2IAdapter, } from 'features/controlAdapters/util/buildControlAdapter'; import { buildControlAdapterProcessor } from 'features/controlAdapters/util/buildControlAdapterProcessor'; -import { getCALayerId, getIPALayerId, INITIAL_IMAGE_LAYER_ID } from 'features/controlLayers/store/controlLayersSlice'; +import { getCALayerId, getIPALayerId, INITIAL_IMAGE_LAYER_ID } from 'features/controlLayers/konva/naming'; import type { ControlAdapterLayer, InitialImageLayer, IPAdapterLayer, Layer } from 'features/controlLayers/store/types'; import { zLayer } from 'features/controlLayers/store/types'; import { diff --git a/invokeai/frontend/web/src/features/metadata/util/recallers.ts b/invokeai/frontend/web/src/features/metadata/util/recallers.ts index 5a17fd4b5d..b69a14810d 100644 --- a/invokeai/frontend/web/src/features/metadata/util/recallers.ts +++ b/invokeai/frontend/web/src/features/metadata/util/recallers.ts @@ -6,12 +6,10 @@ import { ipAdaptersReset, t2iAdaptersReset, } from 'features/controlAdapters/store/controlAdaptersSlice'; +import { getCALayerId, getIPALayerId, getRGLayerId } from 'features/controlLayers/konva/naming'; import { allLayersDeleted, caLayerRecalled, - getCALayerId, - getIPALayerId, - getRGLayerId, heightChanged, iiLayerRecalled, ipaLayerRecalled, diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/generation/addControlLayers.ts b/invokeai/frontend/web/src/features/nodes/util/graph/generation/addControlLayers.ts index 2f254fb120..4261318479 100644 --- a/invokeai/frontend/web/src/features/nodes/util/graph/generation/addControlLayers.ts +++ b/invokeai/frontend/web/src/features/nodes/util/graph/generation/addControlLayers.ts @@ -1,6 +1,10 @@ import { getStore } from 'app/store/nanostores/store'; import type { RootState } from 'app/store/store'; import { deepClone } from 'common/util/deepClone'; +import openBase64ImageInTab from 'common/util/openBase64ImageInTab'; +import { blobToDataURL } from 'features/canvas/util/blobToDataURL'; +import { RG_LAYER_NAME } from 'features/controlLayers/konva/naming'; +import { renderers } from 'features/controlLayers/konva/renderers'; import { isControlAdapterLayer, isInitialImageLayer, @@ -16,7 +20,6 @@ import type { ProcessorConfig, T2IAdapterConfigV2, } from 'features/controlLayers/util/controlAdapters'; -import { getRegionalPromptLayerBlobs } from 'features/controlLayers/util/getLayerBlobs'; import type { ImageField } from 'features/nodes/types/common'; import { CONTROL_NET_COLLECT, @@ -31,11 +34,13 @@ import { T2I_ADAPTER_COLLECT, } from 'features/nodes/util/graph/constants'; import type { Graph } from 'features/nodes/util/graph/generation/Graph'; +import Konva from 'konva'; import { size } from 'lodash-es'; import { getImageDTO, imagesApi } from 'services/api/endpoints/images'; import type { BaseModelType, ImageDTO, Invocation } from 'services/api/types'; import { assert } from 'tsafe'; +//#region addControlLayers /** * Adds the control layers to the graph * @param state The app root state @@ -90,7 +95,7 @@ export const addControlLayers = async ( const validRGLayers = validLayers.filter(isRegionalGuidanceLayer); const layerIds = validRGLayers.map((l) => l.id); - const blobs = await getRegionalPromptLayerBlobs(layerIds); + const blobs = await getRGLayerBlobs(layerIds); assert(size(blobs) === size(layerIds), 'Mismatch between layer IDs and blobs'); for (const layer of validRGLayers) { @@ -257,6 +262,7 @@ export const addControlLayers = async ( g.upsertMetadata({ control_layers: { layers: validLayers, version: state.controlLayers.present._version } }); return validLayers; }; +//#endregion //#region Control Adapters const addGlobalControlAdapterToGraph = ( @@ -509,7 +515,7 @@ const isValidLayer = (layer: Layer, base: BaseModelType) => { }; //#endregion -//#region Helpers +//#region getMaskImage const getMaskImage = async (layer: RegionalGuidanceLayer, blob: Blob): Promise => { if (layer.uploadedMaskImage) { const imageDTO = await getImageDTO(layer.uploadedMaskImage.name); @@ -529,7 +535,9 @@ const getMaskImage = async (layer: RegionalGuidanceLayer, blob: Blob): Promise> => { + const state = getStore().getState(); + const { layers } = state.controlLayers.present; + const { width, height } = state.controlLayers.present.size; + const reduxLayers = layers.filter(isRegionalGuidanceLayer); + const container = document.createElement('div'); + const stage = new Konva.Stage({ container, width, height }); + renderers.renderLayers(stage, reduxLayers, 1, 'brush', getImageDTO); + + const konvaLayers = stage.find(`.${RG_LAYER_NAME}`); + const blobs: Record = {}; + + // First remove all layers + for (const layer of konvaLayers) { + layer.remove(); + } + + // Next render each layer to a blob + for (const layer of konvaLayers) { + if (layerIds && !layerIds.includes(layer.id())) { + continue; + } + const reduxLayer = reduxLayers.find((l) => l.id === layer.id()); + assert(reduxLayer, `Redux layer ${layer.id()} not found`); + stage.add(layer); + const blob = await new Promise((resolve) => { + stage.toBlob({ + callback: (blob) => { + assert(blob, 'Blob is null'); + resolve(blob); + }, + }); + }); + + if (preview) { + const base64 = await blobToDataURL(blob); + openBase64ImageInTab([ + { + base64, + caption: `${reduxLayer.id}: ${reduxLayer.positivePrompt} / ${reduxLayer.negativePrompt}`, + }, + ]); + } + layer.remove(); + blobs[layer.id()] = blob; + } + + return blobs; +}; +//#endregion From 2871676f7942dc1a8f8a18cff4ea4f8a3f239276 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Thu, 6 Jun 2024 09:53:35 -0400 Subject: [PATCH 070/110] LoRA patching optimization (#6439) * allow model patcher to optimize away the unpatching step when feasible * remove lazy_offloading functionality * allow model patcher to optimize away the unpatching step when feasible * remove lazy_offloading functionality * do not save original weights if there is a CPU copy of state dict * Update invokeai/backend/model_manager/load/load_base.py Co-authored-by: Ryan Dick * documentation fixes added during penultimate review --------- Co-authored-by: Lincoln Stein Co-authored-by: Kent Keirsey <31807370+hipsterusername@users.noreply.github.com> Co-authored-by: Ryan Dick --- docs/contributing/MODEL_MANAGER.md | 50 +++++++++++++----- invokeai/app/invocations/compel.py | 17 ++++-- invokeai/app/invocations/latent.py | 8 ++- .../backend/model_manager/load/load_base.py | 52 ++++++++++++++++++- .../load/model_cache/model_cache_base.py | 10 ++++ .../load/model_cache/model_locker.py | 8 ++- invokeai/backend/model_patcher.py | 49 +++++++++-------- 7 files changed, 146 insertions(+), 48 deletions(-) diff --git a/docs/contributing/MODEL_MANAGER.md b/docs/contributing/MODEL_MANAGER.md index c12046293c..201d11995d 100644 --- a/docs/contributing/MODEL_MANAGER.md +++ b/docs/contributing/MODEL_MANAGER.md @@ -1367,12 +1367,20 @@ the in-memory loaded model: | `model` | AnyModel | The instantiated model (details below) | | `locker` | ModelLockerBase | A context manager that mediates the movement of the model into VRAM | -Because the loader can return multiple model types, it is typed to -return `AnyModel`, a Union `ModelMixin`, `torch.nn.Module`, -`IAIOnnxRuntimeModel`, `IPAdapter`, `IPAdapterPlus`, and -`EmbeddingModelRaw`. `ModelMixin` is the base class of all diffusers -models, `EmbeddingModelRaw` is used for LoRA and TextualInversion -models. The others are obvious. +### get_model_by_key(key, [submodel]) -> LoadedModel + +The `get_model_by_key()` method will retrieve the model using its +unique database key. For example: + +loaded_model = loader.get_model_by_key('f13dd932c0c35c22dcb8d6cda4203764', SubModelType('vae')) + +`get_model_by_key()` may raise any of the following exceptions: + +* `UnknownModelException` -- key not in database +* `ModelNotFoundException` -- key in database but model not found at path +* `NotImplementedException` -- the loader doesn't know how to load this type of model + +### Using the Loaded Model in Inference `LoadedModel` acts as a context manager. The context loads the model into the execution device (e.g. VRAM on CUDA systems), locks the model @@ -1380,17 +1388,33 @@ in the execution device for the duration of the context, and returns the model. Use it like this: ``` -model_info = loader.get_model_by_key('f13dd932c0c35c22dcb8d6cda4203764', SubModelType('vae')) -with model_info as vae: +loaded_model_= loader.get_model_by_key('f13dd932c0c35c22dcb8d6cda4203764', SubModelType('vae')) +with loaded_model as vae: image = vae.decode(latents)[0] ``` -`get_model_by_key()` may raise any of the following exceptions: +The object returned by the LoadedModel context manager is an +`AnyModel`, which is a Union of `ModelMixin`, `torch.nn.Module`, +`IAIOnnxRuntimeModel`, `IPAdapter`, `IPAdapterPlus`, and +`EmbeddingModelRaw`. `ModelMixin` is the base class of all diffusers +models, `EmbeddingModelRaw` is used for LoRA and TextualInversion +models. The others are obvious. + +In addition, you may call `LoadedModel.model_on_device()`, a context +manager that returns a tuple of the model's state dict in CPU and the +model itself in VRAM. It is used to optimize the LoRA patching and +unpatching process: + +``` +loaded_model_= loader.get_model_by_key('f13dd932c0c35c22dcb8d6cda4203764', SubModelType('vae')) +with loaded_model.model_on_device() as (state_dict, vae): + image = vae.decode(latents)[0] +``` + +Since not all models have state dicts, the `state_dict` return value +can be None. + -* `UnknownModelException` -- key not in database -* `ModelNotFoundException` -- key in database but model not found at path -* `NotImplementedException` -- the loader doesn't know how to load this type of model - ### Emitting model loading events When the `context` argument is passed to `load_model_*()`, it will diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py index 766b44fdc8..1e78e10d38 100644 --- a/invokeai/app/invocations/compel.py +++ b/invokeai/app/invocations/compel.py @@ -81,9 +81,13 @@ class CompelInvocation(BaseInvocation): with ( # apply all patches while the model is on the target device - text_encoder_info as text_encoder, + text_encoder_info.model_on_device() as (model_state_dict, text_encoder), tokenizer_info as tokenizer, - ModelPatcher.apply_lora_text_encoder(text_encoder, _lora_loader()), + ModelPatcher.apply_lora_text_encoder( + text_encoder, + loras=_lora_loader(), + model_state_dict=model_state_dict, + ), # Apply CLIP Skip after LoRA to prevent LoRA application from failing on skipped layers. ModelPatcher.apply_clip_skip(text_encoder, self.clip.skipped_layers), ModelPatcher.apply_ti(tokenizer, text_encoder, ti_list) as ( @@ -172,9 +176,14 @@ class SDXLPromptInvocationBase: with ( # apply all patches while the model is on the target device - text_encoder_info as text_encoder, + text_encoder_info.model_on_device() as (state_dict, text_encoder), tokenizer_info as tokenizer, - ModelPatcher.apply_lora(text_encoder, _lora_loader(), lora_prefix), + ModelPatcher.apply_lora( + text_encoder, + loras=_lora_loader(), + prefix=lora_prefix, + model_state_dict=state_dict, + ), # Apply CLIP Skip after LoRA to prevent LoRA application from failing on skipped layers. ModelPatcher.apply_clip_skip(text_encoder, clip_field.skipped_layers), ModelPatcher.apply_ti(tokenizer, text_encoder, ti_list) as ( diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index ede2443307..8fb9b93f4c 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -952,11 +952,15 @@ class DenoiseLatentsInvocation(BaseInvocation): assert isinstance(unet_info.model, UNet2DConditionModel) with ( ExitStack() as exit_stack, - unet_info as unet, + unet_info.model_on_device() as (model_state_dict, unet), ModelPatcher.apply_freeu(unet, self.unet.freeu_config), set_seamless(unet, self.unet.seamless_axes), # FIXME # Apply the LoRA after unet has been moved to its target device for faster patching. - ModelPatcher.apply_lora_unet(unet, _lora_loader()), + ModelPatcher.apply_lora_unet( + unet, + loras=_lora_loader(), + model_state_dict=model_state_dict, + ), ): assert isinstance(unet, UNet2DConditionModel) latents = latents.to(device=unet.device, dtype=unet.dtype) diff --git a/invokeai/backend/model_manager/load/load_base.py b/invokeai/backend/model_manager/load/load_base.py index c336926aea..1bb093a990 100644 --- a/invokeai/backend/model_manager/load/load_base.py +++ b/invokeai/backend/model_manager/load/load_base.py @@ -4,10 +4,13 @@ Base class for model loading in InvokeAI. """ from abc import ABC, abstractmethod +from contextlib import contextmanager from dataclasses import dataclass from logging import Logger from pathlib import Path -from typing import Any, Optional +from typing import Any, Dict, Generator, Optional, Tuple + +import torch from invokeai.app.services.config import InvokeAIAppConfig from invokeai.backend.model_manager.config import ( @@ -21,7 +24,42 @@ from invokeai.backend.model_manager.load.model_cache.model_cache_base import Mod @dataclass class LoadedModel: - """Context manager object that mediates transfer from RAM<->VRAM.""" + """ + Context manager object that mediates transfer from RAM<->VRAM. + + This is a context manager object that has two distinct APIs: + + 1. Older API (deprecated): + Use the LoadedModel object directly as a context manager. + It will move the model into VRAM (on CUDA devices), and + return the model in a form suitable for passing to torch. + Example: + ``` + loaded_model_= loader.get_model_by_key('f13dd932', SubModelType('vae')) + with loaded_model as vae: + image = vae.decode(latents)[0] + ``` + + 2. Newer API (recommended): + Call the LoadedModel's `model_on_device()` method in a + context. It returns a tuple consisting of a copy of + the model's state dict in CPU RAM followed by a copy + of the model in VRAM. The state dict is provided to allow + LoRAs and other model patchers to return the model to + its unpatched state without expensive copy and restore + operations. + + Example: + ``` + loaded_model_= loader.get_model_by_key('f13dd932', SubModelType('vae')) + with loaded_model.model_on_device() as (state_dict, vae): + image = vae.decode(latents)[0] + ``` + + The state_dict should be treated as a read-only object and + never modified. Also be aware that some loadable models do + not have a state_dict, in which case this value will be None. + """ config: AnyModelConfig _locker: ModelLockerBase @@ -35,6 +73,16 @@ class LoadedModel: """Context exit.""" self._locker.unlock() + @contextmanager + def model_on_device(self) -> Generator[Tuple[Optional[Dict[str, torch.Tensor]], AnyModel], None, None]: + """Return a tuple consisting of the model's state dict (if it exists) and the locked model on execution device.""" + locked_model = self._locker.lock() + try: + state_dict = self._locker.get_state_dict() + yield (state_dict, locked_model) + finally: + self._locker.unlock() + @property def model(self) -> AnyModel: """Return the model without locking it.""" diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_base.py b/invokeai/backend/model_manager/load/model_cache/model_cache_base.py index 2ecb3b5d79..0106c0ff18 100644 --- a/invokeai/backend/model_manager/load/model_cache/model_cache_base.py +++ b/invokeai/backend/model_manager/load/model_cache/model_cache_base.py @@ -30,6 +30,11 @@ class ModelLockerBase(ABC): """Unlock the contained model, and remove it from VRAM.""" pass + @abstractmethod + def get_state_dict(self) -> Optional[Dict[str, torch.Tensor]]: + """Return the state dict (if any) for the cached model.""" + pass + @property @abstractmethod def model(self) -> AnyModel: @@ -56,6 +61,11 @@ class CacheRecord(Generic[T]): and then injected into the model. When the model is finished, the VRAM copy of the state dict is deleted, and the RAM version is reinjected into the model. + + The state_dict should be treated as a read-only attribute. Do not attempt + to patch or otherwise modify it. Instead, patch the copy of the state_dict + after it is loaded into the execution device (e.g. CUDA) using the `LoadedModel` + context manager call `model_on_device()`. """ key: str diff --git a/invokeai/backend/model_manager/load/model_cache/model_locker.py b/invokeai/backend/model_manager/load/model_cache/model_locker.py index 269ac60479..6d90ed92e8 100644 --- a/invokeai/backend/model_manager/load/model_cache/model_locker.py +++ b/invokeai/backend/model_manager/load/model_cache/model_locker.py @@ -2,6 +2,8 @@ Base class and implementation of a class that moves models in and out of VRAM. """ +from typing import Dict, Optional + import torch from invokeai.backend.model_manager import AnyModel @@ -27,6 +29,10 @@ class ModelLocker(ModelLockerBase): """Return the model without moving it around.""" return self._cache_entry.model + def get_state_dict(self) -> Optional[Dict[str, torch.Tensor]]: + """Return the state dict (if any) for the cached model.""" + return self._cache_entry.state_dict + def lock(self) -> AnyModel: """Move the model into the execution device (GPU) and lock it.""" if not hasattr(self.model, "to"): @@ -37,10 +43,8 @@ class ModelLocker(ModelLockerBase): try: if self._cache.lazy_offloading: self._cache.offload_unlocked_models(self._cache_entry.size) - self._cache.move_model_to_device(self._cache_entry, self._cache.execution_device) self._cache_entry.loaded = True - self._cache.logger.debug(f"Locking {self._cache_entry.key} in {self._cache.execution_device}") self._cache.print_cuda_stats() except torch.cuda.OutOfMemoryError: diff --git a/invokeai/backend/model_patcher.py b/invokeai/backend/model_patcher.py index 76271fc025..c407cd8472 100644 --- a/invokeai/backend/model_patcher.py +++ b/invokeai/backend/model_patcher.py @@ -5,7 +5,7 @@ from __future__ import annotations import pickle from contextlib import contextmanager -from typing import Any, Dict, Iterator, List, Optional, Tuple, Union +from typing import Any, Dict, Generator, Iterator, List, Optional, Tuple, Union import numpy as np import torch @@ -66,8 +66,14 @@ class ModelPatcher: cls, unet: UNet2DConditionModel, loras: Iterator[Tuple[LoRAModelRaw, float]], + model_state_dict: Optional[Dict[str, torch.Tensor]] = None, ) -> None: - with cls.apply_lora(unet, loras, "lora_unet_"): + with cls.apply_lora( + unet, + loras=loras, + prefix="lora_unet_", + model_state_dict=model_state_dict, + ): yield @classmethod @@ -76,28 +82,9 @@ class ModelPatcher: cls, text_encoder: CLIPTextModel, loras: Iterator[Tuple[LoRAModelRaw, float]], + model_state_dict: Optional[Dict[str, torch.Tensor]] = None, ) -> None: - with cls.apply_lora(text_encoder, loras, "lora_te_"): - yield - - @classmethod - @contextmanager - def apply_sdxl_lora_text_encoder( - cls, - text_encoder: CLIPTextModel, - loras: List[Tuple[LoRAModelRaw, float]], - ) -> None: - with cls.apply_lora(text_encoder, loras, "lora_te1_"): - yield - - @classmethod - @contextmanager - def apply_sdxl_lora_text_encoder2( - cls, - text_encoder: CLIPTextModel, - loras: List[Tuple[LoRAModelRaw, float]], - ) -> None: - with cls.apply_lora(text_encoder, loras, "lora_te2_"): + with cls.apply_lora(text_encoder, loras=loras, prefix="lora_te_", model_state_dict=model_state_dict): yield @classmethod @@ -107,7 +94,16 @@ class ModelPatcher: model: AnyModel, loras: Iterator[Tuple[LoRAModelRaw, float]], prefix: str, - ) -> None: + model_state_dict: Optional[Dict[str, torch.Tensor]] = None, + ) -> Generator[Any, None, None]: + """ + Apply one or more LoRAs to a model. + + :param model: The model to patch. + :param loras: An iterator that returns the LoRA to patch in and its patch weight. + :param prefix: A string prefix that precedes keys used in the LoRAs weight layers. + :model_state_dict: Read-only copy of the model's state dict in CPU, for unpatching purposes. + """ original_weights = {} try: with torch.no_grad(): @@ -133,7 +129,10 @@ class ModelPatcher: dtype = module.weight.dtype if module_key not in original_weights: - original_weights[module_key] = module.weight.detach().to(device="cpu", copy=True) + if model_state_dict is not None: # we were provided with the CPU copy of the state dict + original_weights[module_key] = model_state_dict[module_key + ".weight"] + else: + original_weights[module_key] = module.weight.detach().to(device="cpu", copy=True) layer_scale = layer.alpha / layer.rank if (layer.alpha and layer.rank) else 1.0 From 6d067e56f2dcf8f12a219167df354c667d92dea8 Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Fri, 7 Jun 2024 09:35:31 +1000 Subject: [PATCH 071/110] fix(ui): on page load, if CA processed image no longer exists, re-process it --- .../listeners/controlAdapterPreprocessor.ts | 11 +++++-- .../CALayer/CALayerControlAdapterWrapper.tsx | 11 +++++++ .../ControlAndIPAdapter/ControlAdapter.tsx | 6 ++++ .../ControlAdapterImagePreview.tsx | 31 ++++++++++++++++--- 4 files changed, 53 insertions(+), 6 deletions(-) diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlAdapterPreprocessor.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlAdapterPreprocessor.ts index ba04947a2d..a1eb917ebb 100644 --- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlAdapterPreprocessor.ts +++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlAdapterPreprocessor.ts @@ -22,7 +22,13 @@ import type { BatchConfig } from 'services/api/types'; import { socketInvocationComplete } from 'services/events/actions'; import { assert } from 'tsafe'; -const matcher = isAnyOf(caLayerImageChanged, caLayerProcessorConfigChanged, caLayerModelChanged, caLayerRecalled); +const matcher = isAnyOf( + caLayerImageChanged, + caLayerProcessedImageChanged, + caLayerProcessorConfigChanged, + caLayerModelChanged, + caLayerRecalled +); const DEBOUNCE_MS = 300; const log = logger('session'); @@ -73,9 +79,10 @@ export const addControlAdapterPreprocessor = (startAppListening: AppStartListeni const originalConfig = originalLayer?.controlAdapter.processorConfig; const image = layer.controlAdapter.image; + const processedImage = layer.controlAdapter.processedImage; const config = layer.controlAdapter.processorConfig; - if (isEqual(config, originalConfig) && isEqual(image, originalImage)) { + if (isEqual(config, originalConfig) && isEqual(image, originalImage) && processedImage) { // Neither config nor image have changed, we can bail return; } diff --git a/invokeai/frontend/web/src/features/controlLayers/components/CALayer/CALayerControlAdapterWrapper.tsx b/invokeai/frontend/web/src/features/controlLayers/components/CALayer/CALayerControlAdapterWrapper.tsx index 8ff1f9711f..a44ae32c13 100644 --- a/invokeai/frontend/web/src/features/controlLayers/components/CALayer/CALayerControlAdapterWrapper.tsx +++ b/invokeai/frontend/web/src/features/controlLayers/components/CALayer/CALayerControlAdapterWrapper.tsx @@ -4,6 +4,7 @@ import { caLayerControlModeChanged, caLayerImageChanged, caLayerModelChanged, + caLayerProcessedImageChanged, caLayerProcessorConfigChanged, caOrIPALayerBeginEndStepPctChanged, caOrIPALayerWeightChanged, @@ -84,6 +85,14 @@ export const CALayerControlAdapterWrapper = memo(({ layerId }: Props) => { [dispatch, layerId] ); + const onErrorLoadingImage = useCallback(() => { + dispatch(caLayerImageChanged({ layerId, imageDTO: null })); + }, [dispatch, layerId]); + + const onErrorLoadingProcessedImage = useCallback(() => { + dispatch(caLayerProcessedImageChanged({ layerId, imageDTO: null })); + }, [dispatch, layerId]); + const droppableData = useMemo( () => ({ actionType: 'SET_CA_LAYER_IMAGE', @@ -114,6 +123,8 @@ export const CALayerControlAdapterWrapper = memo(({ layerId }: Props) => { onChangeImage={onChangeImage} droppableData={droppableData} postUploadAction={postUploadAction} + onErrorLoadingImage={onErrorLoadingImage} + onErrorLoadingProcessedImage={onErrorLoadingProcessedImage} /> ); }); diff --git a/invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/ControlAdapter.tsx b/invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/ControlAdapter.tsx index c28c40ecc1..2a7b21352e 100644 --- a/invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/ControlAdapter.tsx +++ b/invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/ControlAdapter.tsx @@ -28,6 +28,8 @@ type Props = { onChangeProcessorConfig: (processorConfig: ProcessorConfig | null) => void; onChangeModel: (modelConfig: ControlNetModelConfig | T2IAdapterModelConfig) => void; onChangeImage: (imageDTO: ImageDTO | null) => void; + onErrorLoadingImage: () => void; + onErrorLoadingProcessedImage: () => void; droppableData: TypesafeDroppableData; postUploadAction: PostUploadAction; }; @@ -41,6 +43,8 @@ export const ControlAdapter = memo( onChangeProcessorConfig, onChangeModel, onChangeImage, + onErrorLoadingImage, + onErrorLoadingProcessedImage, droppableData, postUploadAction, }: Props) => { @@ -91,6 +95,8 @@ export const ControlAdapter = memo( onChangeImage={onChangeImage} droppableData={droppableData} postUploadAction={postUploadAction} + onErrorLoadingImage={onErrorLoadingImage} + onErrorLoadingProcessedImage={onErrorLoadingProcessedImage} /> diff --git a/invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/ControlAdapterImagePreview.tsx b/invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/ControlAdapterImagePreview.tsx index 4d93eb12ec..c61cdda4a3 100644 --- a/invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/ControlAdapterImagePreview.tsx +++ b/invokeai/frontend/web/src/features/controlLayers/components/ControlAndIPAdapter/ControlAdapterImagePreview.tsx @@ -27,10 +27,19 @@ type Props = { onChangeImage: (imageDTO: ImageDTO | null) => void; droppableData: TypesafeDroppableData; postUploadAction: PostUploadAction; + onErrorLoadingImage: () => void; + onErrorLoadingProcessedImage: () => void; }; export const ControlAdapterImagePreview = memo( - ({ controlAdapter, onChangeImage, droppableData, postUploadAction }: Props) => { + ({ + controlAdapter, + onChangeImage, + droppableData, + postUploadAction, + onErrorLoadingImage, + onErrorLoadingProcessedImage, + }: Props) => { const { t } = useTranslation(); const dispatch = useAppDispatch(); const autoAddBoardId = useAppSelector((s) => s.gallery.autoAddBoardId); @@ -128,10 +137,23 @@ export const ControlAdapterImagePreview = memo( controlAdapter.processorConfig !== null; useEffect(() => { - if (isConnected && (isErrorControlImage || isErrorProcessedControlImage)) { - handleResetControlImage(); + if (!isConnected) { + return; } - }, [handleResetControlImage, isConnected, isErrorControlImage, isErrorProcessedControlImage]); + if (isErrorControlImage) { + onErrorLoadingImage(); + } + if (isErrorProcessedControlImage) { + onErrorLoadingProcessedImage(); + } + }, [ + handleResetControlImage, + isConnected, + isErrorControlImage, + isErrorProcessedControlImage, + onErrorLoadingImage, + onErrorLoadingProcessedImage, + ]); return ( From f81b8bc9f6452e20672ef6ee52b567a0be77e206 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Mon, 3 Jun 2024 20:31:05 -0400 Subject: [PATCH 072/110] add support for generic loading of diffusers directories --- .../app/services/model_load/model_load_base.py | 7 ++++--- .../services/model_load/model_load_default.py | 13 ++++++++----- .../app/services/shared/invocation_context.py | 8 ++++---- invokeai/backend/model_manager/load/__init__.py | 3 ++- .../backend/model_manager/load/load_base.py | 10 ++++++++-- .../load/model_loaders/generic_diffusers.py | 9 +++------ tests/app/services/model_load/test_load_api.py | 17 +++++++++++------ .../model_manager/model_manager_fixtures.py | 4 ++++ 8 files changed, 44 insertions(+), 27 deletions(-) diff --git a/invokeai/app/services/model_load/model_load_base.py b/invokeai/app/services/model_load/model_load_base.py index 22d815483e..f84b1dae13 100644 --- a/invokeai/app/services/model_load/model_load_base.py +++ b/invokeai/app/services/model_load/model_load_base.py @@ -8,7 +8,7 @@ from typing import Callable, Dict, Optional from torch import Tensor from invokeai.backend.model_manager import AnyModel, AnyModelConfig, SubModelType -from invokeai.backend.model_manager.load import LoadedModel +from invokeai.backend.model_manager.load import LoadedModel, LoadedModelWithoutConfig from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase @@ -38,7 +38,7 @@ class ModelLoadServiceBase(ABC): @abstractmethod def load_model_from_path( self, model_path: Path, loader: Optional[Callable[[Path], Dict[str, Tensor]]] = None - ) -> LoadedModel: + ) -> LoadedModelWithoutConfig: """ Load the model file or directory located at the indicated Path. @@ -47,7 +47,8 @@ class ModelLoadServiceBase(ABC): memory. Otherwise the method will call safetensors.torch.load_file() or torch.load() as appropriate to the file suffix. - Be aware that the LoadedModel object will have a `config` attribute of None. + Be aware that this returns a LoadedModelWithoutConfig object, which is the same as + LoadedModel, but without the config attribute. Args: model_path: A pathlib.Path to a checkpoint-style models file diff --git a/invokeai/app/services/model_load/model_load_default.py b/invokeai/app/services/model_load/model_load_default.py index 776620edca..113334ea0d 100644 --- a/invokeai/app/services/model_load/model_load_default.py +++ b/invokeai/app/services/model_load/model_load_default.py @@ -14,6 +14,7 @@ from invokeai.app.services.invoker import Invoker from invokeai.backend.model_manager import AnyModel, AnyModelConfig, SubModelType from invokeai.backend.model_manager.load import ( LoadedModel, + LoadedModelWithoutConfig, ModelLoaderRegistry, ModelLoaderRegistryBase, ) @@ -85,12 +86,12 @@ class ModelLoadService(ModelLoadServiceBase): return loaded_model def load_model_from_path( - self, model_path: Path, loader: Optional[Callable[[Path], Dict[str, Tensor]]] = None - ) -> LoadedModel: + self, model_path: Path, loader: Optional[Callable[[Path], Dict[str, Tensor] | AnyModel]] = None + ) -> LoadedModelWithoutConfig: cache_key = str(model_path) ram_cache = self.ram_cache try: - return LoadedModel(_locker=ram_cache.get(key=cache_key)) + return LoadedModelWithoutConfig(_locker=ram_cache.get(key=cache_key)) except IndexError: pass @@ -113,11 +114,13 @@ class ModelLoadService(ModelLoadServiceBase): if loader is None: loader = ( - torch_load_file + diffusers_load_directory + if model_path.is_dir() + else torch_load_file if model_path.suffix.endswith((".ckpt", ".pt", ".pth", ".bin")) else lambda path: safetensors_load_file(path, device="cpu") ) raw_model = loader(model_path) ram_cache.put(key=cache_key, model=raw_model) - return LoadedModel(_locker=ram_cache.get(key=cache_key)) + return LoadedModelWithoutConfig(_locker=ram_cache.get(key=cache_key)) diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py index 260bf6a61f..931fc40b82 100644 --- a/invokeai/app/services/shared/invocation_context.py +++ b/invokeai/app/services/shared/invocation_context.py @@ -16,7 +16,7 @@ from invokeai.app.services.invocation_services import InvocationServices from invokeai.app.services.model_records.model_records_base import UnknownModelException from invokeai.app.util.step_callback import stable_diffusion_step_callback from invokeai.backend.model_manager.config import AnyModelConfig, BaseModelType, ModelFormat, ModelType, SubModelType -from invokeai.backend.model_manager.load.load_base import LoadedModel +from invokeai.backend.model_manager.load.load_base import LoadedModel, LoadedModelWithoutConfig from invokeai.backend.stable_diffusion.diffusers_pipeline import PipelineIntermediateState from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningFieldData @@ -461,7 +461,7 @@ class ModelsInterface(InvocationContextInterface): self, source: Path | str | AnyHttpUrl, loader: Optional[Callable[[Path], dict[str, Tensor]]] = None, - ) -> LoadedModel: + ) -> LoadedModelWithoutConfig: """ Download, cache, and load the model file located at the indicated URL. @@ -470,14 +470,14 @@ class ModelsInterface(InvocationContextInterface): If the a loader callable is provided, it will be invoked to load the model. Otherwise, `safetensors.torch.load_file()` or `torch.load()` will be called to load the model. - Be aware that the LoadedModel object will have a `config` attribute of None. + Be aware that the LoadedModelWithoutConfig object has no `config` attribute Args: source: A model Path, URL, or repoid. loader: A Callable that expects a Path and returns a dict[str|int, Any] Returns: - A LoadedModel object. + A LoadedModelWithoutConfig object. """ if isinstance(source, Path): diff --git a/invokeai/backend/model_manager/load/__init__.py b/invokeai/backend/model_manager/load/__init__.py index f47a2c4368..25125f43fb 100644 --- a/invokeai/backend/model_manager/load/__init__.py +++ b/invokeai/backend/model_manager/load/__init__.py @@ -7,7 +7,7 @@ from importlib import import_module from pathlib import Path from .convert_cache.convert_cache_default import ModelConvertCache -from .load_base import LoadedModel, ModelLoaderBase +from .load_base import LoadedModel, LoadedModelWithoutConfig, ModelLoaderBase from .load_default import ModelLoader from .model_cache.model_cache_default import ModelCache from .model_loader_registry import ModelLoaderRegistry, ModelLoaderRegistryBase @@ -19,6 +19,7 @@ for module in loaders: __all__ = [ "LoadedModel", + "LoadedModelWithoutConfig", "ModelCache", "ModelConvertCache", "ModelLoaderBase", diff --git a/invokeai/backend/model_manager/load/load_base.py b/invokeai/backend/model_manager/load/load_base.py index 41a36d7b51..a7c080ed2b 100644 --- a/invokeai/backend/model_manager/load/load_base.py +++ b/invokeai/backend/model_manager/load/load_base.py @@ -20,11 +20,10 @@ from invokeai.backend.model_manager.load.model_cache.model_cache_base import Mod @dataclass -class LoadedModel: +class LoadedModelWithoutConfig: """Context manager object that mediates transfer from RAM<->VRAM.""" _locker: ModelLockerBase - config: Optional[AnyModelConfig] = None def __enter__(self) -> AnyModel: """Context entry.""" @@ -41,6 +40,13 @@ class LoadedModel: return self._locker.model +@dataclass +class LoadedModel(LoadedModelWithoutConfig): + """Context manager object that mediates transfer from RAM<->VRAM.""" + + config: Optional[AnyModelConfig] = None + + # TODO(MM2): # Some "intermediary" subclasses in the ModelLoaderBase class hierarchy define methods that their subclasses don't # know about. I think the problem may be related to this class being an ABC. diff --git a/invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py b/invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py index a4874b33ce..6320797b8a 100644 --- a/invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py +++ b/invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py @@ -65,14 +65,11 @@ class GenericDiffusersLoader(ModelLoader): else: try: config = self._load_diffusers_config(model_path, config_name="config.json") - class_name = config.get("_class_name", None) - if class_name: + if class_name := config.get("_class_name"): result = self._hf_definition_to_type(module="diffusers", class_name=class_name) - if config.get("model_type", None) == "clip_vision_model": - class_name = config.get("architectures") - assert class_name is not None + elif class_name := config.get("architectures"): result = self._hf_definition_to_type(module="transformers", class_name=class_name[0]) - if not class_name: + else: raise InvalidModelConfigException("Unable to decipher Load Class based on given config.json") except KeyError as e: raise InvalidModelConfigException("An expected config.json file is missing from this model.") from e diff --git a/tests/app/services/model_load/test_load_api.py b/tests/app/services/model_load/test_load_api.py index a10bc4d66a..9671c8c6c3 100644 --- a/tests/app/services/model_load/test_load_api.py +++ b/tests/app/services/model_load/test_load_api.py @@ -2,11 +2,12 @@ from pathlib import Path import pytest import torch +from diffusers import AutoencoderTiny from invokeai.app.services.invocation_services import InvocationServices from invokeai.app.services.model_manager import ModelManagerServiceBase from invokeai.app.services.shared.invocation_context import InvocationContext, build_invocation_context -from invokeai.backend.model_manager.load.load_base import LoadedModel +from invokeai.backend.model_manager.load.load_base import LoadedModelWithoutConfig from tests.backend.model_manager.model_manager_fixtures import * # noqa F403 @@ -43,30 +44,34 @@ def test_load_from_path(mock_context: InvocationContext, embedding_file: Path) - "https://www.test.foo/download/test_embedding.safetensors" ) loaded_model_1 = mock_context.models.load_and_cache_model(downloaded_path) - assert isinstance(loaded_model_1, LoadedModel) + assert isinstance(loaded_model_1, LoadedModelWithoutConfig) loaded_model_2 = mock_context.models.load_and_cache_model(downloaded_path) - assert isinstance(loaded_model_2, LoadedModel) + assert isinstance(loaded_model_2, LoadedModelWithoutConfig) assert loaded_model_1.model is loaded_model_2.model loaded_model_3 = mock_context.models.load_and_cache_model(embedding_file) - assert isinstance(loaded_model_3, LoadedModel) + assert isinstance(loaded_model_3, LoadedModelWithoutConfig) assert loaded_model_1.model is not loaded_model_3.model assert isinstance(loaded_model_1.model, dict) assert isinstance(loaded_model_3.model, dict) assert torch.equal(loaded_model_1.model["emb_params"], loaded_model_3.model["emb_params"]) +def test_load_from_dir(mock_context: InvocationContext, vae_directory: Path) -> None: + loaded_model = mock_context.models.load_and_cache_model(vae_directory) + assert isinstance(loaded_model, LoadedModelWithoutConfig) + assert isinstance(loaded_model.model, AutoencoderTiny) def test_download_and_load(mock_context: InvocationContext) -> None: loaded_model_1 = mock_context.models.load_and_cache_model( "https://www.test.foo/download/test_embedding.safetensors" ) - assert isinstance(loaded_model_1, LoadedModel) + assert isinstance(loaded_model_1, LoadedModelWithoutConfig) loaded_model_2 = mock_context.models.load_and_cache_model( "https://www.test.foo/download/test_embedding.safetensors" ) - assert isinstance(loaded_model_2, LoadedModel) + assert isinstance(loaded_model_2, LoadedModelWithoutConfig) assert loaded_model_1.model is loaded_model_2.model # should be cached copy diff --git a/tests/backend/model_manager/model_manager_fixtures.py b/tests/backend/model_manager/model_manager_fixtures.py index dc2ad2f1e4..ee66c459b8 100644 --- a/tests/backend/model_manager/model_manager_fixtures.py +++ b/tests/backend/model_manager/model_manager_fixtures.py @@ -60,6 +60,10 @@ def mm2_model_files(tmp_path_factory) -> Path: def embedding_file(mm2_model_files: Path) -> Path: return mm2_model_files / "test_embedding.safetensors" +@pytest.fixture +def vae_directory(mm2_model_files: Path) -> Path: + return mm2_model_files / "taesdxl" + @pytest.fixture def diffusers_dir(mm2_model_files: Path) -> Path: From 9f9379682e63c2993df4207ad176d8c971768478 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Mon, 3 Jun 2024 20:33:31 -0400 Subject: [PATCH 073/110] ruff fixes --- tests/app/services/model_load/test_load_api.py | 2 ++ tests/backend/model_manager/model_manager_fixtures.py | 1 + 2 files changed, 3 insertions(+) diff --git a/tests/app/services/model_load/test_load_api.py b/tests/app/services/model_load/test_load_api.py index 9671c8c6c3..8dd948692d 100644 --- a/tests/app/services/model_load/test_load_api.py +++ b/tests/app/services/model_load/test_load_api.py @@ -57,11 +57,13 @@ def test_load_from_path(mock_context: InvocationContext, embedding_file: Path) - assert isinstance(loaded_model_3.model, dict) assert torch.equal(loaded_model_1.model["emb_params"], loaded_model_3.model["emb_params"]) + def test_load_from_dir(mock_context: InvocationContext, vae_directory: Path) -> None: loaded_model = mock_context.models.load_and_cache_model(vae_directory) assert isinstance(loaded_model, LoadedModelWithoutConfig) assert isinstance(loaded_model.model, AutoencoderTiny) + def test_download_and_load(mock_context: InvocationContext) -> None: loaded_model_1 = mock_context.models.load_and_cache_model( "https://www.test.foo/download/test_embedding.safetensors" diff --git a/tests/backend/model_manager/model_manager_fixtures.py b/tests/backend/model_manager/model_manager_fixtures.py index ee66c459b8..9ce272fc42 100644 --- a/tests/backend/model_manager/model_manager_fixtures.py +++ b/tests/backend/model_manager/model_manager_fixtures.py @@ -60,6 +60,7 @@ def mm2_model_files(tmp_path_factory) -> Path: def embedding_file(mm2_model_files: Path) -> Path: return mm2_model_files / "test_embedding.safetensors" + @pytest.fixture def vae_directory(mm2_model_files: Path) -> Path: return mm2_model_files / "taesdxl" From dc134935c8be752eabf61fb71a7802c736e0f3dc Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Thu, 6 Jun 2024 00:31:41 -0400 Subject: [PATCH 074/110] replace load_and_cache_model() with load_remote_model() and load_local_odel() --- docs/contributing/MODEL_MANAGER.md | 42 ++++++++++----- .../controlnet_image_processors.py | 2 +- invokeai/app/invocations/infill.py | 2 +- invokeai/app/invocations/upscale.py | 2 +- .../model_install/model_install_base.py | 4 +- .../model_install/model_install_default.py | 7 +-- .../services/model_load/model_load_base.py | 6 +-- .../services/model_load/model_load_default.py | 29 +++++------ .../app/services/shared/invocation_context.py | 52 ++++++++++++++----- .../migrations/migration_11.py | 4 +- .../app/services/model_load/test_load_api.py | 17 +++--- .../model_manager/model_manager_fixtures.py | 8 +-- 12 files changed, 106 insertions(+), 69 deletions(-) diff --git a/docs/contributing/MODEL_MANAGER.md b/docs/contributing/MODEL_MANAGER.md index fbc9079d49..dfa724fee8 100644 --- a/docs/contributing/MODEL_MANAGER.md +++ b/docs/contributing/MODEL_MANAGER.md @@ -1585,9 +1585,9 @@ Within invocations, the following methods are available from the ### context.download_and_cache_model(source) -> Path -This method accepts a `source` of a model, downloads and caches it -locally, and returns a Path to the local model. The source can be a -local file or directory, a URL, or a HuggingFace repo_id. +This method accepts a `source` of a remote model, downloads and caches +it locally, and then returns a Path to the local model. The source can +be a direct download URL or a HuggingFace repo_id. In the case of HuggingFace repo_id, the following variants are recognized: @@ -1602,16 +1602,34 @@ directory using this syntax: * stabilityai/stable-diffusion-v4::/checkpoints/sd4.safetensors -### context.load_and_cache_model(source, [loader]) -> LoadedModel +### context.load_local_model(model_path, [loader]) -> LoadedModel -This method takes a model source, downloads it, caches it, and then -loads it into the RAM cache for use in inference. The optional loader -is a Callable that accepts a Path to the object, and returns a -`Dict[str, torch.Tensor]`. If no loader is provided, then the method -will use `torch.load()` for a .ckpt or .bin checkpoint file, -`safetensors.torch.load_file()` for a safetensors checkpoint file, or -`*.from_pretrained()` for a directory that looks like a -diffusers directory. +This method loads a local model from the indicated path, returning a +`LoadedModel`. The optional loader is a Callable that accepts a Path +to the object, and returns a `AnyModel` object. If no loader is +provided, then the method will use `torch.load()` for a .ckpt or .bin +checkpoint file, `safetensors.torch.load_file()` for a safetensors +checkpoint file, or `cls.from_pretrained()` for a directory that looks +like a diffusers directory. + +### context.load_remote_model(source, [loader]) -> LoadedModel + +This method accepts a `source` of a remote model, downloads and caches +it locally, loads it, and returns a `LoadedModel`. The source can be a +direct download URL or a HuggingFace repo_id. + +In the case of HuggingFace repo_id, the following variants are +recognized: + +* stabilityai/stable-diffusion-v4 -- default model +* stabilityai/stable-diffusion-v4:fp16 -- fp16 variant +* stabilityai/stable-diffusion-v4:fp16:vae -- the fp16 vae subfolder +* stabilityai/stable-diffusion-v4:onnx:vae -- the onnx variant vae subfolder + +You can also point at an arbitrary individual file within a repo_id +directory using this syntax: + +* stabilityai/stable-diffusion-v4::/checkpoints/sd4.safetensors diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py index 1e4ad672bf..c0b332f27b 100644 --- a/invokeai/app/invocations/controlnet_image_processors.py +++ b/invokeai/app/invocations/controlnet_image_processors.py @@ -611,7 +611,7 @@ class DepthAnythingImageProcessorInvocation(ImageProcessorInvocation): model_path, model_size=self.model_size, device=TorchDevice.choose_torch_device() ) - with self._context.models.load_and_cache_model( + with self._context.models.load_remote_model( source=DEPTH_ANYTHING_MODELS[self.model_size], loader=loader ) as model: depth_anything_detector = DepthAnythingDetector(model, TorchDevice.choose_torch_device()) diff --git a/invokeai/app/invocations/infill.py b/invokeai/app/invocations/infill.py index f188ecf8f7..7e1a2ee322 100644 --- a/invokeai/app/invocations/infill.py +++ b/invokeai/app/invocations/infill.py @@ -134,7 +134,7 @@ class LaMaInfillInvocation(InfillImageProcessorInvocation): """Infills transparent areas of an image using the LaMa model""" def infill(self, image: Image.Image): - with self._context.models.load_and_cache_model( + with self._context.models.load_remote_model( source="https://github.com/Sanster/models/releases/download/add_big_lama/big-lama.pt", loader=LaMA.load_jit_model, ) as model: diff --git a/invokeai/app/invocations/upscale.py b/invokeai/app/invocations/upscale.py index 670082f120..f93060f8d3 100644 --- a/invokeai/app/invocations/upscale.py +++ b/invokeai/app/invocations/upscale.py @@ -91,7 +91,7 @@ class ESRGANInvocation(BaseInvocation, WithMetadata, WithBoard): context.logger.error(msg) raise ValueError(msg) - loadnet = context.models.load_and_cache_model( + loadnet = context.models.load_remote_model( source=ESRGAN_MODEL_URLS[self.model_name], ) diff --git a/invokeai/app/services/model_install/model_install_base.py b/invokeai/app/services/model_install/model_install_base.py index 734f05d574..20afaeaa50 100644 --- a/invokeai/app/services/model_install/model_install_base.py +++ b/invokeai/app/services/model_install/model_install_base.py @@ -5,6 +5,8 @@ from abc import ABC, abstractmethod from pathlib import Path from typing import Any, Dict, List, Optional, Union +from pydantic.networks import AnyHttpUrl + from invokeai.app.services.config import InvokeAIAppConfig from invokeai.app.services.download import DownloadQueueServiceBase from invokeai.app.services.events.events_base import EventServiceBase @@ -241,7 +243,7 @@ class ModelInstallServiceBase(ABC): """ @abstractmethod - def download_and_cache_model(self, source: str) -> Path: + def download_and_cache_model(self, source: str | AnyHttpUrl) -> Path: """ Download the model file located at source to the models cache and return its Path. diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py index de9bb8eed8..39e38a593f 100644 --- a/invokeai/app/services/model_install/model_install_default.py +++ b/invokeai/app/services/model_install/model_install_default.py @@ -15,6 +15,7 @@ import torch import yaml from huggingface_hub import HfFolder from pydantic.networks import AnyHttpUrl +from pydantic_core import Url from requests import Session from invokeai.app.services.config import InvokeAIAppConfig @@ -374,7 +375,7 @@ class ModelInstallService(ModelInstallServiceBase): def download_and_cache_model( self, - source: str, + source: str | AnyHttpUrl, ) -> Path: """Download the model file located at source to the models cache and return its Path.""" model_path = self._download_cache_path(str(source), self._app_config) @@ -388,7 +389,7 @@ class ModelInstallService(ModelInstallServiceBase): return contents[0] model_path.mkdir(parents=True, exist_ok=True) - model_source = self._guess_source(source) + model_source = self._guess_source(str(source)) remote_files, _ = self._remote_files_from_source(model_source) job = self._multifile_download( dest=model_path, @@ -447,7 +448,7 @@ class ModelInstallService(ModelInstallServiceBase): ) elif re.match(r"^https?://[^/]+", source): source_obj = URLModelSource( - url=AnyHttpUrl(source), + url=Url(source), ) else: raise ValueError(f"Unsupported model source: '{source}'") diff --git a/invokeai/app/services/model_load/model_load_base.py b/invokeai/app/services/model_load/model_load_base.py index f84b1dae13..da56772195 100644 --- a/invokeai/app/services/model_load/model_load_base.py +++ b/invokeai/app/services/model_load/model_load_base.py @@ -3,9 +3,7 @@ from abc import ABC, abstractmethod from pathlib import Path -from typing import Callable, Dict, Optional - -from torch import Tensor +from typing import Callable, Optional from invokeai.backend.model_manager import AnyModel, AnyModelConfig, SubModelType from invokeai.backend.model_manager.load import LoadedModel, LoadedModelWithoutConfig @@ -37,7 +35,7 @@ class ModelLoadServiceBase(ABC): @abstractmethod def load_model_from_path( - self, model_path: Path, loader: Optional[Callable[[Path], Dict[str, Tensor]]] = None + self, model_path: Path, loader: Optional[Callable[[Path], AnyModel]] = None ) -> LoadedModelWithoutConfig: """ Load the model file or directory located at the indicated Path. diff --git a/invokeai/app/services/model_load/model_load_default.py b/invokeai/app/services/model_load/model_load_default.py index 113334ea0d..7067481378 100644 --- a/invokeai/app/services/model_load/model_load_default.py +++ b/invokeai/app/services/model_load/model_load_default.py @@ -2,11 +2,10 @@ """Implementation of model loader service.""" from pathlib import Path -from typing import Callable, Dict, Optional, Type +from typing import Callable, Optional, Type from picklescan.scanner import scan_file_path from safetensors.torch import load_file as safetensors_load_file -from torch import Tensor from torch import load as torch_load from invokeai.app.services.config import InvokeAIAppConfig @@ -86,7 +85,7 @@ class ModelLoadService(ModelLoadServiceBase): return loaded_model def load_model_from_path( - self, model_path: Path, loader: Optional[Callable[[Path], Dict[str, Tensor] | AnyModel]] = None + self, model_path: Path, loader: Optional[Callable[[Path], AnyModel]] = None ) -> LoadedModelWithoutConfig: cache_key = str(model_path) ram_cache = self.ram_cache @@ -95,11 +94,11 @@ class ModelLoadService(ModelLoadServiceBase): except IndexError: pass - def torch_load_file(checkpoint: Path) -> Dict[str, Tensor]: + def torch_load_file(checkpoint: Path) -> AnyModel: scan_result = scan_file_path(checkpoint) if scan_result.infected_files != 0: raise Exception("The model at {checkpoint} is potentially infected by malware. Aborting load.") - result: Dict[str, Tensor] = torch_load(checkpoint, map_location="cpu") + result = torch_load(checkpoint, map_location="cpu") return result def diffusers_load_directory(directory: Path) -> AnyModel: @@ -109,18 +108,16 @@ class ModelLoadService(ModelLoadServiceBase): ram_cache=self._ram_cache, convert_cache=self.convert_cache, ).get_hf_load_class(directory) - result: AnyModel = load_class.from_pretrained(model_path, torch_dtype=TorchDevice.choose_torch_dtype()) - return result - - if loader is None: - loader = ( - diffusers_load_directory - if model_path.is_dir() - else torch_load_file - if model_path.suffix.endswith((".ckpt", ".pt", ".pth", ".bin")) - else lambda path: safetensors_load_file(path, device="cpu") - ) + return load_class.from_pretrained(model_path, torch_dtype=TorchDevice.choose_torch_dtype()) + loader = loader or ( + diffusers_load_directory + if model_path.is_dir() + else torch_load_file + if model_path.suffix.endswith((".ckpt", ".pt", ".pth", ".bin")) + else lambda path: safetensors_load_file(path, device="cpu") + ) + assert loader is not None raw_model = loader(model_path) ram_cache.put(key=cache_key, model=raw_model) return LoadedModelWithoutConfig(_locker=ram_cache.get(key=cache_key)) diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py index 931fc40b82..01662335e4 100644 --- a/invokeai/app/services/shared/invocation_context.py +++ b/invokeai/app/services/shared/invocation_context.py @@ -15,7 +15,14 @@ from invokeai.app.services.images.images_common import ImageDTO from invokeai.app.services.invocation_services import InvocationServices from invokeai.app.services.model_records.model_records_base import UnknownModelException from invokeai.app.util.step_callback import stable_diffusion_step_callback -from invokeai.backend.model_manager.config import AnyModelConfig, BaseModelType, ModelFormat, ModelType, SubModelType +from invokeai.backend.model_manager.config import ( + AnyModel, + AnyModelConfig, + BaseModelType, + ModelFormat, + ModelType, + SubModelType, +) from invokeai.backend.model_manager.load.load_base import LoadedModel, LoadedModelWithoutConfig from invokeai.backend.stable_diffusion.diffusers_pipeline import PipelineIntermediateState from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningFieldData @@ -449,21 +456,42 @@ class ModelsInterface(InvocationContextInterface): installed, the cached path will be returned. Otherwise it will be downloaded. Args: - source: A model path, URL or repo_id. + source: A URL that points to the model, or a huggingface repo_id. Returns: Path to the downloaded model """ - return self._services.model_manager.install.download_and_cache_model(source=source) - def load_and_cache_model( + def load_local_model( self, - source: Path | str | AnyHttpUrl, - loader: Optional[Callable[[Path], dict[str, Tensor]]] = None, + model_path: Path, + loader: Optional[Callable[[Path], AnyModel]] = None, ) -> LoadedModelWithoutConfig: """ - Download, cache, and load the model file located at the indicated URL. + Load the model file located at the indicated path + + If a loader callable is provided, it will be invoked to load the model. Otherwise, + `safetensors.torch.load_file()` or `torch.load()` will be called to load the model. + + Be aware that the LoadedModelWithoutConfig object has no `config` attribute + + Args: + path: A model Path + loader: A Callable that expects a Path and returns a dict[str|int, Any] + + Returns: + A LoadedModelWithoutConfig object. + """ + return self._services.model_manager.load.load_model_from_path(model_path=model_path, loader=loader) + + def load_remote_model( + self, + source: str | AnyHttpUrl, + loader: Optional[Callable[[Path], AnyModel]] = None, + ) -> LoadedModelWithoutConfig: + """ + Download, cache, and load the model file located at the indicated URL or repo_id. If the model is already downloaded, it will be loaded from the cache. @@ -473,18 +501,14 @@ class ModelsInterface(InvocationContextInterface): Be aware that the LoadedModelWithoutConfig object has no `config` attribute Args: - source: A model Path, URL, or repoid. + source: A URL or huggingface repoid. loader: A Callable that expects a Path and returns a dict[str|int, Any] Returns: A LoadedModelWithoutConfig object. """ - - if isinstance(source, Path): - return self._services.model_manager.load.load_model_from_path(model_path=source, loader=loader) - else: - model_path = self._services.model_manager.install.download_and_cache_model(source=str(source)) - return self._services.model_manager.load.load_model_from_path(model_path=model_path, loader=loader) + model_path = self._services.model_manager.install.download_and_cache_model(source=str(source)) + return self._services.model_manager.load.load_model_from_path(model_path=model_path, loader=loader) class ConfigInterface(InvocationContextInterface): diff --git a/invokeai/app/services/shared/sqlite_migrator/migrations/migration_11.py b/invokeai/app/services/shared/sqlite_migrator/migrations/migration_11.py index 3b616e2b82..f66374e0b1 100644 --- a/invokeai/app/services/shared/sqlite_migrator/migrations/migration_11.py +++ b/invokeai/app/services/shared/sqlite_migrator/migrations/migration_11.py @@ -59,14 +59,12 @@ class Migration11Callback: def build_migration_11(app_config: InvokeAIAppConfig, logger: Logger) -> Migration: """ - Build the migration from database version 9 to 10. + Build the migration from database version 10 to 11. This migration does the following: - Moves "core" models previously downloaded with download_with_progress_bar() into new "models/.download_cache" directory. - Renames "models/.cache" to "models/.convert_cache". - - Adds `error_type` and `error_message` columns to the session queue table. - - Renames the `error` column to `error_traceback`. """ migration_11 = Migration( from_version=10, diff --git a/tests/app/services/model_load/test_load_api.py b/tests/app/services/model_load/test_load_api.py index 8dd948692d..6f2c7bd931 100644 --- a/tests/app/services/model_load/test_load_api.py +++ b/tests/app/services/model_load/test_load_api.py @@ -43,14 +43,14 @@ def test_load_from_path(mock_context: InvocationContext, embedding_file: Path) - downloaded_path = mock_context.models.download_and_cache_model( "https://www.test.foo/download/test_embedding.safetensors" ) - loaded_model_1 = mock_context.models.load_and_cache_model(downloaded_path) + loaded_model_1 = mock_context.models.load_local_model(downloaded_path) assert isinstance(loaded_model_1, LoadedModelWithoutConfig) - loaded_model_2 = mock_context.models.load_and_cache_model(downloaded_path) + loaded_model_2 = mock_context.models.load_local_model(downloaded_path) assert isinstance(loaded_model_2, LoadedModelWithoutConfig) assert loaded_model_1.model is loaded_model_2.model - loaded_model_3 = mock_context.models.load_and_cache_model(embedding_file) + loaded_model_3 = mock_context.models.load_local_model(embedding_file) assert isinstance(loaded_model_3, LoadedModelWithoutConfig) assert loaded_model_1.model is not loaded_model_3.model assert isinstance(loaded_model_1.model, dict) @@ -58,21 +58,18 @@ def test_load_from_path(mock_context: InvocationContext, embedding_file: Path) - assert torch.equal(loaded_model_1.model["emb_params"], loaded_model_3.model["emb_params"]) +@pytest.mark.skip(reason="This requires a test model to load") def test_load_from_dir(mock_context: InvocationContext, vae_directory: Path) -> None: - loaded_model = mock_context.models.load_and_cache_model(vae_directory) + loaded_model = mock_context.models.load_local_model(vae_directory) assert isinstance(loaded_model, LoadedModelWithoutConfig) assert isinstance(loaded_model.model, AutoencoderTiny) def test_download_and_load(mock_context: InvocationContext) -> None: - loaded_model_1 = mock_context.models.load_and_cache_model( - "https://www.test.foo/download/test_embedding.safetensors" - ) + loaded_model_1 = mock_context.models.load_remote_model("https://www.test.foo/download/test_embedding.safetensors") assert isinstance(loaded_model_1, LoadedModelWithoutConfig) - loaded_model_2 = mock_context.models.load_and_cache_model( - "https://www.test.foo/download/test_embedding.safetensors" - ) + loaded_model_2 = mock_context.models.load_remote_model("https://www.test.foo/download/test_embedding.safetensors") assert isinstance(loaded_model_2, LoadedModelWithoutConfig) assert loaded_model_1.model is loaded_model_2.model # should be cached copy diff --git a/tests/backend/model_manager/model_manager_fixtures.py b/tests/backend/model_manager/model_manager_fixtures.py index 9ce272fc42..f82239298e 100644 --- a/tests/backend/model_manager/model_manager_fixtures.py +++ b/tests/backend/model_manager/model_manager_fixtures.py @@ -61,9 +61,11 @@ def embedding_file(mm2_model_files: Path) -> Path: return mm2_model_files / "test_embedding.safetensors" -@pytest.fixture -def vae_directory(mm2_model_files: Path) -> Path: - return mm2_model_files / "taesdxl" +# Can be used to test diffusers model directory loading, but +# the test file adds ~10MB of space. +# @pytest.fixture +# def vae_directory(mm2_model_files: Path) -> Path: +# return mm2_model_files / "taesdxl" @pytest.fixture From 0b37496c57abdc07b0c18e1d797df75d9a29d048 Mon Sep 17 00:00:00 2001 From: Ryan Dick Date: Wed, 5 Jun 2024 10:30:29 -0400 Subject: [PATCH 075/110] Move IdealSizeInvocation to its own file. No functional changes. --- invokeai/app/invocations/ideal_size.py | 65 ++++++++++++++++++++++++++ invokeai/app/invocations/latent.py | 56 ---------------------- 2 files changed, 65 insertions(+), 56 deletions(-) create mode 100644 invokeai/app/invocations/ideal_size.py diff --git a/invokeai/app/invocations/ideal_size.py b/invokeai/app/invocations/ideal_size.py new file mode 100644 index 0000000000..120f8c1ba0 --- /dev/null +++ b/invokeai/app/invocations/ideal_size.py @@ -0,0 +1,65 @@ +import math +from typing import Tuple + +from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output +from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR +from invokeai.app.invocations.fields import FieldDescriptions, InputField, OutputField +from invokeai.app.invocations.model import UNetField +from invokeai.app.services.shared.invocation_context import InvocationContext +from invokeai.backend.model_manager.config import BaseModelType + + +@invocation_output("ideal_size_output") +class IdealSizeOutput(BaseInvocationOutput): + """Base class for invocations that output an image""" + + width: int = OutputField(description="The ideal width of the image (in pixels)") + height: int = OutputField(description="The ideal height of the image (in pixels)") + + +@invocation( + "ideal_size", + title="Ideal Size", + tags=["latents", "math", "ideal_size"], + version="1.0.3", +) +class IdealSizeInvocation(BaseInvocation): + """Calculates the ideal size for generation to avoid duplication""" + + width: int = InputField(default=1024, description="Final image width") + height: int = InputField(default=576, description="Final image height") + unet: UNetField = InputField(default=None, description=FieldDescriptions.unet) + multiplier: float = InputField( + default=1.0, + description="Amount to multiply the model's dimensions by when calculating the ideal size (may result in " + "initial generation artifacts if too large)", + ) + + def trim_to_multiple_of(self, *args: int, multiple_of: int = LATENT_SCALE_FACTOR) -> Tuple[int, ...]: + return tuple((x - x % multiple_of) for x in args) + + def invoke(self, context: InvocationContext) -> IdealSizeOutput: + unet_config = context.models.get_config(self.unet.unet.key) + aspect = self.width / self.height + dimension: float = 512 + if unet_config.base == BaseModelType.StableDiffusion2: + dimension = 768 + elif unet_config.base == BaseModelType.StableDiffusionXL: + dimension = 1024 + dimension = dimension * self.multiplier + min_dimension = math.floor(dimension * 0.5) + model_area = dimension * dimension # hardcoded for now since all models are trained on square images + + if aspect > 1.0: + init_height = max(min_dimension, math.sqrt(model_area / aspect)) + init_width = init_height * aspect + else: + init_width = max(min_dimension, math.sqrt(model_area * aspect)) + init_height = init_width / aspect + + scaled_width, scaled_height = self.trim_to_multiple_of( + math.floor(init_width), + math.floor(init_height), + ) + + return IdealSizeOutput(width=scaled_width, height=scaled_height) diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index 8fb9b93f4c..6bb5b6882f 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -1,6 +1,5 @@ # Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654) import inspect -import math from contextlib import ExitStack from functools import singledispatchmethod from typing import Any, Dict, Iterator, List, Literal, Optional, Tuple, Union @@ -1448,58 +1447,3 @@ class CropLatentsCoreInvocation(BaseInvocation): name = context.tensors.save(tensor=cropped_latents) return LatentsOutput.build(latents_name=name, latents=cropped_latents) - - -@invocation_output("ideal_size_output") -class IdealSizeOutput(BaseInvocationOutput): - """Base class for invocations that output an image""" - - width: int = OutputField(description="The ideal width of the image (in pixels)") - height: int = OutputField(description="The ideal height of the image (in pixels)") - - -@invocation( - "ideal_size", - title="Ideal Size", - tags=["latents", "math", "ideal_size"], - version="1.0.3", -) -class IdealSizeInvocation(BaseInvocation): - """Calculates the ideal size for generation to avoid duplication""" - - width: int = InputField(default=1024, description="Final image width") - height: int = InputField(default=576, description="Final image height") - unet: UNetField = InputField(default=None, description=FieldDescriptions.unet) - multiplier: float = InputField( - default=1.0, - description="Amount to multiply the model's dimensions by when calculating the ideal size (may result in initial generation artifacts if too large)", - ) - - def trim_to_multiple_of(self, *args: int, multiple_of: int = LATENT_SCALE_FACTOR) -> Tuple[int, ...]: - return tuple((x - x % multiple_of) for x in args) - - def invoke(self, context: InvocationContext) -> IdealSizeOutput: - unet_config = context.models.get_config(self.unet.unet.key) - aspect = self.width / self.height - dimension: float = 512 - if unet_config.base == BaseModelType.StableDiffusion2: - dimension = 768 - elif unet_config.base == BaseModelType.StableDiffusionXL: - dimension = 1024 - dimension = dimension * self.multiplier - min_dimension = math.floor(dimension * 0.5) - model_area = dimension * dimension # hardcoded for now since all models are trained on square images - - if aspect > 1.0: - init_height = max(min_dimension, math.sqrt(model_area / aspect)) - init_width = init_height * aspect - else: - init_width = max(min_dimension, math.sqrt(model_area * aspect)) - init_height = init_width / aspect - - scaled_width, scaled_height = self.trim_to_multiple_of( - math.floor(init_width), - math.floor(init_height), - ) - - return IdealSizeOutput(width=scaled_width, height=scaled_height) From ed03d281e683ad6a9fdf373679008b7c6ec805f5 Mon Sep 17 00:00:00 2001 From: Ryan Dick Date: Wed, 5 Jun 2024 10:53:24 -0400 Subject: [PATCH 076/110] Move CropLatentsCoreInvocation to its own file. No functional changes. --- invokeai/app/invocations/crop_latents.py | 61 ++++++++++++++++++++++++ invokeai/app/invocations/latent.py | 56 ---------------------- 2 files changed, 61 insertions(+), 56 deletions(-) create mode 100644 invokeai/app/invocations/crop_latents.py diff --git a/invokeai/app/invocations/crop_latents.py b/invokeai/app/invocations/crop_latents.py new file mode 100644 index 0000000000..258049fd2c --- /dev/null +++ b/invokeai/app/invocations/crop_latents.py @@ -0,0 +1,61 @@ +from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation +from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR +from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, LatentsField +from invokeai.app.invocations.primitives import LatentsOutput +from invokeai.app.services.shared.invocation_context import InvocationContext + + +# The Crop Latents node was copied from @skunkworxdark's implementation here: +# https://github.com/skunkworxdark/XYGrid_nodes/blob/74647fa9c1fa57d317a94bd43ca689af7f0aae5e/images_to_grids.py#L1117C1-L1167C80 +@invocation( + "crop_latents", + title="Crop Latents", + tags=["latents", "crop"], + category="latents", + version="1.0.2", +) +# TODO(ryand): Named `CropLatentsCoreInvocation` to prevent a conflict with custom node `CropLatentsInvocation`. +# Currently, if the class names conflict then 'GET /openapi.json' fails. +class CropLatentsCoreInvocation(BaseInvocation): + """Crops a latent-space tensor to a box specified in image-space. The box dimensions and coordinates must be + divisible by the latent scale factor of 8. + """ + + latents: LatentsField = InputField( + description=FieldDescriptions.latents, + input=Input.Connection, + ) + x: int = InputField( + ge=0, + multiple_of=LATENT_SCALE_FACTOR, + description="The left x coordinate (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.", + ) + y: int = InputField( + ge=0, + multiple_of=LATENT_SCALE_FACTOR, + description="The top y coordinate (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.", + ) + width: int = InputField( + ge=1, + multiple_of=LATENT_SCALE_FACTOR, + description="The width (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.", + ) + height: int = InputField( + ge=1, + multiple_of=LATENT_SCALE_FACTOR, + description="The height (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.", + ) + + def invoke(self, context: InvocationContext) -> LatentsOutput: + latents = context.tensors.load(self.latents.latents_name) + + x1 = self.x // LATENT_SCALE_FACTOR + y1 = self.y // LATENT_SCALE_FACTOR + x2 = x1 + (self.width // LATENT_SCALE_FACTOR) + y2 = y1 + (self.height // LATENT_SCALE_FACTOR) + + cropped_latents = latents[..., y1:y2, x1:x2] + + name = context.tensors.save(tensor=cropped_latents) + + return LatentsOutput.build(latents_name=name, latents=cropped_latents) diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index 6bb5b6882f..747e0ddc65 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -1391,59 +1391,3 @@ class BlendLatentsInvocation(BaseInvocation): name = context.tensors.save(tensor=blended_latents) return LatentsOutput.build(latents_name=name, latents=blended_latents, seed=self.latents_a.seed) - - -# The Crop Latents node was copied from @skunkworxdark's implementation here: -# https://github.com/skunkworxdark/XYGrid_nodes/blob/74647fa9c1fa57d317a94bd43ca689af7f0aae5e/images_to_grids.py#L1117C1-L1167C80 -@invocation( - "crop_latents", - title="Crop Latents", - tags=["latents", "crop"], - category="latents", - version="1.0.2", -) -# TODO(ryand): Named `CropLatentsCoreInvocation` to prevent a conflict with custom node `CropLatentsInvocation`. -# Currently, if the class names conflict then 'GET /openapi.json' fails. -class CropLatentsCoreInvocation(BaseInvocation): - """Crops a latent-space tensor to a box specified in image-space. The box dimensions and coordinates must be - divisible by the latent scale factor of 8. - """ - - latents: LatentsField = InputField( - description=FieldDescriptions.latents, - input=Input.Connection, - ) - x: int = InputField( - ge=0, - multiple_of=LATENT_SCALE_FACTOR, - description="The left x coordinate (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.", - ) - y: int = InputField( - ge=0, - multiple_of=LATENT_SCALE_FACTOR, - description="The top y coordinate (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.", - ) - width: int = InputField( - ge=1, - multiple_of=LATENT_SCALE_FACTOR, - description="The width (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.", - ) - height: int = InputField( - ge=1, - multiple_of=LATENT_SCALE_FACTOR, - description="The height (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.", - ) - - def invoke(self, context: InvocationContext) -> LatentsOutput: - latents = context.tensors.load(self.latents.latents_name) - - x1 = self.x // LATENT_SCALE_FACTOR - y1 = self.y // LATENT_SCALE_FACTOR - x2 = x1 + (self.width // LATENT_SCALE_FACTOR) - y2 = y1 + (self.height // LATENT_SCALE_FACTOR) - - cropped_latents = latents[..., y1:y2, x1:x2] - - name = context.tensors.save(tensor=cropped_latents) - - return LatentsOutput.build(latents_name=name, latents=cropped_latents) From 595096bdcf07c343e566ccdcece7431c896ce916 Mon Sep 17 00:00:00 2001 From: Ryan Dick Date: Wed, 5 Jun 2024 11:04:17 -0400 Subject: [PATCH 077/110] Move BlendLatentsInvocation to its own file. No functional changes. --- invokeai/app/invocations/blend_latents.py | 98 +++++++++++++++++++++++ invokeai/app/invocations/latent.py | 88 -------------------- 2 files changed, 98 insertions(+), 88 deletions(-) create mode 100644 invokeai/app/invocations/blend_latents.py diff --git a/invokeai/app/invocations/blend_latents.py b/invokeai/app/invocations/blend_latents.py new file mode 100644 index 0000000000..9238f4b34c --- /dev/null +++ b/invokeai/app/invocations/blend_latents.py @@ -0,0 +1,98 @@ +from typing import Any, Union + +import numpy as np +import numpy.typing as npt +import torch + +from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation +from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, LatentsField +from invokeai.app.invocations.primitives import LatentsOutput +from invokeai.app.services.shared.invocation_context import InvocationContext +from invokeai.backend.util.devices import TorchDevice + + +@invocation( + "lblend", + title="Blend Latents", + tags=["latents", "blend"], + category="latents", + version="1.0.3", +) +class BlendLatentsInvocation(BaseInvocation): + """Blend two latents using a given alpha. Latents must have same size.""" + + latents_a: LatentsField = InputField( + description=FieldDescriptions.latents, + input=Input.Connection, + ) + latents_b: LatentsField = InputField( + description=FieldDescriptions.latents, + input=Input.Connection, + ) + alpha: float = InputField(default=0.5, description=FieldDescriptions.blend_alpha) + + def invoke(self, context: InvocationContext) -> LatentsOutput: + latents_a = context.tensors.load(self.latents_a.latents_name) + latents_b = context.tensors.load(self.latents_b.latents_name) + + if latents_a.shape != latents_b.shape: + raise Exception("Latents to blend must be the same size.") + + device = TorchDevice.choose_torch_device() + + def slerp( + t: Union[float, npt.NDArray[Any]], # FIXME: maybe use np.float32 here? + v0: Union[torch.Tensor, npt.NDArray[Any]], + v1: Union[torch.Tensor, npt.NDArray[Any]], + DOT_THRESHOLD: float = 0.9995, + ) -> Union[torch.Tensor, npt.NDArray[Any]]: + """ + Spherical linear interpolation + Args: + t (float/np.ndarray): Float value between 0.0 and 1.0 + v0 (np.ndarray): Starting vector + v1 (np.ndarray): Final vector + DOT_THRESHOLD (float): Threshold for considering the two vectors as + colineal. Not recommended to alter this. + Returns: + v2 (np.ndarray): Interpolation vector between v0 and v1 + """ + inputs_are_torch = False + if not isinstance(v0, np.ndarray): + inputs_are_torch = True + v0 = v0.detach().cpu().numpy() + if not isinstance(v1, np.ndarray): + inputs_are_torch = True + v1 = v1.detach().cpu().numpy() + + dot = np.sum(v0 * v1 / (np.linalg.norm(v0) * np.linalg.norm(v1))) + if np.abs(dot) > DOT_THRESHOLD: + v2 = (1 - t) * v0 + t * v1 + else: + theta_0 = np.arccos(dot) + sin_theta_0 = np.sin(theta_0) + theta_t = theta_0 * t + sin_theta_t = np.sin(theta_t) + s0 = np.sin(theta_0 - theta_t) / sin_theta_0 + s1 = sin_theta_t / sin_theta_0 + v2 = s0 * v0 + s1 * v1 + + if inputs_are_torch: + v2_torch: torch.Tensor = torch.from_numpy(v2).to(device) + return v2_torch + else: + assert isinstance(v2, np.ndarray) + return v2 + + # blend + bl = slerp(self.alpha, latents_a, latents_b) + assert isinstance(bl, torch.Tensor) + blended_latents: torch.Tensor = bl # for type checking convenience + + # https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699 + blended_latents = blended_latents.to("cpu") + + TorchDevice.empty_cache() + + name = context.tensors.save(tensor=blended_latents) + return LatentsOutput.build(latents_name=name, latents=blended_latents, seed=self.latents_a.seed) diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index 747e0ddc65..240a52517b 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -6,7 +6,6 @@ from typing import Any, Dict, Iterator, List, Literal, Optional, Tuple, Union import einops import numpy as np -import numpy.typing as npt import torch import torchvision import torchvision.transforms as T @@ -1304,90 +1303,3 @@ class ImageToLatentsInvocation(BaseInvocation): assert isinstance(vae, torch.nn.Module) latents: torch.FloatTensor = vae.encode(image_tensor).latents return latents - - -@invocation( - "lblend", - title="Blend Latents", - tags=["latents", "blend"], - category="latents", - version="1.0.3", -) -class BlendLatentsInvocation(BaseInvocation): - """Blend two latents using a given alpha. Latents must have same size.""" - - latents_a: LatentsField = InputField( - description=FieldDescriptions.latents, - input=Input.Connection, - ) - latents_b: LatentsField = InputField( - description=FieldDescriptions.latents, - input=Input.Connection, - ) - alpha: float = InputField(default=0.5, description=FieldDescriptions.blend_alpha) - - def invoke(self, context: InvocationContext) -> LatentsOutput: - latents_a = context.tensors.load(self.latents_a.latents_name) - latents_b = context.tensors.load(self.latents_b.latents_name) - - if latents_a.shape != latents_b.shape: - raise Exception("Latents to blend must be the same size.") - - device = TorchDevice.choose_torch_device() - - def slerp( - t: Union[float, npt.NDArray[Any]], # FIXME: maybe use np.float32 here? - v0: Union[torch.Tensor, npt.NDArray[Any]], - v1: Union[torch.Tensor, npt.NDArray[Any]], - DOT_THRESHOLD: float = 0.9995, - ) -> Union[torch.Tensor, npt.NDArray[Any]]: - """ - Spherical linear interpolation - Args: - t (float/np.ndarray): Float value between 0.0 and 1.0 - v0 (np.ndarray): Starting vector - v1 (np.ndarray): Final vector - DOT_THRESHOLD (float): Threshold for considering the two vectors as - colineal. Not recommended to alter this. - Returns: - v2 (np.ndarray): Interpolation vector between v0 and v1 - """ - inputs_are_torch = False - if not isinstance(v0, np.ndarray): - inputs_are_torch = True - v0 = v0.detach().cpu().numpy() - if not isinstance(v1, np.ndarray): - inputs_are_torch = True - v1 = v1.detach().cpu().numpy() - - dot = np.sum(v0 * v1 / (np.linalg.norm(v0) * np.linalg.norm(v1))) - if np.abs(dot) > DOT_THRESHOLD: - v2 = (1 - t) * v0 + t * v1 - else: - theta_0 = np.arccos(dot) - sin_theta_0 = np.sin(theta_0) - theta_t = theta_0 * t - sin_theta_t = np.sin(theta_t) - s0 = np.sin(theta_0 - theta_t) / sin_theta_0 - s1 = sin_theta_t / sin_theta_0 - v2 = s0 * v0 + s1 * v1 - - if inputs_are_torch: - v2_torch: torch.Tensor = torch.from_numpy(v2).to(device) - return v2_torch - else: - assert isinstance(v2, np.ndarray) - return v2 - - # blend - bl = slerp(self.alpha, latents_a, latents_b) - assert isinstance(bl, torch.Tensor) - blended_latents: torch.Tensor = bl # for type checking convenience - - # https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699 - blended_latents = blended_latents.to("cpu") - - TorchDevice.empty_cache() - - name = context.tensors.save(tensor=blended_latents) - return LatentsOutput.build(latents_name=name, latents=blended_latents, seed=self.latents_a.seed) From 5e419dbb562b6bedaffeeb44b7d302747c81f135 Mon Sep 17 00:00:00 2001 From: Ryan Dick Date: Wed, 5 Jun 2024 11:05:44 -0400 Subject: [PATCH 078/110] Move ScaleLatentsInvocation and ResizeLatentsInvocation to their own file. No functional changes. --- invokeai/app/invocations/latent.py | 89 ------------------ invokeai/app/invocations/resize_latents.py | 103 +++++++++++++++++++++ 2 files changed, 103 insertions(+), 89 deletions(-) create mode 100644 invokeai/app/invocations/resize_latents.py diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index 240a52517b..79d23199c5 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -1117,95 +1117,6 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard): return ImageOutput.build(image_dto) -LATENTS_INTERPOLATION_MODE = Literal["nearest", "linear", "bilinear", "bicubic", "trilinear", "area", "nearest-exact"] - - -@invocation( - "lresize", - title="Resize Latents", - tags=["latents", "resize"], - category="latents", - version="1.0.2", -) -class ResizeLatentsInvocation(BaseInvocation): - """Resizes latents to explicit width/height (in pixels). Provided dimensions are floor-divided by 8.""" - - latents: LatentsField = InputField( - description=FieldDescriptions.latents, - input=Input.Connection, - ) - width: int = InputField( - ge=64, - multiple_of=LATENT_SCALE_FACTOR, - description=FieldDescriptions.width, - ) - height: int = InputField( - ge=64, - multiple_of=LATENT_SCALE_FACTOR, - description=FieldDescriptions.width, - ) - mode: LATENTS_INTERPOLATION_MODE = InputField(default="bilinear", description=FieldDescriptions.interp_mode) - antialias: bool = InputField(default=False, description=FieldDescriptions.torch_antialias) - - def invoke(self, context: InvocationContext) -> LatentsOutput: - latents = context.tensors.load(self.latents.latents_name) - device = TorchDevice.choose_torch_device() - - resized_latents = torch.nn.functional.interpolate( - latents.to(device), - size=(self.height // LATENT_SCALE_FACTOR, self.width // LATENT_SCALE_FACTOR), - mode=self.mode, - antialias=self.antialias if self.mode in ["bilinear", "bicubic"] else False, - ) - - # https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699 - resized_latents = resized_latents.to("cpu") - - TorchDevice.empty_cache() - - name = context.tensors.save(tensor=resized_latents) - return LatentsOutput.build(latents_name=name, latents=resized_latents, seed=self.latents.seed) - - -@invocation( - "lscale", - title="Scale Latents", - tags=["latents", "resize"], - category="latents", - version="1.0.2", -) -class ScaleLatentsInvocation(BaseInvocation): - """Scales latents by a given factor.""" - - latents: LatentsField = InputField( - description=FieldDescriptions.latents, - input=Input.Connection, - ) - scale_factor: float = InputField(gt=0, description=FieldDescriptions.scale_factor) - mode: LATENTS_INTERPOLATION_MODE = InputField(default="bilinear", description=FieldDescriptions.interp_mode) - antialias: bool = InputField(default=False, description=FieldDescriptions.torch_antialias) - - def invoke(self, context: InvocationContext) -> LatentsOutput: - latents = context.tensors.load(self.latents.latents_name) - - device = TorchDevice.choose_torch_device() - - # resizing - resized_latents = torch.nn.functional.interpolate( - latents.to(device), - scale_factor=self.scale_factor, - mode=self.mode, - antialias=self.antialias if self.mode in ["bilinear", "bicubic"] else False, - ) - - # https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699 - resized_latents = resized_latents.to("cpu") - TorchDevice.empty_cache() - - name = context.tensors.save(tensor=resized_latents) - return LatentsOutput.build(latents_name=name, latents=resized_latents, seed=self.latents.seed) - - @invocation( "i2l", title="Image to Latents", diff --git a/invokeai/app/invocations/resize_latents.py b/invokeai/app/invocations/resize_latents.py new file mode 100644 index 0000000000..90253e52e8 --- /dev/null +++ b/invokeai/app/invocations/resize_latents.py @@ -0,0 +1,103 @@ +from typing import Literal + +import torch + +from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation +from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR +from invokeai.app.invocations.fields import ( + FieldDescriptions, + Input, + InputField, + LatentsField, +) +from invokeai.app.invocations.primitives import LatentsOutput +from invokeai.app.services.shared.invocation_context import InvocationContext +from invokeai.backend.util.devices import TorchDevice + +LATENTS_INTERPOLATION_MODE = Literal["nearest", "linear", "bilinear", "bicubic", "trilinear", "area", "nearest-exact"] + + +@invocation( + "lresize", + title="Resize Latents", + tags=["latents", "resize"], + category="latents", + version="1.0.2", +) +class ResizeLatentsInvocation(BaseInvocation): + """Resizes latents to explicit width/height (in pixels). Provided dimensions are floor-divided by 8.""" + + latents: LatentsField = InputField( + description=FieldDescriptions.latents, + input=Input.Connection, + ) + width: int = InputField( + ge=64, + multiple_of=LATENT_SCALE_FACTOR, + description=FieldDescriptions.width, + ) + height: int = InputField( + ge=64, + multiple_of=LATENT_SCALE_FACTOR, + description=FieldDescriptions.width, + ) + mode: LATENTS_INTERPOLATION_MODE = InputField(default="bilinear", description=FieldDescriptions.interp_mode) + antialias: bool = InputField(default=False, description=FieldDescriptions.torch_antialias) + + def invoke(self, context: InvocationContext) -> LatentsOutput: + latents = context.tensors.load(self.latents.latents_name) + device = TorchDevice.choose_torch_device() + + resized_latents = torch.nn.functional.interpolate( + latents.to(device), + size=(self.height // LATENT_SCALE_FACTOR, self.width // LATENT_SCALE_FACTOR), + mode=self.mode, + antialias=self.antialias if self.mode in ["bilinear", "bicubic"] else False, + ) + + # https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699 + resized_latents = resized_latents.to("cpu") + + TorchDevice.empty_cache() + + name = context.tensors.save(tensor=resized_latents) + return LatentsOutput.build(latents_name=name, latents=resized_latents, seed=self.latents.seed) + + +@invocation( + "lscale", + title="Scale Latents", + tags=["latents", "resize"], + category="latents", + version="1.0.2", +) +class ScaleLatentsInvocation(BaseInvocation): + """Scales latents by a given factor.""" + + latents: LatentsField = InputField( + description=FieldDescriptions.latents, + input=Input.Connection, + ) + scale_factor: float = InputField(gt=0, description=FieldDescriptions.scale_factor) + mode: LATENTS_INTERPOLATION_MODE = InputField(default="bilinear", description=FieldDescriptions.interp_mode) + antialias: bool = InputField(default=False, description=FieldDescriptions.torch_antialias) + + def invoke(self, context: InvocationContext) -> LatentsOutput: + latents = context.tensors.load(self.latents.latents_name) + + device = TorchDevice.choose_torch_device() + + # resizing + resized_latents = torch.nn.functional.interpolate( + latents.to(device), + scale_factor=self.scale_factor, + mode=self.mode, + antialias=self.antialias if self.mode in ["bilinear", "bicubic"] else False, + ) + + # https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699 + resized_latents = resized_latents.to("cpu") + TorchDevice.empty_cache() + + name = context.tensors.save(tensor=resized_latents) + return LatentsOutput.build(latents_name=name, latents=resized_latents, seed=self.latents.seed) From 58697141bfe57a7a293cc4c1dd8d20b116be3fa3 Mon Sep 17 00:00:00 2001 From: Ryan Dick Date: Wed, 5 Jun 2024 13:47:38 -0400 Subject: [PATCH 079/110] Move ImageToLatentsInvocation to its own file. No functional changes. --- invokeai/app/invocations/image_to_latents.py | 125 +++++++++++++++++++ invokeai/app/invocations/latent.py | 101 --------------- 2 files changed, 125 insertions(+), 101 deletions(-) create mode 100644 invokeai/app/invocations/image_to_latents.py diff --git a/invokeai/app/invocations/image_to_latents.py b/invokeai/app/invocations/image_to_latents.py new file mode 100644 index 0000000000..53c64d8b4e --- /dev/null +++ b/invokeai/app/invocations/image_to_latents.py @@ -0,0 +1,125 @@ +from functools import singledispatchmethod + +import einops +import torch +from diffusers.models.attention_processor import ( + AttnProcessor2_0, + LoRAAttnProcessor2_0, + LoRAXFormersAttnProcessor, + XFormersAttnProcessor, +) +from diffusers.models.autoencoders.autoencoder_kl import AutoencoderKL +from diffusers.models.autoencoders.autoencoder_tiny import AutoencoderTiny + +from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation +from invokeai.app.invocations.fields import ( + FieldDescriptions, + ImageField, + Input, + InputField, +) +from invokeai.app.invocations.latent import DEFAULT_PRECISION +from invokeai.app.invocations.model import VAEField +from invokeai.app.invocations.primitives import LatentsOutput +from invokeai.app.services.shared.invocation_context import InvocationContext +from invokeai.backend.model_manager import LoadedModel +from invokeai.backend.stable_diffusion.diffusers_pipeline import image_resized_to_grid_as_tensor + + +@invocation( + "i2l", + title="Image to Latents", + tags=["latents", "image", "vae", "i2l"], + category="latents", + version="1.0.2", +) +class ImageToLatentsInvocation(BaseInvocation): + """Encodes an image into latents.""" + + image: ImageField = InputField( + description="The image to encode", + ) + vae: VAEField = InputField( + description=FieldDescriptions.vae, + input=Input.Connection, + ) + tiled: bool = InputField(default=False, description=FieldDescriptions.tiled) + fp32: bool = InputField(default=DEFAULT_PRECISION == "float32", description=FieldDescriptions.fp32) + + @staticmethod + def vae_encode(vae_info: LoadedModel, upcast: bool, tiled: bool, image_tensor: torch.Tensor) -> torch.Tensor: + with vae_info as vae: + assert isinstance(vae, torch.nn.Module) + orig_dtype = vae.dtype + if upcast: + vae.to(dtype=torch.float32) + + use_torch_2_0_or_xformers = hasattr(vae.decoder, "mid_block") and isinstance( + vae.decoder.mid_block.attentions[0].processor, + ( + AttnProcessor2_0, + XFormersAttnProcessor, + LoRAXFormersAttnProcessor, + LoRAAttnProcessor2_0, + ), + ) + # if xformers or torch_2_0 is used attention block does not need + # to be in float32 which can save lots of memory + if use_torch_2_0_or_xformers: + vae.post_quant_conv.to(orig_dtype) + vae.decoder.conv_in.to(orig_dtype) + vae.decoder.mid_block.to(orig_dtype) + # else: + # latents = latents.float() + + else: + vae.to(dtype=torch.float16) + # latents = latents.half() + + if tiled: + vae.enable_tiling() + else: + vae.disable_tiling() + + # non_noised_latents_from_image + image_tensor = image_tensor.to(device=vae.device, dtype=vae.dtype) + with torch.inference_mode(): + latents = ImageToLatentsInvocation._encode_to_tensor(vae, image_tensor) + + latents = vae.config.scaling_factor * latents + latents = latents.to(dtype=orig_dtype) + + return latents + + @torch.no_grad() + def invoke(self, context: InvocationContext) -> LatentsOutput: + image = context.images.get_pil(self.image.image_name) + + vae_info = context.models.load(self.vae.vae) + + image_tensor = image_resized_to_grid_as_tensor(image.convert("RGB")) + if image_tensor.dim() == 3: + image_tensor = einops.rearrange(image_tensor, "c h w -> 1 c h w") + + latents = self.vae_encode(vae_info, self.fp32, self.tiled, image_tensor) + + latents = latents.to("cpu") + name = context.tensors.save(tensor=latents) + return LatentsOutput.build(latents_name=name, latents=latents, seed=None) + + @singledispatchmethod + @staticmethod + def _encode_to_tensor(vae: AutoencoderKL, image_tensor: torch.FloatTensor) -> torch.FloatTensor: + assert isinstance(vae, torch.nn.Module) + image_tensor_dist = vae.encode(image_tensor).latent_dist + latents: torch.Tensor = image_tensor_dist.sample().to( + dtype=vae.dtype + ) # FIXME: uses torch.randn. make reproducible! + return latents + + @_encode_to_tensor.register + @staticmethod + def _(vae: AutoencoderTiny, image_tensor: torch.FloatTensor) -> torch.FloatTensor: + assert isinstance(vae, torch.nn.Module) + latents: torch.FloatTensor = vae.encode(image_tensor).latents + return latents diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index 79d23199c5..c41dca195e 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -1,10 +1,8 @@ # Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654) import inspect from contextlib import ExitStack -from functools import singledispatchmethod from typing import Any, Dict, Iterator, List, Literal, Optional, Tuple, Union -import einops import numpy as np import torch import torchvision @@ -1115,102 +1113,3 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard): image_dto = context.images.save(image=image) return ImageOutput.build(image_dto) - - -@invocation( - "i2l", - title="Image to Latents", - tags=["latents", "image", "vae", "i2l"], - category="latents", - version="1.0.2", -) -class ImageToLatentsInvocation(BaseInvocation): - """Encodes an image into latents.""" - - image: ImageField = InputField( - description="The image to encode", - ) - vae: VAEField = InputField( - description=FieldDescriptions.vae, - input=Input.Connection, - ) - tiled: bool = InputField(default=False, description=FieldDescriptions.tiled) - fp32: bool = InputField(default=DEFAULT_PRECISION == "float32", description=FieldDescriptions.fp32) - - @staticmethod - def vae_encode(vae_info: LoadedModel, upcast: bool, tiled: bool, image_tensor: torch.Tensor) -> torch.Tensor: - with vae_info as vae: - assert isinstance(vae, torch.nn.Module) - orig_dtype = vae.dtype - if upcast: - vae.to(dtype=torch.float32) - - use_torch_2_0_or_xformers = hasattr(vae.decoder, "mid_block") and isinstance( - vae.decoder.mid_block.attentions[0].processor, - ( - AttnProcessor2_0, - XFormersAttnProcessor, - LoRAXFormersAttnProcessor, - LoRAAttnProcessor2_0, - ), - ) - # if xformers or torch_2_0 is used attention block does not need - # to be in float32 which can save lots of memory - if use_torch_2_0_or_xformers: - vae.post_quant_conv.to(orig_dtype) - vae.decoder.conv_in.to(orig_dtype) - vae.decoder.mid_block.to(orig_dtype) - # else: - # latents = latents.float() - - else: - vae.to(dtype=torch.float16) - # latents = latents.half() - - if tiled: - vae.enable_tiling() - else: - vae.disable_tiling() - - # non_noised_latents_from_image - image_tensor = image_tensor.to(device=vae.device, dtype=vae.dtype) - with torch.inference_mode(): - latents = ImageToLatentsInvocation._encode_to_tensor(vae, image_tensor) - - latents = vae.config.scaling_factor * latents - latents = latents.to(dtype=orig_dtype) - - return latents - - @torch.no_grad() - def invoke(self, context: InvocationContext) -> LatentsOutput: - image = context.images.get_pil(self.image.image_name) - - vae_info = context.models.load(self.vae.vae) - - image_tensor = image_resized_to_grid_as_tensor(image.convert("RGB")) - if image_tensor.dim() == 3: - image_tensor = einops.rearrange(image_tensor, "c h w -> 1 c h w") - - latents = self.vae_encode(vae_info, self.fp32, self.tiled, image_tensor) - - latents = latents.to("cpu") - name = context.tensors.save(tensor=latents) - return LatentsOutput.build(latents_name=name, latents=latents, seed=None) - - @singledispatchmethod - @staticmethod - def _encode_to_tensor(vae: AutoencoderKL, image_tensor: torch.FloatTensor) -> torch.FloatTensor: - assert isinstance(vae, torch.nn.Module) - image_tensor_dist = vae.encode(image_tensor).latent_dist - latents: torch.Tensor = image_tensor_dist.sample().to( - dtype=vae.dtype - ) # FIXME: uses torch.randn. make reproducible! - return latents - - @_encode_to_tensor.register - @staticmethod - def _(vae: AutoencoderTiny, image_tensor: torch.FloatTensor) -> torch.FloatTensor: - assert isinstance(vae, torch.nn.Module) - latents: torch.FloatTensor = vae.encode(image_tensor).latents - return latents From 045caddee134d358f0f4f1b1f95b67ac56520879 Mon Sep 17 00:00:00 2001 From: Ryan Dick Date: Wed, 5 Jun 2024 13:53:53 -0400 Subject: [PATCH 080/110] Move LatentsToImageInvocation to its own file. No functional changes. --- invokeai/app/invocations/latent.py | 93 +--------------- invokeai/app/invocations/latents_to_image.py | 107 +++++++++++++++++++ 2 files changed, 108 insertions(+), 92 deletions(-) create mode 100644 invokeai/app/invocations/latents_to_image.py diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index c41dca195e..7102a0a4eb 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -8,16 +8,7 @@ import torch import torchvision import torchvision.transforms as T from diffusers.configuration_utils import ConfigMixin -from diffusers.image_processor import VaeImageProcessor from diffusers.models.adapter import T2IAdapter -from diffusers.models.attention_processor import ( - AttnProcessor2_0, - LoRAAttnProcessor2_0, - LoRAXFormersAttnProcessor, - XFormersAttnProcessor, -) -from diffusers.models.autoencoders.autoencoder_kl import AutoencoderKL -from diffusers.models.autoencoders.autoencoder_tiny import AutoencoderTiny from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel from diffusers.schedulers.scheduling_dpmsolver_sde import DPMSolverSDEScheduler from diffusers.schedulers.scheduling_tcd import TCDScheduler @@ -38,11 +29,9 @@ from invokeai.app.invocations.fields import ( LatentsField, OutputField, UIType, - WithBoard, - WithMetadata, ) from invokeai.app.invocations.ip_adapter import IPAdapterField -from invokeai.app.invocations.primitives import DenoiseMaskOutput, ImageOutput, LatentsOutput +from invokeai.app.invocations.primitives import DenoiseMaskOutput, LatentsOutput from invokeai.app.invocations.t2i_adapter import T2IAdapterField from invokeai.app.services.shared.invocation_context import InvocationContext from invokeai.app.util.controlnet_utils import prepare_control_image @@ -1033,83 +1022,3 @@ class DenoiseLatentsInvocation(BaseInvocation): name = context.tensors.save(tensor=result_latents) return LatentsOutput.build(latents_name=name, latents=result_latents, seed=None) - - -@invocation( - "l2i", - title="Latents to Image", - tags=["latents", "image", "vae", "l2i"], - category="latents", - version="1.2.2", -) -class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard): - """Generates an image from latents.""" - - latents: LatentsField = InputField( - description=FieldDescriptions.latents, - input=Input.Connection, - ) - vae: VAEField = InputField( - description=FieldDescriptions.vae, - input=Input.Connection, - ) - tiled: bool = InputField(default=False, description=FieldDescriptions.tiled) - fp32: bool = InputField(default=DEFAULT_PRECISION == "float32", description=FieldDescriptions.fp32) - - @torch.no_grad() - def invoke(self, context: InvocationContext) -> ImageOutput: - latents = context.tensors.load(self.latents.latents_name) - - vae_info = context.models.load(self.vae.vae) - assert isinstance(vae_info.model, (UNet2DConditionModel, AutoencoderKL, AutoencoderTiny)) - with set_seamless(vae_info.model, self.vae.seamless_axes), vae_info as vae: - assert isinstance(vae, torch.nn.Module) - latents = latents.to(vae.device) - if self.fp32: - vae.to(dtype=torch.float32) - - use_torch_2_0_or_xformers = hasattr(vae.decoder, "mid_block") and isinstance( - vae.decoder.mid_block.attentions[0].processor, - ( - AttnProcessor2_0, - XFormersAttnProcessor, - LoRAXFormersAttnProcessor, - LoRAAttnProcessor2_0, - ), - ) - # if xformers or torch_2_0 is used attention block does not need - # to be in float32 which can save lots of memory - if use_torch_2_0_or_xformers: - vae.post_quant_conv.to(latents.dtype) - vae.decoder.conv_in.to(latents.dtype) - vae.decoder.mid_block.to(latents.dtype) - else: - latents = latents.float() - - else: - vae.to(dtype=torch.float16) - latents = latents.half() - - if self.tiled or context.config.get().force_tiled_decode: - vae.enable_tiling() - else: - vae.disable_tiling() - - # clear memory as vae decode can request a lot - TorchDevice.empty_cache() - - with torch.inference_mode(): - # copied from diffusers pipeline - latents = latents / vae.config.scaling_factor - image = vae.decode(latents, return_dict=False)[0] - image = (image / 2 + 0.5).clamp(0, 1) # denormalize - # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16 - np_image = image.cpu().permute(0, 2, 3, 1).float().numpy() - - image = VaeImageProcessor.numpy_to_pil(np_image)[0] - - TorchDevice.empty_cache() - - image_dto = context.images.save(image=image) - - return ImageOutput.build(image_dto) diff --git a/invokeai/app/invocations/latents_to_image.py b/invokeai/app/invocations/latents_to_image.py new file mode 100644 index 0000000000..e5038869dd --- /dev/null +++ b/invokeai/app/invocations/latents_to_image.py @@ -0,0 +1,107 @@ +import torch +from diffusers.image_processor import VaeImageProcessor +from diffusers.models.attention_processor import ( + AttnProcessor2_0, + LoRAAttnProcessor2_0, + LoRAXFormersAttnProcessor, + XFormersAttnProcessor, +) +from diffusers.models.autoencoders.autoencoder_kl import AutoencoderKL +from diffusers.models.autoencoders.autoencoder_tiny import AutoencoderTiny +from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel + +from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation +from invokeai.app.invocations.fields import ( + FieldDescriptions, + Input, + InputField, + LatentsField, + WithBoard, + WithMetadata, +) +from invokeai.app.invocations.latent import DEFAULT_PRECISION +from invokeai.app.invocations.model import VAEField +from invokeai.app.invocations.primitives import ImageOutput +from invokeai.app.services.shared.invocation_context import InvocationContext +from invokeai.backend.stable_diffusion import set_seamless +from invokeai.backend.util.devices import TorchDevice + + +@invocation( + "l2i", + title="Latents to Image", + tags=["latents", "image", "vae", "l2i"], + category="latents", + version="1.2.2", +) +class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard): + """Generates an image from latents.""" + + latents: LatentsField = InputField( + description=FieldDescriptions.latents, + input=Input.Connection, + ) + vae: VAEField = InputField( + description=FieldDescriptions.vae, + input=Input.Connection, + ) + tiled: bool = InputField(default=False, description=FieldDescriptions.tiled) + fp32: bool = InputField(default=DEFAULT_PRECISION == "float32", description=FieldDescriptions.fp32) + + @torch.no_grad() + def invoke(self, context: InvocationContext) -> ImageOutput: + latents = context.tensors.load(self.latents.latents_name) + + vae_info = context.models.load(self.vae.vae) + assert isinstance(vae_info.model, (UNet2DConditionModel, AutoencoderKL, AutoencoderTiny)) + with set_seamless(vae_info.model, self.vae.seamless_axes), vae_info as vae: + assert isinstance(vae, torch.nn.Module) + latents = latents.to(vae.device) + if self.fp32: + vae.to(dtype=torch.float32) + + use_torch_2_0_or_xformers = hasattr(vae.decoder, "mid_block") and isinstance( + vae.decoder.mid_block.attentions[0].processor, + ( + AttnProcessor2_0, + XFormersAttnProcessor, + LoRAXFormersAttnProcessor, + LoRAAttnProcessor2_0, + ), + ) + # if xformers or torch_2_0 is used attention block does not need + # to be in float32 which can save lots of memory + if use_torch_2_0_or_xformers: + vae.post_quant_conv.to(latents.dtype) + vae.decoder.conv_in.to(latents.dtype) + vae.decoder.mid_block.to(latents.dtype) + else: + latents = latents.float() + + else: + vae.to(dtype=torch.float16) + latents = latents.half() + + if self.tiled or context.config.get().force_tiled_decode: + vae.enable_tiling() + else: + vae.disable_tiling() + + # clear memory as vae decode can request a lot + TorchDevice.empty_cache() + + with torch.inference_mode(): + # copied from diffusers pipeline + latents = latents / vae.config.scaling_factor + image = vae.decode(latents, return_dict=False)[0] + image = (image / 2 + 0.5).clamp(0, 1) # denormalize + # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16 + np_image = image.cpu().permute(0, 2, 3, 1).float().numpy() + + image = VaeImageProcessor.numpy_to_pil(np_image)[0] + + TorchDevice.empty_cache() + + image_dto = context.images.save(image=image) + + return ImageOutput.build(image_dto) From fea9013cad127c82cbbf3a91a97121dcc9db263a Mon Sep 17 00:00:00 2001 From: Ryan Dick Date: Wed, 5 Jun 2024 14:48:32 -0400 Subject: [PATCH 081/110] Move CreateGradientMaskInvocation to its own file. No functional changes. --- .../app/invocations/create_gradient_mask.py | 138 ++++++++++++++++++ invokeai/app/invocations/latent.py | 122 +--------------- 2 files changed, 141 insertions(+), 119 deletions(-) create mode 100644 invokeai/app/invocations/create_gradient_mask.py diff --git a/invokeai/app/invocations/create_gradient_mask.py b/invokeai/app/invocations/create_gradient_mask.py new file mode 100644 index 0000000000..5d3212caf8 --- /dev/null +++ b/invokeai/app/invocations/create_gradient_mask.py @@ -0,0 +1,138 @@ +from typing import Literal, Optional + +import numpy as np +import torch +import torchvision.transforms as T +from PIL import Image, ImageFilter +from torchvision.transforms.functional import resize as tv_resize + +from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output +from invokeai.app.invocations.fields import ( + DenoiseMaskField, + FieldDescriptions, + ImageField, + Input, + InputField, + OutputField, +) +from invokeai.app.invocations.image_to_latents import ImageToLatentsInvocation +from invokeai.app.invocations.latent import DEFAULT_PRECISION +from invokeai.app.invocations.model import UNetField, VAEField +from invokeai.app.services.shared.invocation_context import InvocationContext +from invokeai.backend.model_manager import LoadedModel +from invokeai.backend.model_manager.config import MainConfigBase, ModelVariantType +from invokeai.backend.stable_diffusion.diffusers_pipeline import image_resized_to_grid_as_tensor + + +@invocation_output("gradient_mask_output") +class GradientMaskOutput(BaseInvocationOutput): + """Outputs a denoise mask and an image representing the total gradient of the mask.""" + + denoise_mask: DenoiseMaskField = OutputField(description="Mask for denoise model run") + expanded_mask_area: ImageField = OutputField( + description="Image representing the total gradient area of the mask. For paste-back purposes." + ) + + +@invocation( + "create_gradient_mask", + title="Create Gradient Mask", + tags=["mask", "denoise"], + category="latents", + version="1.1.0", +) +class CreateGradientMaskInvocation(BaseInvocation): + """Creates mask for denoising model run.""" + + mask: ImageField = InputField(default=None, description="Image which will be masked", ui_order=1) + edge_radius: int = InputField( + default=16, ge=0, description="How far to blur/expand the edges of the mask", ui_order=2 + ) + coherence_mode: Literal["Gaussian Blur", "Box Blur", "Staged"] = InputField(default="Gaussian Blur", ui_order=3) + minimum_denoise: float = InputField( + default=0.0, ge=0, le=1, description="Minimum denoise level for the coherence region", ui_order=4 + ) + image: Optional[ImageField] = InputField( + default=None, + description="OPTIONAL: Only connect for specialized Inpainting models, masked_latents will be generated from the image with the VAE", + title="[OPTIONAL] Image", + ui_order=6, + ) + unet: Optional[UNetField] = InputField( + description="OPTIONAL: If the Unet is a specialized Inpainting model, masked_latents will be generated from the image with the VAE", + default=None, + input=Input.Connection, + title="[OPTIONAL] UNet", + ui_order=5, + ) + vae: Optional[VAEField] = InputField( + default=None, + description="OPTIONAL: Only connect for specialized Inpainting models, masked_latents will be generated from the image with the VAE", + title="[OPTIONAL] VAE", + input=Input.Connection, + ui_order=7, + ) + tiled: bool = InputField(default=False, description=FieldDescriptions.tiled, ui_order=8) + fp32: bool = InputField( + default=DEFAULT_PRECISION == "float32", + description=FieldDescriptions.fp32, + ui_order=9, + ) + + @torch.no_grad() + def invoke(self, context: InvocationContext) -> GradientMaskOutput: + mask_image = context.images.get_pil(self.mask.image_name, mode="L") + if self.edge_radius > 0: + if self.coherence_mode == "Box Blur": + blur_mask = mask_image.filter(ImageFilter.BoxBlur(self.edge_radius)) + else: # Gaussian Blur OR Staged + # Gaussian Blur uses standard deviation. 1/2 radius is a good approximation + blur_mask = mask_image.filter(ImageFilter.GaussianBlur(self.edge_radius / 2)) + + blur_tensor: torch.Tensor = image_resized_to_grid_as_tensor(blur_mask, normalize=False) + + # redistribute blur so that the original edges are 0 and blur outwards to 1 + blur_tensor = (blur_tensor - 0.5) * 2 + + threshold = 1 - self.minimum_denoise + + if self.coherence_mode == "Staged": + # wherever the blur_tensor is less than fully masked, convert it to threshold + blur_tensor = torch.where((blur_tensor < 1) & (blur_tensor > 0), threshold, blur_tensor) + else: + # wherever the blur_tensor is above threshold but less than 1, drop it to threshold + blur_tensor = torch.where((blur_tensor > threshold) & (blur_tensor < 1), threshold, blur_tensor) + + else: + blur_tensor: torch.Tensor = image_resized_to_grid_as_tensor(mask_image, normalize=False) + + mask_name = context.tensors.save(tensor=blur_tensor.unsqueeze(1)) + + # compute a [0, 1] mask from the blur_tensor + expanded_mask = torch.where((blur_tensor < 1), 0, 1) + expanded_mask_image = Image.fromarray((expanded_mask.squeeze(0).numpy() * 255).astype(np.uint8), mode="L") + expanded_image_dto = context.images.save(expanded_mask_image) + + masked_latents_name = None + if self.unet is not None and self.vae is not None and self.image is not None: + # all three fields must be present at the same time + main_model_config = context.models.get_config(self.unet.unet.key) + assert isinstance(main_model_config, MainConfigBase) + if main_model_config.variant is ModelVariantType.Inpaint: + mask = blur_tensor + vae_info: LoadedModel = context.models.load(self.vae.vae) + image = context.images.get_pil(self.image.image_name) + image_tensor = image_resized_to_grid_as_tensor(image.convert("RGB")) + if image_tensor.dim() == 3: + image_tensor = image_tensor.unsqueeze(0) + img_mask = tv_resize(mask, image_tensor.shape[-2:], T.InterpolationMode.BILINEAR, antialias=False) + masked_image = image_tensor * torch.where(img_mask < 0.5, 0.0, 1.0) + masked_latents = ImageToLatentsInvocation.vae_encode( + vae_info, self.fp32, self.tiled, masked_image.clone() + ) + masked_latents_name = context.tensors.save(tensor=masked_latents) + + return GradientMaskOutput( + denoise_mask=DenoiseMaskField(mask_name=mask_name, masked_latents_name=masked_latents_name, gradient=True), + expanded_mask_area=ImageField(image_name=expanded_image_dto.image_name), + ) diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index 7102a0a4eb..5359d7f92a 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -1,9 +1,8 @@ # Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654) import inspect from contextlib import ExitStack -from typing import Any, Dict, Iterator, List, Literal, Optional, Tuple, Union +from typing import Any, Dict, Iterator, List, Optional, Tuple, Union -import numpy as np import torch import torchvision import torchvision.transforms as T @@ -13,7 +12,7 @@ from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel from diffusers.schedulers.scheduling_dpmsolver_sde import DPMSolverSDEScheduler from diffusers.schedulers.scheduling_tcd import TCDScheduler from diffusers.schedulers.scheduling_utils import SchedulerMixin as Scheduler -from PIL import Image, ImageFilter +from PIL import Image from pydantic import field_validator from torchvision.transforms.functional import resize as tv_resize from transformers import CLIPVisionModelWithProjection @@ -37,8 +36,7 @@ from invokeai.app.services.shared.invocation_context import InvocationContext from invokeai.app.util.controlnet_utils import prepare_control_image from invokeai.backend.ip_adapter.ip_adapter import IPAdapter from invokeai.backend.lora import LoRAModelRaw -from invokeai.backend.model_manager import BaseModelType, LoadedModel -from invokeai.backend.model_manager.config import MainConfigBase, ModelVariantType +from invokeai.backend.model_manager import BaseModelType from invokeai.backend.model_patcher import ModelPatcher from invokeai.backend.stable_diffusion import PipelineIntermediateState, set_seamless from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ( @@ -158,120 +156,6 @@ class CreateDenoiseMaskInvocation(BaseInvocation): ) -@invocation_output("gradient_mask_output") -class GradientMaskOutput(BaseInvocationOutput): - """Outputs a denoise mask and an image representing the total gradient of the mask.""" - - denoise_mask: DenoiseMaskField = OutputField(description="Mask for denoise model run") - expanded_mask_area: ImageField = OutputField( - description="Image representing the total gradient area of the mask. For paste-back purposes." - ) - - -@invocation( - "create_gradient_mask", - title="Create Gradient Mask", - tags=["mask", "denoise"], - category="latents", - version="1.1.0", -) -class CreateGradientMaskInvocation(BaseInvocation): - """Creates mask for denoising model run.""" - - mask: ImageField = InputField(default=None, description="Image which will be masked", ui_order=1) - edge_radius: int = InputField( - default=16, ge=0, description="How far to blur/expand the edges of the mask", ui_order=2 - ) - coherence_mode: Literal["Gaussian Blur", "Box Blur", "Staged"] = InputField(default="Gaussian Blur", ui_order=3) - minimum_denoise: float = InputField( - default=0.0, ge=0, le=1, description="Minimum denoise level for the coherence region", ui_order=4 - ) - image: Optional[ImageField] = InputField( - default=None, - description="OPTIONAL: Only connect for specialized Inpainting models, masked_latents will be generated from the image with the VAE", - title="[OPTIONAL] Image", - ui_order=6, - ) - unet: Optional[UNetField] = InputField( - description="OPTIONAL: If the Unet is a specialized Inpainting model, masked_latents will be generated from the image with the VAE", - default=None, - input=Input.Connection, - title="[OPTIONAL] UNet", - ui_order=5, - ) - vae: Optional[VAEField] = InputField( - default=None, - description="OPTIONAL: Only connect for specialized Inpainting models, masked_latents will be generated from the image with the VAE", - title="[OPTIONAL] VAE", - input=Input.Connection, - ui_order=7, - ) - tiled: bool = InputField(default=False, description=FieldDescriptions.tiled, ui_order=8) - fp32: bool = InputField( - default=DEFAULT_PRECISION == "float32", - description=FieldDescriptions.fp32, - ui_order=9, - ) - - @torch.no_grad() - def invoke(self, context: InvocationContext) -> GradientMaskOutput: - mask_image = context.images.get_pil(self.mask.image_name, mode="L") - if self.edge_radius > 0: - if self.coherence_mode == "Box Blur": - blur_mask = mask_image.filter(ImageFilter.BoxBlur(self.edge_radius)) - else: # Gaussian Blur OR Staged - # Gaussian Blur uses standard deviation. 1/2 radius is a good approximation - blur_mask = mask_image.filter(ImageFilter.GaussianBlur(self.edge_radius / 2)) - - blur_tensor: torch.Tensor = image_resized_to_grid_as_tensor(blur_mask, normalize=False) - - # redistribute blur so that the original edges are 0 and blur outwards to 1 - blur_tensor = (blur_tensor - 0.5) * 2 - - threshold = 1 - self.minimum_denoise - - if self.coherence_mode == "Staged": - # wherever the blur_tensor is less than fully masked, convert it to threshold - blur_tensor = torch.where((blur_tensor < 1) & (blur_tensor > 0), threshold, blur_tensor) - else: - # wherever the blur_tensor is above threshold but less than 1, drop it to threshold - blur_tensor = torch.where((blur_tensor > threshold) & (blur_tensor < 1), threshold, blur_tensor) - - else: - blur_tensor: torch.Tensor = image_resized_to_grid_as_tensor(mask_image, normalize=False) - - mask_name = context.tensors.save(tensor=blur_tensor.unsqueeze(1)) - - # compute a [0, 1] mask from the blur_tensor - expanded_mask = torch.where((blur_tensor < 1), 0, 1) - expanded_mask_image = Image.fromarray((expanded_mask.squeeze(0).numpy() * 255).astype(np.uint8), mode="L") - expanded_image_dto = context.images.save(expanded_mask_image) - - masked_latents_name = None - if self.unet is not None and self.vae is not None and self.image is not None: - # all three fields must be present at the same time - main_model_config = context.models.get_config(self.unet.unet.key) - assert isinstance(main_model_config, MainConfigBase) - if main_model_config.variant is ModelVariantType.Inpaint: - mask = blur_tensor - vae_info: LoadedModel = context.models.load(self.vae.vae) - image = context.images.get_pil(self.image.image_name) - image_tensor = image_resized_to_grid_as_tensor(image.convert("RGB")) - if image_tensor.dim() == 3: - image_tensor = image_tensor.unsqueeze(0) - img_mask = tv_resize(mask, image_tensor.shape[-2:], T.InterpolationMode.BILINEAR, antialias=False) - masked_image = image_tensor * torch.where(img_mask < 0.5, 0.0, 1.0) - masked_latents = ImageToLatentsInvocation.vae_encode( - vae_info, self.fp32, self.tiled, masked_image.clone() - ) - masked_latents_name = context.tensors.save(tensor=masked_latents) - - return GradientMaskOutput( - denoise_mask=DenoiseMaskField(mask_name=mask_name, masked_latents_name=masked_latents_name, gradient=True), - expanded_mask_area=ImageField(image_name=expanded_image_dto.image_name), - ) - - def get_scheduler( context: InvocationContext, scheduler_info: ModelIdentifierField, From 854bca668a2258e8fbccde427bb8b1e69fcafba9 Mon Sep 17 00:00:00 2001 From: Ryan Dick Date: Wed, 5 Jun 2024 14:59:45 -0400 Subject: [PATCH 082/110] Move CreateDenoiseMaskInvocation to its own file. No functional changes. --- .../app/invocations/create_denoise_mask.py | 80 +++++++++++++++++++ invokeai/app/invocations/latent.py | 72 +---------------- 2 files changed, 82 insertions(+), 70 deletions(-) create mode 100644 invokeai/app/invocations/create_denoise_mask.py diff --git a/invokeai/app/invocations/create_denoise_mask.py b/invokeai/app/invocations/create_denoise_mask.py new file mode 100644 index 0000000000..d6763a88c3 --- /dev/null +++ b/invokeai/app/invocations/create_denoise_mask.py @@ -0,0 +1,80 @@ +from typing import Optional + +import torch +import torchvision.transforms as T +from PIL import Image +from torchvision.transforms.functional import resize as tv_resize + +from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation +from invokeai.app.invocations.fields import FieldDescriptions, ImageField, Input, InputField +from invokeai.app.invocations.image_to_latents import ImageToLatentsInvocation +from invokeai.app.invocations.latent import DEFAULT_PRECISION +from invokeai.app.invocations.model import VAEField +from invokeai.app.invocations.primitives import DenoiseMaskOutput +from invokeai.app.services.shared.invocation_context import InvocationContext +from invokeai.backend.stable_diffusion.diffusers_pipeline import image_resized_to_grid_as_tensor + + +@invocation( + "create_denoise_mask", + title="Create Denoise Mask", + tags=["mask", "denoise"], + category="latents", + version="1.0.2", +) +class CreateDenoiseMaskInvocation(BaseInvocation): + """Creates mask for denoising model run.""" + + vae: VAEField = InputField(description=FieldDescriptions.vae, input=Input.Connection, ui_order=0) + image: Optional[ImageField] = InputField(default=None, description="Image which will be masked", ui_order=1) + mask: ImageField = InputField(description="The mask to use when pasting", ui_order=2) + tiled: bool = InputField(default=False, description=FieldDescriptions.tiled, ui_order=3) + fp32: bool = InputField( + default=DEFAULT_PRECISION == "float32", + description=FieldDescriptions.fp32, + ui_order=4, + ) + + def prep_mask_tensor(self, mask_image: Image.Image) -> torch.Tensor: + if mask_image.mode != "L": + mask_image = mask_image.convert("L") + mask_tensor: torch.Tensor = image_resized_to_grid_as_tensor(mask_image, normalize=False) + if mask_tensor.dim() == 3: + mask_tensor = mask_tensor.unsqueeze(0) + # if shape is not None: + # mask_tensor = tv_resize(mask_tensor, shape, T.InterpolationMode.BILINEAR) + return mask_tensor + + @torch.no_grad() + def invoke(self, context: InvocationContext) -> DenoiseMaskOutput: + if self.image is not None: + image = context.images.get_pil(self.image.image_name) + image_tensor = image_resized_to_grid_as_tensor(image.convert("RGB")) + if image_tensor.dim() == 3: + image_tensor = image_tensor.unsqueeze(0) + else: + image_tensor = None + + mask = self.prep_mask_tensor( + context.images.get_pil(self.mask.image_name), + ) + + if image_tensor is not None: + vae_info = context.models.load(self.vae.vae) + + img_mask = tv_resize(mask, image_tensor.shape[-2:], T.InterpolationMode.BILINEAR, antialias=False) + masked_image = image_tensor * torch.where(img_mask < 0.5, 0.0, 1.0) + # TODO: + masked_latents = ImageToLatentsInvocation.vae_encode(vae_info, self.fp32, self.tiled, masked_image.clone()) + + masked_latents_name = context.tensors.save(tensor=masked_latents) + else: + masked_latents_name = None + + mask_name = context.tensors.save(tensor=mask) + + return DenoiseMaskOutput.build( + mask_name=mask_name, + masked_latents_name=masked_latents_name, + gradient=False, + ) diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index 5359d7f92a..deeb484aea 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -12,7 +12,6 @@ from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel from diffusers.schedulers.scheduling_dpmsolver_sde import DPMSolverSDEScheduler from diffusers.schedulers.scheduling_tcd import TCDScheduler from diffusers.schedulers.scheduling_utils import SchedulerMixin as Scheduler -from PIL import Image from pydantic import field_validator from torchvision.transforms.functional import resize as tv_resize from transformers import CLIPVisionModelWithProjection @@ -22,7 +21,6 @@ from invokeai.app.invocations.fields import ( ConditioningField, DenoiseMaskField, FieldDescriptions, - ImageField, Input, InputField, LatentsField, @@ -30,7 +28,7 @@ from invokeai.app.invocations.fields import ( UIType, ) from invokeai.app.invocations.ip_adapter import IPAdapterField -from invokeai.app.invocations.primitives import DenoiseMaskOutput, LatentsOutput +from invokeai.app.invocations.primitives import LatentsOutput from invokeai.app.invocations.t2i_adapter import T2IAdapterField from invokeai.app.services.shared.invocation_context import InvocationContext from invokeai.app.util.controlnet_utils import prepare_control_image @@ -55,13 +53,12 @@ from ...backend.stable_diffusion.diffusers_pipeline import ( ControlNetData, StableDiffusionGeneratorPipeline, T2IAdapterData, - image_resized_to_grid_as_tensor, ) from ...backend.stable_diffusion.schedulers import SCHEDULER_MAP from ...backend.util.devices import TorchDevice from .baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output from .controlnet_image_processors import ControlField -from .model import ModelIdentifierField, UNetField, VAEField +from .model import ModelIdentifierField, UNetField DEFAULT_PRECISION = TorchDevice.choose_torch_dtype() @@ -91,71 +88,6 @@ class SchedulerInvocation(BaseInvocation): return SchedulerOutput(scheduler=self.scheduler) -@invocation( - "create_denoise_mask", - title="Create Denoise Mask", - tags=["mask", "denoise"], - category="latents", - version="1.0.2", -) -class CreateDenoiseMaskInvocation(BaseInvocation): - """Creates mask for denoising model run.""" - - vae: VAEField = InputField(description=FieldDescriptions.vae, input=Input.Connection, ui_order=0) - image: Optional[ImageField] = InputField(default=None, description="Image which will be masked", ui_order=1) - mask: ImageField = InputField(description="The mask to use when pasting", ui_order=2) - tiled: bool = InputField(default=False, description=FieldDescriptions.tiled, ui_order=3) - fp32: bool = InputField( - default=DEFAULT_PRECISION == "float32", - description=FieldDescriptions.fp32, - ui_order=4, - ) - - def prep_mask_tensor(self, mask_image: Image.Image) -> torch.Tensor: - if mask_image.mode != "L": - mask_image = mask_image.convert("L") - mask_tensor: torch.Tensor = image_resized_to_grid_as_tensor(mask_image, normalize=False) - if mask_tensor.dim() == 3: - mask_tensor = mask_tensor.unsqueeze(0) - # if shape is not None: - # mask_tensor = tv_resize(mask_tensor, shape, T.InterpolationMode.BILINEAR) - return mask_tensor - - @torch.no_grad() - def invoke(self, context: InvocationContext) -> DenoiseMaskOutput: - if self.image is not None: - image = context.images.get_pil(self.image.image_name) - image_tensor = image_resized_to_grid_as_tensor(image.convert("RGB")) - if image_tensor.dim() == 3: - image_tensor = image_tensor.unsqueeze(0) - else: - image_tensor = None - - mask = self.prep_mask_tensor( - context.images.get_pil(self.mask.image_name), - ) - - if image_tensor is not None: - vae_info = context.models.load(self.vae.vae) - - img_mask = tv_resize(mask, image_tensor.shape[-2:], T.InterpolationMode.BILINEAR, antialias=False) - masked_image = image_tensor * torch.where(img_mask < 0.5, 0.0, 1.0) - # TODO: - masked_latents = ImageToLatentsInvocation.vae_encode(vae_info, self.fp32, self.tiled, masked_image.clone()) - - masked_latents_name = context.tensors.save(tensor=masked_latents) - else: - masked_latents_name = None - - mask_name = context.tensors.save(tensor=mask) - - return DenoiseMaskOutput.build( - mask_name=mask_name, - masked_latents_name=masked_latents_name, - gradient=False, - ) - - def get_scheduler( context: InvocationContext, scheduler_info: ModelIdentifierField, From 8f1afc032a5496186ebd7e5e97464f94c62313b8 Mon Sep 17 00:00:00 2001 From: Ryan Dick Date: Wed, 5 Jun 2024 17:18:39 -0400 Subject: [PATCH 083/110] Move SchedulerInvocation to a new file. No functional changes. --- invokeai/app/invocations/latent.py | 28 +--------------------- invokeai/app/invocations/scheduler.py | 34 +++++++++++++++++++++++++++ 2 files changed, 35 insertions(+), 27 deletions(-) create mode 100644 invokeai/app/invocations/scheduler.py diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py index deeb484aea..3851caa647 100644 --- a/invokeai/app/invocations/latent.py +++ b/invokeai/app/invocations/latent.py @@ -24,7 +24,6 @@ from invokeai.app.invocations.fields import ( Input, InputField, LatentsField, - OutputField, UIType, ) from invokeai.app.invocations.ip_adapter import IPAdapterField @@ -56,38 +55,13 @@ from ...backend.stable_diffusion.diffusers_pipeline import ( ) from ...backend.stable_diffusion.schedulers import SCHEDULER_MAP from ...backend.util.devices import TorchDevice -from .baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output +from .baseinvocation import BaseInvocation, invocation from .controlnet_image_processors import ControlField from .model import ModelIdentifierField, UNetField DEFAULT_PRECISION = TorchDevice.choose_torch_dtype() -@invocation_output("scheduler_output") -class SchedulerOutput(BaseInvocationOutput): - scheduler: SCHEDULER_NAME_VALUES = OutputField(description=FieldDescriptions.scheduler, ui_type=UIType.Scheduler) - - -@invocation( - "scheduler", - title="Scheduler", - tags=["scheduler"], - category="latents", - version="1.0.0", -) -class SchedulerInvocation(BaseInvocation): - """Selects a scheduler.""" - - scheduler: SCHEDULER_NAME_VALUES = InputField( - default="euler", - description=FieldDescriptions.scheduler, - ui_type=UIType.Scheduler, - ) - - def invoke(self, context: InvocationContext) -> SchedulerOutput: - return SchedulerOutput(scheduler=self.scheduler) - - def get_scheduler( context: InvocationContext, scheduler_info: ModelIdentifierField, diff --git a/invokeai/app/invocations/scheduler.py b/invokeai/app/invocations/scheduler.py new file mode 100644 index 0000000000..52af20378e --- /dev/null +++ b/invokeai/app/invocations/scheduler.py @@ -0,0 +1,34 @@ +from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output +from invokeai.app.invocations.constants import SCHEDULER_NAME_VALUES +from invokeai.app.invocations.fields import ( + FieldDescriptions, + InputField, + OutputField, + UIType, +) +from invokeai.app.services.shared.invocation_context import InvocationContext + + +@invocation_output("scheduler_output") +class SchedulerOutput(BaseInvocationOutput): + scheduler: SCHEDULER_NAME_VALUES = OutputField(description=FieldDescriptions.scheduler, ui_type=UIType.Scheduler) + + +@invocation( + "scheduler", + title="Scheduler", + tags=["scheduler"], + category="latents", + version="1.0.0", +) +class SchedulerInvocation(BaseInvocation): + """Selects a scheduler.""" + + scheduler: SCHEDULER_NAME_VALUES = InputField( + default="euler", + description=FieldDescriptions.scheduler, + ui_type=UIType.Scheduler, + ) + + def invoke(self, context: InvocationContext) -> SchedulerOutput: + return SchedulerOutput(scheduler=self.scheduler) From 52c0c4a32f989e1d25a244c5ad094b7ec45cca47 Mon Sep 17 00:00:00 2001 From: Ryan Dick Date: Thu, 6 Jun 2024 13:43:58 -0400 Subject: [PATCH 084/110] Rename latent.py -> denoise_latents.py. --- invokeai/app/invocations/create_denoise_mask.py | 2 +- invokeai/app/invocations/create_gradient_mask.py | 2 +- invokeai/app/invocations/{latent.py => denoise_latents.py} | 0 invokeai/app/invocations/image_to_latents.py | 2 +- invokeai/app/invocations/latents_to_image.py | 2 +- invokeai/invocation_api/__init__.py | 4 ++-- pyproject.toml | 2 +- 7 files changed, 7 insertions(+), 7 deletions(-) rename invokeai/app/invocations/{latent.py => denoise_latents.py} (100%) diff --git a/invokeai/app/invocations/create_denoise_mask.py b/invokeai/app/invocations/create_denoise_mask.py index d6763a88c3..d128e0efec 100644 --- a/invokeai/app/invocations/create_denoise_mask.py +++ b/invokeai/app/invocations/create_denoise_mask.py @@ -6,9 +6,9 @@ from PIL import Image from torchvision.transforms.functional import resize as tv_resize from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation +from invokeai.app.invocations.denoise_latents import DEFAULT_PRECISION from invokeai.app.invocations.fields import FieldDescriptions, ImageField, Input, InputField from invokeai.app.invocations.image_to_latents import ImageToLatentsInvocation -from invokeai.app.invocations.latent import DEFAULT_PRECISION from invokeai.app.invocations.model import VAEField from invokeai.app.invocations.primitives import DenoiseMaskOutput from invokeai.app.services.shared.invocation_context import InvocationContext diff --git a/invokeai/app/invocations/create_gradient_mask.py b/invokeai/app/invocations/create_gradient_mask.py index 5d3212caf8..2d2b13fdcc 100644 --- a/invokeai/app/invocations/create_gradient_mask.py +++ b/invokeai/app/invocations/create_gradient_mask.py @@ -7,6 +7,7 @@ from PIL import Image, ImageFilter from torchvision.transforms.functional import resize as tv_resize from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output +from invokeai.app.invocations.denoise_latents import DEFAULT_PRECISION from invokeai.app.invocations.fields import ( DenoiseMaskField, FieldDescriptions, @@ -16,7 +17,6 @@ from invokeai.app.invocations.fields import ( OutputField, ) from invokeai.app.invocations.image_to_latents import ImageToLatentsInvocation -from invokeai.app.invocations.latent import DEFAULT_PRECISION from invokeai.app.invocations.model import UNetField, VAEField from invokeai.app.services.shared.invocation_context import InvocationContext from invokeai.backend.model_manager import LoadedModel diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/denoise_latents.py similarity index 100% rename from invokeai/app/invocations/latent.py rename to invokeai/app/invocations/denoise_latents.py diff --git a/invokeai/app/invocations/image_to_latents.py b/invokeai/app/invocations/image_to_latents.py index 53c64d8b4e..bf2eb414e1 100644 --- a/invokeai/app/invocations/image_to_latents.py +++ b/invokeai/app/invocations/image_to_latents.py @@ -12,13 +12,13 @@ from diffusers.models.autoencoders.autoencoder_kl import AutoencoderKL from diffusers.models.autoencoders.autoencoder_tiny import AutoencoderTiny from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation +from invokeai.app.invocations.denoise_latents import DEFAULT_PRECISION from invokeai.app.invocations.fields import ( FieldDescriptions, ImageField, Input, InputField, ) -from invokeai.app.invocations.latent import DEFAULT_PRECISION from invokeai.app.invocations.model import VAEField from invokeai.app.invocations.primitives import LatentsOutput from invokeai.app.services.shared.invocation_context import InvocationContext diff --git a/invokeai/app/invocations/latents_to_image.py b/invokeai/app/invocations/latents_to_image.py index e5038869dd..648ee7ac68 100644 --- a/invokeai/app/invocations/latents_to_image.py +++ b/invokeai/app/invocations/latents_to_image.py @@ -11,6 +11,7 @@ from diffusers.models.autoencoders.autoencoder_tiny import AutoencoderTiny from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation +from invokeai.app.invocations.denoise_latents import DEFAULT_PRECISION from invokeai.app.invocations.fields import ( FieldDescriptions, Input, @@ -19,7 +20,6 @@ from invokeai.app.invocations.fields import ( WithBoard, WithMetadata, ) -from invokeai.app.invocations.latent import DEFAULT_PRECISION from invokeai.app.invocations.model import VAEField from invokeai.app.invocations.primitives import ImageOutput from invokeai.app.services.shared.invocation_context import InvocationContext diff --git a/invokeai/invocation_api/__init__.py b/invokeai/invocation_api/__init__.py index 4eb78cf1ee..8f7452bb4b 100644 --- a/invokeai/invocation_api/__init__.py +++ b/invokeai/invocation_api/__init__.py @@ -12,6 +12,7 @@ from invokeai.app.invocations.baseinvocation import ( invocation_output, ) from invokeai.app.invocations.constants import SCHEDULER_NAME_VALUES +from invokeai.app.invocations.denoise_latents import SchedulerOutput from invokeai.app.invocations.fields import ( BoardField, ColorField, @@ -31,7 +32,6 @@ from invokeai.app.invocations.fields import ( WithMetadata, WithWorkflow, ) -from invokeai.app.invocations.latent import SchedulerOutput from invokeai.app.invocations.metadata import MetadataItemField, MetadataItemOutput, MetadataOutput from invokeai.app.invocations.model import ( CLIPField, @@ -108,7 +108,7 @@ __all__ = [ "WithBoard", "WithMetadata", "WithWorkflow", - # invokeai.app.invocations.latent + # invokeai.app.invocations.scheduler "SchedulerOutput", # invokeai.app.invocations.metadata "MetadataItemField", diff --git a/pyproject.toml b/pyproject.toml index bb30747ba8..fcc0aff60c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -224,7 +224,7 @@ follow_imports = "skip" # skips type checking of the modules listed below module = [ "invokeai.app.api.routers.models", "invokeai.app.invocations.compel", - "invokeai.app.invocations.latent", + "invokeai.app.invocations.denoise_latents", "invokeai.app.services.invocation_stats.invocation_stats_default", "invokeai.app.services.model_manager.model_manager_base", "invokeai.app.services.model_manager.model_manager_default", From b1e56e2485e712b39ddc5f9f94fd7d3a44244e1d Mon Sep 17 00:00:00 2001 From: blessedcoolant <54517381+blessedcoolant@users.noreply.github.com> Date: Sun, 9 Jun 2024 13:57:57 +0530 Subject: [PATCH 085/110] fix: SchedulerOutput not being imported correctly --- invokeai/invocation_api/__init__.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/invokeai/invocation_api/__init__.py b/invokeai/invocation_api/__init__.py index 8f7452bb4b..97260c4dfe 100644 --- a/invokeai/invocation_api/__init__.py +++ b/invokeai/invocation_api/__init__.py @@ -12,7 +12,6 @@ from invokeai.app.invocations.baseinvocation import ( invocation_output, ) from invokeai.app.invocations.constants import SCHEDULER_NAME_VALUES -from invokeai.app.invocations.denoise_latents import SchedulerOutput from invokeai.app.invocations.fields import ( BoardField, ColorField, @@ -64,6 +63,7 @@ from invokeai.app.invocations.primitives import ( StringCollectionOutput, StringOutput, ) +from invokeai.app.invocations.scheduler import SchedulerOutput from invokeai.app.services.boards.boards_common import BoardDTO from invokeai.app.services.config.config_default import InvokeAIAppConfig from invokeai.app.services.image_records.image_records_common import ImageCategory From 568a4844f7bbed88e7c336bf9f4febba19320885 Mon Sep 17 00:00:00 2001 From: blessedcoolant <54517381+blessedcoolant@users.noreply.github.com> Date: Sun, 9 Jun 2024 14:04:43 +0530 Subject: [PATCH 086/110] fix: other recursive imports --- .../app/services/download/download_default.py | 5 +---- invokeai/app/services/events/events_base.py | 1 - .../model_install/model_install_default.py | 18 +++++++++--------- 3 files changed, 10 insertions(+), 14 deletions(-) diff --git a/invokeai/app/services/download/download_default.py b/invokeai/app/services/download/download_default.py index 4640a656dc..f6c7c1a1a0 100644 --- a/invokeai/app/services/download/download_default.py +++ b/invokeai/app/services/download/download_default.py @@ -8,7 +8,7 @@ import time import traceback from pathlib import Path from queue import Empty, PriorityQueue -from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional, Set +from typing import Any, Dict, List, Literal, Optional, Set import requests from pydantic.networks import AnyHttpUrl @@ -34,9 +34,6 @@ from .download_base import ( UnknownJobIDException, ) -if TYPE_CHECKING: - from invokeai.app.services.events.events_base import EventServiceBase - # Maximum number of bytes to download during each call to requests.iter_content() DOWNLOAD_CHUNK_SIZE = 100000 diff --git a/invokeai/app/services/events/events_base.py b/invokeai/app/services/events/events_base.py index 3c0fb0a30b..cf49cc0626 100644 --- a/invokeai/app/services/events/events_base.py +++ b/invokeai/app/services/events/events_base.py @@ -34,7 +34,6 @@ from invokeai.backend.stable_diffusion.diffusers_pipeline import PipelineInterme if TYPE_CHECKING: from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput from invokeai.app.services.download.download_base import DownloadJob - from invokeai.app.services.events.events_common import EventBase from invokeai.app.services.model_install.model_install_common import ModelInstallJob from invokeai.app.services.session_processor.session_processor_common import ProgressImage from invokeai.app.services.session_queue.session_queue_common import ( diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py index 39e38a593f..0a2e2d798a 100644 --- a/invokeai/app/services/model_install/model_install_default.py +++ b/invokeai/app/services/model_install/model_install_default.py @@ -9,7 +9,7 @@ from pathlib import Path from queue import Empty, Queue from shutil import copyfile, copytree, move, rmtree from tempfile import mkdtemp -from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Type, Union +from typing import Any, Dict, List, Optional, Tuple, Type, Union import torch import yaml @@ -60,9 +60,6 @@ from .model_install_common import ( TMPDIR_PREFIX = "tmpinstall_" -if TYPE_CHECKING: - from invokeai.app.services.events.events_base import EventServiceBase - class ModelInstallService(ModelInstallServiceBase): """class for InvokeAI model installation.""" @@ -412,11 +409,14 @@ class ModelInstallService(ModelInstallServiceBase): if isinstance(source, HFModelSource): metadata = HuggingFaceMetadataFetch(self._session).from_id(source.repo_id, source.variant) assert isinstance(metadata, ModelMetadataWithFiles) - return metadata.download_urls( - variant=source.variant or self._guess_variant(), - subfolder=source.subfolder, - session=self._session, - ), metadata + return ( + metadata.download_urls( + variant=source.variant or self._guess_variant(), + subfolder=source.subfolder, + session=self._session, + ), + metadata, + ) if isinstance(source, URLModelSource): try: From a3cb5da130280d380cbb7bf4492f8cf50ebd060b Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Thu, 13 Jun 2024 13:10:03 -0400 Subject: [PATCH 087/110] Improve RAM<->VRAM memory copy performance in LoRA patching and elsewhere (#6490) * allow model patcher to optimize away the unpatching step when feasible * remove lazy_offloading functionality * allow model patcher to optimize away the unpatching step when feasible * remove lazy_offloading functionality * do not save original weights if there is a CPU copy of state dict * Update invokeai/backend/model_manager/load/load_base.py Co-authored-by: Ryan Dick * documentation fixes requested during penultimate review * add non-blocking=True parameters to several torch.nn.Module.to() calls, for slight performance increases * fix ruff errors * prevent crash on non-cuda-enabled systems --------- Co-authored-by: Lincoln Stein Co-authored-by: Kent Keirsey <31807370+hipsterusername@users.noreply.github.com> Co-authored-by: Ryan Dick --- invokeai/backend/ip_adapter/ip_adapter.py | 11 ++-- invokeai/backend/lora.py | 51 +++++++++++-------- .../load/model_cache/model_cache_default.py | 4 +- invokeai/backend/model_patcher.py | 16 +++--- invokeai/backend/onnx/onnx_runtime.py | 10 ++++ invokeai/backend/raw_model.py | 18 ++++++- invokeai/backend/textual_inversion.py | 12 +++++ 7 files changed, 84 insertions(+), 38 deletions(-) diff --git a/invokeai/backend/ip_adapter/ip_adapter.py b/invokeai/backend/ip_adapter/ip_adapter.py index f3be042146..c33cb3f4ab 100644 --- a/invokeai/backend/ip_adapter/ip_adapter.py +++ b/invokeai/backend/ip_adapter/ip_adapter.py @@ -125,13 +125,16 @@ class IPAdapter(RawModel): self.device, dtype=self.dtype ) - def to(self, device: torch.device, dtype: Optional[torch.dtype] = None): - self.device = device + def to( + self, device: Optional[torch.device] = None, dtype: Optional[torch.dtype] = None, non_blocking: bool = False + ): + if device is not None: + self.device = device if dtype is not None: self.dtype = dtype - self._image_proj_model.to(device=self.device, dtype=self.dtype) - self.attn_weights.to(device=self.device, dtype=self.dtype) + self._image_proj_model.to(device=self.device, dtype=self.dtype, non_blocking=non_blocking) + self.attn_weights.to(device=self.device, dtype=self.dtype, non_blocking=non_blocking) def calc_size(self): # workaround for circular import diff --git a/invokeai/backend/lora.py b/invokeai/backend/lora.py index 0b7128034a..f7c3863a6a 100644 --- a/invokeai/backend/lora.py +++ b/invokeai/backend/lora.py @@ -61,9 +61,10 @@ class LoRALayerBase: self, device: Optional[torch.device] = None, dtype: Optional[torch.dtype] = None, + non_blocking: bool = False, ) -> None: if self.bias is not None: - self.bias = self.bias.to(device=device, dtype=dtype) + self.bias = self.bias.to(device=device, dtype=dtype, non_blocking=non_blocking) # TODO: find and debug lora/locon with bias @@ -109,14 +110,15 @@ class LoRALayer(LoRALayerBase): self, device: Optional[torch.device] = None, dtype: Optional[torch.dtype] = None, + non_blocking: bool = False, ) -> None: - super().to(device=device, dtype=dtype) + super().to(device=device, dtype=dtype, non_blocking=non_blocking) - self.up = self.up.to(device=device, dtype=dtype) - self.down = self.down.to(device=device, dtype=dtype) + self.up = self.up.to(device=device, dtype=dtype, non_blocking=non_blocking) + self.down = self.down.to(device=device, dtype=dtype, non_blocking=non_blocking) if self.mid is not None: - self.mid = self.mid.to(device=device, dtype=dtype) + self.mid = self.mid.to(device=device, dtype=dtype, non_blocking=non_blocking) class LoHALayer(LoRALayerBase): @@ -169,18 +171,19 @@ class LoHALayer(LoRALayerBase): self, device: Optional[torch.device] = None, dtype: Optional[torch.dtype] = None, + non_blocking: bool = False, ) -> None: super().to(device=device, dtype=dtype) - self.w1_a = self.w1_a.to(device=device, dtype=dtype) - self.w1_b = self.w1_b.to(device=device, dtype=dtype) + self.w1_a = self.w1_a.to(device=device, dtype=dtype, non_blocking=non_blocking) + self.w1_b = self.w1_b.to(device=device, dtype=dtype, non_blocking=non_blocking) if self.t1 is not None: - self.t1 = self.t1.to(device=device, dtype=dtype) + self.t1 = self.t1.to(device=device, dtype=dtype, non_blocking=non_blocking) - self.w2_a = self.w2_a.to(device=device, dtype=dtype) - self.w2_b = self.w2_b.to(device=device, dtype=dtype) + self.w2_a = self.w2_a.to(device=device, dtype=dtype, non_blocking=non_blocking) + self.w2_b = self.w2_b.to(device=device, dtype=dtype, non_blocking=non_blocking) if self.t2 is not None: - self.t2 = self.t2.to(device=device, dtype=dtype) + self.t2 = self.t2.to(device=device, dtype=dtype, non_blocking=non_blocking) class LoKRLayer(LoRALayerBase): @@ -265,6 +268,7 @@ class LoKRLayer(LoRALayerBase): self, device: Optional[torch.device] = None, dtype: Optional[torch.dtype] = None, + non_blocking: bool = False, ) -> None: super().to(device=device, dtype=dtype) @@ -273,19 +277,19 @@ class LoKRLayer(LoRALayerBase): else: assert self.w1_a is not None assert self.w1_b is not None - self.w1_a = self.w1_a.to(device=device, dtype=dtype) - self.w1_b = self.w1_b.to(device=device, dtype=dtype) + self.w1_a = self.w1_a.to(device=device, dtype=dtype, non_blocking=non_blocking) + self.w1_b = self.w1_b.to(device=device, dtype=dtype, non_blocking=non_blocking) if self.w2 is not None: - self.w2 = self.w2.to(device=device, dtype=dtype) + self.w2 = self.w2.to(device=device, dtype=dtype, non_blocking=non_blocking) else: assert self.w2_a is not None assert self.w2_b is not None - self.w2_a = self.w2_a.to(device=device, dtype=dtype) - self.w2_b = self.w2_b.to(device=device, dtype=dtype) + self.w2_a = self.w2_a.to(device=device, dtype=dtype, non_blocking=non_blocking) + self.w2_b = self.w2_b.to(device=device, dtype=dtype, non_blocking=non_blocking) if self.t2 is not None: - self.t2 = self.t2.to(device=device, dtype=dtype) + self.t2 = self.t2.to(device=device, dtype=dtype, non_blocking=non_blocking) class FullLayer(LoRALayerBase): @@ -319,10 +323,11 @@ class FullLayer(LoRALayerBase): self, device: Optional[torch.device] = None, dtype: Optional[torch.dtype] = None, + non_blocking: bool = False, ) -> None: super().to(device=device, dtype=dtype) - self.weight = self.weight.to(device=device, dtype=dtype) + self.weight = self.weight.to(device=device, dtype=dtype, non_blocking=non_blocking) class IA3Layer(LoRALayerBase): @@ -358,11 +363,12 @@ class IA3Layer(LoRALayerBase): self, device: Optional[torch.device] = None, dtype: Optional[torch.dtype] = None, + non_blocking: bool = False, ): super().to(device=device, dtype=dtype) - self.weight = self.weight.to(device=device, dtype=dtype) - self.on_input = self.on_input.to(device=device, dtype=dtype) + self.weight = self.weight.to(device=device, dtype=dtype, non_blocking=non_blocking) + self.on_input = self.on_input.to(device=device, dtype=dtype, non_blocking=non_blocking) AnyLoRALayer = Union[LoRALayer, LoHALayer, LoKRLayer, FullLayer, IA3Layer] @@ -388,10 +394,11 @@ class LoRAModelRaw(RawModel): # (torch.nn.Module): self, device: Optional[torch.device] = None, dtype: Optional[torch.dtype] = None, + non_blocking: bool = False, ) -> None: # TODO: try revert if exception? for _key, layer in self.layers.items(): - layer.to(device=device, dtype=dtype) + layer.to(device=device, dtype=dtype, non_blocking=non_blocking) def calc_size(self) -> int: model_size = 0 @@ -514,7 +521,7 @@ class LoRAModelRaw(RawModel): # (torch.nn.Module): # lower memory consumption by removing already parsed layer values state_dict[layer_key].clear() - layer.to(device=device, dtype=dtype) + layer.to(device=device, dtype=dtype, non_blocking=True) model.layers[layer_key] = layer return model diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py index 335a15a5c8..d48e45426e 100644 --- a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py +++ b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py @@ -285,9 +285,9 @@ class ModelCache(ModelCacheBase[AnyModel]): else: new_dict: Dict[str, torch.Tensor] = {} for k, v in cache_entry.state_dict.items(): - new_dict[k] = v.to(torch.device(target_device), copy=True) + new_dict[k] = v.to(torch.device(target_device), copy=True, non_blocking=True) cache_entry.model.load_state_dict(new_dict, assign=True) - cache_entry.model.to(target_device) + cache_entry.model.to(target_device, non_blocking=True) cache_entry.device = target_device except Exception as e: # blow away cache entry self._delete_cache_entry(cache_entry) diff --git a/invokeai/backend/model_patcher.py b/invokeai/backend/model_patcher.py index c407cd8472..fdc79539ae 100644 --- a/invokeai/backend/model_patcher.py +++ b/invokeai/backend/model_patcher.py @@ -67,7 +67,7 @@ class ModelPatcher: unet: UNet2DConditionModel, loras: Iterator[Tuple[LoRAModelRaw, float]], model_state_dict: Optional[Dict[str, torch.Tensor]] = None, - ) -> None: + ) -> Generator[None, None, None]: with cls.apply_lora( unet, loras=loras, @@ -83,7 +83,7 @@ class ModelPatcher: text_encoder: CLIPTextModel, loras: Iterator[Tuple[LoRAModelRaw, float]], model_state_dict: Optional[Dict[str, torch.Tensor]] = None, - ) -> None: + ) -> Generator[None, None, None]: with cls.apply_lora(text_encoder, loras=loras, prefix="lora_te_", model_state_dict=model_state_dict): yield @@ -95,7 +95,7 @@ class ModelPatcher: loras: Iterator[Tuple[LoRAModelRaw, float]], prefix: str, model_state_dict: Optional[Dict[str, torch.Tensor]] = None, - ) -> Generator[Any, None, None]: + ) -> Generator[None, None, None]: """ Apply one or more LoRAs to a model. @@ -139,12 +139,12 @@ class ModelPatcher: # We intentionally move to the target device first, then cast. Experimentally, this was found to # be significantly faster for 16-bit CPU tensors being moved to a CUDA device than doing the # same thing in a single call to '.to(...)'. - layer.to(device=device) - layer.to(dtype=torch.float32) + layer.to(device=device, non_blocking=True) + layer.to(dtype=torch.float32, non_blocking=True) # TODO(ryand): Using torch.autocast(...) over explicit casting may offer a speed benefit on CUDA # devices here. Experimentally, it was found to be very slow on CPU. More investigation needed. layer_weight = layer.get_weight(module.weight) * (lora_weight * layer_scale) - layer.to(device=torch.device("cpu")) + layer.to(device=torch.device("cpu"), non_blocking=True) assert isinstance(layer_weight, torch.Tensor) # mypy thinks layer_weight is a float|Any ??! if module.weight.shape != layer_weight.shape: @@ -153,7 +153,7 @@ class ModelPatcher: layer_weight = layer_weight.reshape(module.weight.shape) assert isinstance(layer_weight, torch.Tensor) # mypy thinks layer_weight is a float|Any ??! - module.weight += layer_weight.to(dtype=dtype) + module.weight += layer_weight.to(dtype=dtype, non_blocking=True) yield # wait for context manager exit @@ -161,7 +161,7 @@ class ModelPatcher: assert hasattr(model, "get_submodule") # mypy not picking up fact that torch.nn.Module has get_submodule() with torch.no_grad(): for module_key, weight in original_weights.items(): - model.get_submodule(module_key).weight.copy_(weight) + model.get_submodule(module_key).weight.copy_(weight, non_blocking=True) @classmethod @contextmanager diff --git a/invokeai/backend/onnx/onnx_runtime.py b/invokeai/backend/onnx/onnx_runtime.py index 8916865dd5..9fcd4d093f 100644 --- a/invokeai/backend/onnx/onnx_runtime.py +++ b/invokeai/backend/onnx/onnx_runtime.py @@ -6,6 +6,7 @@ from typing import Any, List, Optional, Tuple, Union import numpy as np import onnx +import torch from onnx import numpy_helper from onnxruntime import InferenceSession, SessionOptions, get_available_providers @@ -188,6 +189,15 @@ class IAIOnnxRuntimeModel(RawModel): # return self.io_binding.copy_outputs_to_cpu() return self.session.run(None, inputs) + # compatability with RawModel ABC + def to( + self, + device: Optional[torch.device] = None, + dtype: Optional[torch.dtype] = None, + non_blocking: bool = False, + ) -> None: + pass + # compatability with diffusers load code @classmethod def from_pretrained( diff --git a/invokeai/backend/raw_model.py b/invokeai/backend/raw_model.py index d0dc50c456..7bca6945d9 100644 --- a/invokeai/backend/raw_model.py +++ b/invokeai/backend/raw_model.py @@ -10,6 +10,20 @@ The term 'raw' was introduced to describe a wrapper around a torch.nn.Module that adds additional methods and attributes. """ +from abc import ABC, abstractmethod +from typing import Optional -class RawModel: - """Base class for 'Raw' model wrappers.""" +import torch + + +class RawModel(ABC): + """Abstract base class for 'Raw' model wrappers.""" + + @abstractmethod + def to( + self, + device: Optional[torch.device] = None, + dtype: Optional[torch.dtype] = None, + non_blocking: bool = False, + ) -> None: + pass diff --git a/invokeai/backend/textual_inversion.py b/invokeai/backend/textual_inversion.py index 98104f769e..0408176edb 100644 --- a/invokeai/backend/textual_inversion.py +++ b/invokeai/backend/textual_inversion.py @@ -65,6 +65,18 @@ class TextualInversionModelRaw(RawModel): return result + def to( + self, + device: Optional[torch.device] = None, + dtype: Optional[torch.dtype] = None, + non_blocking: bool = False, + ) -> None: + if not torch.cuda.is_available(): + return + for emb in [self.embedding, self.embedding_2]: + if emb is not None: + emb.to(device=device, dtype=dtype, non_blocking=non_blocking) + class TextualInversionManager(BaseTextualInversionManager): """TextualInversionManager implements the BaseTextualInversionManager ABC from the compel library.""" From 785bb1d9e446987b64a41491a1517e207793655c Mon Sep 17 00:00:00 2001 From: Ryan Dick Date: Thu, 6 Jun 2024 09:16:45 -0400 Subject: [PATCH 088/110] Fix all comparisons against the DEFAULT_PRECISION constant. DEFAULT_PRECISION is a torch.dtype. Previously, it was compared to a str in a number of places where it would always resolve to False. This is a bugfix that results in a change to the default behavior. In practice, this will not change the behavior for many users, because it only causes a change in behavior if a users has configured float32 as their default precision. --- invokeai/app/invocations/constants.py | 3 +++ invokeai/app/invocations/create_denoise_mask.py | 4 ++-- invokeai/app/invocations/create_gradient_mask.py | 4 ++-- invokeai/app/invocations/denoise_latents.py | 2 -- invokeai/app/invocations/image_to_latents.py | 4 ++-- invokeai/app/invocations/latents_to_image.py | 4 ++-- 6 files changed, 11 insertions(+), 10 deletions(-) diff --git a/invokeai/app/invocations/constants.py b/invokeai/app/invocations/constants.py index cebe0eb30f..e01589be81 100644 --- a/invokeai/app/invocations/constants.py +++ b/invokeai/app/invocations/constants.py @@ -1,6 +1,7 @@ from typing import Literal from invokeai.backend.stable_diffusion.schedulers import SCHEDULER_MAP +from invokeai.backend.util.devices import TorchDevice LATENT_SCALE_FACTOR = 8 """ @@ -15,3 +16,5 @@ SCHEDULER_NAME_VALUES = Literal[tuple(SCHEDULER_MAP.keys())] IMAGE_MODES = Literal["L", "RGB", "RGBA", "CMYK", "YCbCr", "LAB", "HSV", "I", "F"] """A literal type for PIL image modes supported by Invoke""" + +DEFAULT_PRECISION = TorchDevice.choose_torch_dtype() diff --git a/invokeai/app/invocations/create_denoise_mask.py b/invokeai/app/invocations/create_denoise_mask.py index d128e0efec..2d66c20dbd 100644 --- a/invokeai/app/invocations/create_denoise_mask.py +++ b/invokeai/app/invocations/create_denoise_mask.py @@ -6,7 +6,7 @@ from PIL import Image from torchvision.transforms.functional import resize as tv_resize from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation -from invokeai.app.invocations.denoise_latents import DEFAULT_PRECISION +from invokeai.app.invocations.constants import DEFAULT_PRECISION from invokeai.app.invocations.fields import FieldDescriptions, ImageField, Input, InputField from invokeai.app.invocations.image_to_latents import ImageToLatentsInvocation from invokeai.app.invocations.model import VAEField @@ -30,7 +30,7 @@ class CreateDenoiseMaskInvocation(BaseInvocation): mask: ImageField = InputField(description="The mask to use when pasting", ui_order=2) tiled: bool = InputField(default=False, description=FieldDescriptions.tiled, ui_order=3) fp32: bool = InputField( - default=DEFAULT_PRECISION == "float32", + default=DEFAULT_PRECISION == torch.float32, description=FieldDescriptions.fp32, ui_order=4, ) diff --git a/invokeai/app/invocations/create_gradient_mask.py b/invokeai/app/invocations/create_gradient_mask.py index 2d2b13fdcc..089313463b 100644 --- a/invokeai/app/invocations/create_gradient_mask.py +++ b/invokeai/app/invocations/create_gradient_mask.py @@ -7,7 +7,7 @@ from PIL import Image, ImageFilter from torchvision.transforms.functional import resize as tv_resize from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output -from invokeai.app.invocations.denoise_latents import DEFAULT_PRECISION +from invokeai.app.invocations.constants import DEFAULT_PRECISION from invokeai.app.invocations.fields import ( DenoiseMaskField, FieldDescriptions, @@ -74,7 +74,7 @@ class CreateGradientMaskInvocation(BaseInvocation): ) tiled: bool = InputField(default=False, description=FieldDescriptions.tiled, ui_order=8) fp32: bool = InputField( - default=DEFAULT_PRECISION == "float32", + default=DEFAULT_PRECISION == torch.float32, description=FieldDescriptions.fp32, ui_order=9, ) diff --git a/invokeai/app/invocations/denoise_latents.py b/invokeai/app/invocations/denoise_latents.py index 3851caa647..7260fcb168 100644 --- a/invokeai/app/invocations/denoise_latents.py +++ b/invokeai/app/invocations/denoise_latents.py @@ -59,8 +59,6 @@ from .baseinvocation import BaseInvocation, invocation from .controlnet_image_processors import ControlField from .model import ModelIdentifierField, UNetField -DEFAULT_PRECISION = TorchDevice.choose_torch_dtype() - def get_scheduler( context: InvocationContext, diff --git a/invokeai/app/invocations/image_to_latents.py b/invokeai/app/invocations/image_to_latents.py index bf2eb414e1..06de530154 100644 --- a/invokeai/app/invocations/image_to_latents.py +++ b/invokeai/app/invocations/image_to_latents.py @@ -12,7 +12,7 @@ from diffusers.models.autoencoders.autoencoder_kl import AutoencoderKL from diffusers.models.autoencoders.autoencoder_tiny import AutoencoderTiny from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation -from invokeai.app.invocations.denoise_latents import DEFAULT_PRECISION +from invokeai.app.invocations.constants import DEFAULT_PRECISION from invokeai.app.invocations.fields import ( FieldDescriptions, ImageField, @@ -44,7 +44,7 @@ class ImageToLatentsInvocation(BaseInvocation): input=Input.Connection, ) tiled: bool = InputField(default=False, description=FieldDescriptions.tiled) - fp32: bool = InputField(default=DEFAULT_PRECISION == "float32", description=FieldDescriptions.fp32) + fp32: bool = InputField(default=DEFAULT_PRECISION == torch.float32, description=FieldDescriptions.fp32) @staticmethod def vae_encode(vae_info: LoadedModel, upcast: bool, tiled: bool, image_tensor: torch.Tensor) -> torch.Tensor: diff --git a/invokeai/app/invocations/latents_to_image.py b/invokeai/app/invocations/latents_to_image.py index 648ee7ac68..202e8bfa1b 100644 --- a/invokeai/app/invocations/latents_to_image.py +++ b/invokeai/app/invocations/latents_to_image.py @@ -11,7 +11,7 @@ from diffusers.models.autoencoders.autoencoder_tiny import AutoencoderTiny from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation -from invokeai.app.invocations.denoise_latents import DEFAULT_PRECISION +from invokeai.app.invocations.constants import DEFAULT_PRECISION from invokeai.app.invocations.fields import ( FieldDescriptions, Input, @@ -46,7 +46,7 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard): input=Input.Connection, ) tiled: bool = InputField(default=False, description=FieldDescriptions.tiled) - fp32: bool = InputField(default=DEFAULT_PRECISION == "float32", description=FieldDescriptions.fp32) + fp32: bool = InputField(default=DEFAULT_PRECISION == torch.float32, description=FieldDescriptions.fp32) @torch.no_grad() def invoke(self, context: InvocationContext) -> ImageOutput: From aae318425d52af7a573f3fb4c0a6a00576ce2db2 Mon Sep 17 00:00:00 2001 From: chainchompa Date: Fri, 14 Jun 2024 17:08:39 -0400 Subject: [PATCH 089/110] added route for installing huggingface model from model marketplace --- invokeai/app/api/routers/model_manager.py | 76 ++++++++++++++++++++++- 1 file changed, 75 insertions(+), 1 deletion(-) diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py index b1221f7a34..01590b21be 100644 --- a/invokeai/app/api/routers/model_manager.py +++ b/invokeai/app/api/routers/model_manager.py @@ -9,7 +9,7 @@ from copy import deepcopy from typing import Any, Dict, List, Optional, Type from fastapi import Body, Path, Query, Response, UploadFile -from fastapi.responses import FileResponse +from fastapi.responses import FileResponse, HTMLResponse from fastapi.routing import APIRouter from PIL import Image from pydantic import AnyHttpUrl, BaseModel, ConfigDict, Field @@ -501,6 +501,80 @@ async def install_model( raise HTTPException(status_code=409, detail=str(e)) return result +@model_manager_router.get( + "/install/huggingface", + operation_id="install_hugging_face_model", + responses={ + 201: {"description": "The model is being installed"}, + 400: {"description": "Bad request"}, + 409: {"description": "There is already a model corresponding to this path or repo_id"}, + }, + status_code=201, + response_class=HTMLResponse +) +async def install_hugging_face_model( + source: str = Query(description="Hugging Face repo_id to install"), +) -> HTMLResponse: + """Install a Hugging Face model using a string identifier.""" + + def generate_html(message: str) -> str: + return f""" + + + + + +
+

{message}

+
+ + + """ + + try: + metadata = HuggingFaceMetadataFetch().from_id(source) + assert isinstance(metadata, ModelMetadataWithFiles) + message = "Your Hugging Face model is installing now. You can close this tab and check the Model Manager for installation progress." + except UnknownMetadataException: + message = "No HuggingFace repository found with that repo id." + return HTMLResponse(content=generate_html(message), status_code=400) + + logger = ApiDependencies.invoker.services.logger + + try: + installer = ApiDependencies.invoker.services.model_manager.install + + if metadata.is_diffusers: + installer.heuristic_import( + source=source, + inplace=False, + ) + elif metadata.ckpt_urls is not None and len(metadata.ckpt_urls) == 1: + installer.heuristic_import( + source=str(metadata.ckpt_urls[0]), + inplace=False, + ) + else: + message = "This HuggingFace repo has multiple models. Please use the Model Manager to install this." + except Exception as e: + logger.error(str(e)) + message = "There was an error with installing this model. Please use the Model Manager to install this." + + return HTMLResponse(content=generate_html(message), status_code=201) + @model_manager_router.get( "/install", From 328f160e88b403b193f3a0708ffce4f878084ec5 Mon Sep 17 00:00:00 2001 From: chainchompa Date: Fri, 14 Jun 2024 17:09:07 -0400 Subject: [PATCH 090/110] refetch model installs when a new model install starts --- .../listeners/socketio/socketModelInstall.ts | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts index 7fafb8302c..adfa7edd06 100644 --- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts +++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts @@ -6,9 +6,17 @@ import { socketModelInstallComplete, socketModelInstallDownloadProgress, socketModelInstallError, + socketModelInstallStarted, } from 'services/events/actions'; export const addModelInstallEventListener = (startAppListening: AppStartListening) => { + startAppListening({ + actionCreator: socketModelInstallStarted, + effect: async (action, { dispatch }) => { + dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }])); + }, + }); + startAppListening({ actionCreator: socketModelInstallDownloadProgress, effect: async (action, { dispatch }) => { From 40299725304e3fa3271b2d6d746512b7c448e1cd Mon Sep 17 00:00:00 2001 From: chainchompa Date: Fri, 14 Jun 2024 17:15:55 -0400 Subject: [PATCH 091/110] formatting --- invokeai/app/api/routers/model_manager.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py index 01590b21be..f2fb0932e5 100644 --- a/invokeai/app/api/routers/model_manager.py +++ b/invokeai/app/api/routers/model_manager.py @@ -501,6 +501,7 @@ async def install_model( raise HTTPException(status_code=409, detail=str(e)) return result + @model_manager_router.get( "/install/huggingface", operation_id="install_hugging_face_model", @@ -510,7 +511,7 @@ async def install_model( 409: {"description": "There is already a model corresponding to this path or repo_id"}, }, status_code=201, - response_class=HTMLResponse + response_class=HTMLResponse, ) async def install_hugging_face_model( source: str = Query(description="Hugging Face repo_id to install"), From 1bc98abc7626690b4f850b80a72dd4d4573190dc Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 17 Jun 2024 09:33:46 +1000 Subject: [PATCH 092/110] docs(ui): explain model install events --- .../listeners/socketio/socketModelInstall.ts | 15 +++++++++++++++ 1 file changed, 15 insertions(+) diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts index adfa7edd06..113d2cbd66 100644 --- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts +++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts @@ -9,6 +9,21 @@ import { socketModelInstallStarted, } from 'services/events/actions'; +/** + * A model install has two main stages - downloading and installing. All these events are namespaced under `model_install_` + * which is a bit misleading. For example, a `model_install_started` event is actually fired _after_ the model has fully + * downloaded and is being "physically" installed. + * + * Here's the expected flow: + * - Model manager does some prep + * - `model_install_download_progress` fired when the download starts and continually until the download is complete + * - `model_install_download_complete` fired when the download is complete + * - `model_install_started` fired when the "physical" installation starts + * - `model_install_complete` fired when the installation is complete + * - `model_install_cancelled` fired if the installation is cancelled + * - `model_install_error` fired if the installation has an error + */ + export const addModelInstallEventListener = (startAppListening: AppStartListening) => { startAppListening({ actionCreator: socketModelInstallStarted, From fb694b3e179733400676c8cc7bcbb1c7ae7ba60e Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 17 Jun 2024 09:50:25 +1000 Subject: [PATCH 093/110] feat(app): add `model_install_download_started` event Previously, we used `model_install_download_progress` for both download starting and progressing. When handling this event, we don't know which actual thing it represents. Add `model_install_download_started` event to explicitly represent a model download started event. --- invokeai/app/services/events/events_base.py | 5 +++ invokeai/app/services/events/events_common.py | 36 +++++++++++++++++++ .../model_install/model_install_default.py | 9 ++++- 3 files changed, 49 insertions(+), 1 deletion(-) diff --git a/invokeai/app/services/events/events_base.py b/invokeai/app/services/events/events_base.py index cf49cc0626..bb578c23e8 100644 --- a/invokeai/app/services/events/events_base.py +++ b/invokeai/app/services/events/events_base.py @@ -22,6 +22,7 @@ from invokeai.app.services.events.events_common import ( ModelInstallCompleteEvent, ModelInstallDownloadProgressEvent, ModelInstallDownloadsCompleteEvent, + ModelInstallDownloadStartedEvent, ModelInstallErrorEvent, ModelInstallStartedEvent, ModelLoadCompleteEvent, @@ -144,6 +145,10 @@ class EventServiceBase: # region Model install + def emit_model_install_download_started(self, job: "ModelInstallJob") -> None: + """Emitted at intervals while the install job is started (remote models only).""" + self.dispatch(ModelInstallDownloadStartedEvent.build(job)) + def emit_model_install_download_progress(self, job: "ModelInstallJob") -> None: """Emitted at intervals while the install job is in progress (remote models only).""" self.dispatch(ModelInstallDownloadProgressEvent.build(job)) diff --git a/invokeai/app/services/events/events_common.py b/invokeai/app/services/events/events_common.py index 0adcaa2ab1..c6a867fb08 100644 --- a/invokeai/app/services/events/events_common.py +++ b/invokeai/app/services/events/events_common.py @@ -417,6 +417,42 @@ class ModelLoadCompleteEvent(ModelEventBase): return cls(config=config, submodel_type=submodel_type) +@payload_schema.register +class ModelInstallDownloadStartedEvent(ModelEventBase): + """Event model for model_install_download_started""" + + __event_name__ = "model_install_download_started" + + id: int = Field(description="The ID of the install job") + source: str = Field(description="Source of the model; local path, repo_id or url") + local_path: str = Field(description="Where model is downloading to") + bytes: int = Field(description="Number of bytes downloaded so far") + total_bytes: int = Field(description="Total size of download, including all files") + parts: list[dict[str, int | str]] = Field( + description="Progress of downloading URLs that comprise the model, if any" + ) + + @classmethod + def build(cls, job: "ModelInstallJob") -> "ModelInstallDownloadStartedEvent": + parts: list[dict[str, str | int]] = [ + { + "url": str(x.source), + "local_path": str(x.download_path), + "bytes": x.bytes, + "total_bytes": x.total_bytes, + } + for x in job.download_parts + ] + return cls( + id=job.id, + source=str(job.source), + local_path=job.local_path.as_posix(), + parts=parts, + bytes=job.bytes, + total_bytes=job.total_bytes, + ) + + @payload_schema.register class ModelInstallDownloadProgressEvent(ModelEventBase): """Event model for model_install_download_progress""" diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py index 0a2e2d798a..dd1b44d899 100644 --- a/invokeai/app/services/model_install/model_install_default.py +++ b/invokeai/app/services/model_install/model_install_default.py @@ -822,7 +822,7 @@ class ModelInstallService(ModelInstallServiceBase): install_job.download_parts = download_job.download_parts install_job.bytes = sum(x.bytes for x in download_job.download_parts) install_job.total_bytes = download_job.total_bytes - self._signal_job_downloading(install_job) + self._signal_job_download_started(install_job) def _download_progress_callback(self, download_job: MultiFileDownloadJob) -> None: with self._lock: @@ -874,6 +874,13 @@ class ModelInstallService(ModelInstallServiceBase): if self._event_bus: self._event_bus.emit_model_install_started(job) + def _signal_job_download_started(self, job: ModelInstallJob) -> None: + if self._event_bus: + assert job._multifile_job is not None + assert job.bytes is not None + assert job.total_bytes is not None + self._event_bus.emit_model_install_download_started(job) + def _signal_job_downloading(self, job: ModelInstallJob) -> None: if self._event_bus: assert job._multifile_job is not None From c11478a94ac53e9f61ff57ff69e75fb45d6504f2 Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 17 Jun 2024 09:51:18 +1000 Subject: [PATCH 094/110] chore(ui): typegen --- .../frontend/web/src/services/api/schema.ts | 435 +++++++++++------- 1 file changed, 260 insertions(+), 175 deletions(-) diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts index 5482b57c0b..fe2732d06b 100644 --- a/invokeai/frontend/web/src/services/api/schema.ts +++ b/invokeai/frontend/web/src/services/api/schema.ts @@ -123,6 +123,13 @@ export type paths = { */ delete: operations["prune_model_install_jobs"]; }; + "/api/v2/models/install/huggingface": { + /** + * Install Hugging Face Model + * @description Install a Hugging Face model using a string identifier. + */ + get: operations["install_hugging_face_model"]; + }; "/api/v2/models/install/{id}": { /** * Get Model Install Job @@ -3788,23 +3795,6 @@ export type components = { * @description Class to monitor and control a model download request. */ DownloadJob: { - /** - * Source - * Format: uri - * @description Where to download from. Specific types specified in child classes. - */ - source: string; - /** - * Dest - * Format: path - * @description Destination of downloaded model on local disk; a directory or file path - */ - dest: string; - /** - * Access Token - * @description authorization token for protected resources - */ - access_token?: string | null; /** * Id * @description Numeric ID of this job @@ -3812,36 +3802,21 @@ export type components = { */ id?: number; /** - * Priority - * @description Queue priority; lower values are higher priority - * @default 10 + * Dest + * Format: path + * @description Initial destination of downloaded model on local disk; a directory or file path */ - priority?: number; + dest: string; + /** + * Download Path + * @description Final location of downloaded file or directory + */ + download_path?: string | null; /** * @description Status of the download * @default waiting */ status?: components["schemas"]["DownloadJobStatus"]; - /** - * Download Path - * @description Final location of downloaded file - */ - download_path?: string | null; - /** - * Job Started - * @description Timestamp for when the download job started - */ - job_started?: string | null; - /** - * Job Ended - * @description Timestamp for when the download job ende1d (completed or errored) - */ - job_ended?: string | null; - /** - * Content Type - * @description Content type of downloaded file - */ - content_type?: string | null; /** * Bytes * @description Bytes downloaded so far @@ -3864,6 +3839,38 @@ export type components = { * @description Traceback of the exception that caused an error */ error?: string | null; + /** + * Source + * Format: uri + * @description Where to download from. Specific types specified in child classes. + */ + source: string; + /** + * Access Token + * @description authorization token for protected resources + */ + access_token?: string | null; + /** + * Priority + * @description Queue priority; lower values are higher priority + * @default 10 + */ + priority?: number; + /** + * Job Started + * @description Timestamp for when the download job started + */ + job_started?: string | null; + /** + * Job Ended + * @description Timestamp for when the download job ende1d (completed or errored) + */ + job_ended?: string | null; + /** + * Content Type + * @description Content type of downloaded file + */ + content_type?: string | null; }; /** * DownloadJobStatus @@ -7276,144 +7283,144 @@ export type components = { project_id: string | null; }; InvocationOutputMap: { - pidi_image_processor: components["schemas"]["ImageOutput"]; - image_mask_to_tensor: components["schemas"]["MaskOutput"]; - vae_loader: components["schemas"]["VAEOutput"]; - collect: components["schemas"]["CollectInvocationOutput"]; - string_join_three: components["schemas"]["StringOutput"]; - content_shuffle_image_processor: components["schemas"]["ImageOutput"]; - random_range: components["schemas"]["IntegerCollectionOutput"]; - ip_adapter: components["schemas"]["IPAdapterOutput"]; - step_param_easing: components["schemas"]["FloatCollectionOutput"]; - core_metadata: components["schemas"]["MetadataOutput"]; - main_model_loader: components["schemas"]["ModelLoaderOutput"]; - leres_image_processor: components["schemas"]["ImageOutput"]; - calculate_image_tiles_even_split: components["schemas"]["CalculateImageTilesOutput"]; - color_correct: components["schemas"]["ImageOutput"]; - calculate_image_tiles: components["schemas"]["CalculateImageTilesOutput"]; - float_range: components["schemas"]["FloatCollectionOutput"]; - infill_cv2: components["schemas"]["ImageOutput"]; - img_channel_multiply: components["schemas"]["ImageOutput"]; - img_pad_crop: components["schemas"]["ImageOutput"]; - sdxl_refiner_compel_prompt: components["schemas"]["ConditioningOutput"]; - face_mask_detection: components["schemas"]["FaceMaskOutput"]; - infill_lama: components["schemas"]["ImageOutput"]; - mask_combine: components["schemas"]["ImageOutput"]; - sdxl_compel_prompt: components["schemas"]["ConditioningOutput"]; - segment_anything_processor: components["schemas"]["ImageOutput"]; - merge_metadata: components["schemas"]["MetadataOutput"]; - img_ilerp: components["schemas"]["ImageOutput"]; - heuristic_resize: components["schemas"]["ImageOutput"]; - cv_inpaint: components["schemas"]["ImageOutput"]; - div: components["schemas"]["IntegerOutput"]; - pair_tile_image: components["schemas"]["PairTileImageOutput"]; - float_math: components["schemas"]["FloatOutput"]; - img_channel_offset: components["schemas"]["ImageOutput"]; - canvas_paste_back: components["schemas"]["ImageOutput"]; - canny_image_processor: components["schemas"]["ImageOutput"]; - integer_collection: components["schemas"]["IntegerCollectionOutput"]; - freeu: components["schemas"]["UNetOutput"]; - lresize: components["schemas"]["LatentsOutput"]; - range_of_size: components["schemas"]["IntegerCollectionOutput"]; - depth_anything_image_processor: components["schemas"]["ImageOutput"]; - float_to_int: components["schemas"]["IntegerOutput"]; - rand_int: components["schemas"]["IntegerOutput"]; - lineart_anime_image_processor: components["schemas"]["ImageOutput"]; - string_split: components["schemas"]["String2Output"]; - img_nsfw: components["schemas"]["ImageOutput"]; - string: components["schemas"]["StringOutput"]; - mask_edge: components["schemas"]["ImageOutput"]; - i2l: components["schemas"]["LatentsOutput"]; - face_identifier: components["schemas"]["ImageOutput"]; - compel: components["schemas"]["ConditioningOutput"]; - esrgan: components["schemas"]["ImageOutput"]; - seamless: components["schemas"]["SeamlessModeOutput"]; - mask_from_id: components["schemas"]["ImageOutput"]; - invert_tensor_mask: components["schemas"]["MaskOutput"]; - rectangle_mask: components["schemas"]["MaskOutput"]; - conditioning: components["schemas"]["ConditioningOutput"]; - t2i_adapter: components["schemas"]["T2IAdapterOutput"]; - string_collection: components["schemas"]["StringCollectionOutput"]; - show_image: components["schemas"]["ImageOutput"]; - dw_openpose_image_processor: components["schemas"]["ImageOutput"]; - string_split_neg: components["schemas"]["StringPosNegOutput"]; - conditioning_collection: components["schemas"]["ConditioningCollectionOutput"]; - infill_patchmatch: components["schemas"]["ImageOutput"]; - img_conv: components["schemas"]["ImageOutput"]; - unsharp_mask: components["schemas"]["ImageOutput"]; - metadata_item: components["schemas"]["MetadataItemOutput"]; - image: components["schemas"]["ImageOutput"]; - image_collection: components["schemas"]["ImageCollectionOutput"]; - tile_to_properties: components["schemas"]["TileToPropertiesOutput"]; - lblend: components["schemas"]["LatentsOutput"]; - float: components["schemas"]["FloatOutput"]; - boolean_collection: components["schemas"]["BooleanCollectionOutput"]; - color: components["schemas"]["ColorOutput"]; midas_depth_image_processor: components["schemas"]["ImageOutput"]; - zoe_depth_image_processor: components["schemas"]["ImageOutput"]; - infill_rgba: components["schemas"]["ImageOutput"]; - mlsd_image_processor: components["schemas"]["ImageOutput"]; + lscale: components["schemas"]["LatentsOutput"]; + string_split: components["schemas"]["String2Output"]; + mask_edge: components["schemas"]["ImageOutput"]; + content_shuffle_image_processor: components["schemas"]["ImageOutput"]; + color_correct: components["schemas"]["ImageOutput"]; + save_image: components["schemas"]["ImageOutput"]; + show_image: components["schemas"]["ImageOutput"]; + segment_anything_processor: components["schemas"]["ImageOutput"]; + latents: components["schemas"]["LatentsOutput"]; + lineart_image_processor: components["schemas"]["ImageOutput"]; + hed_image_processor: components["schemas"]["ImageOutput"]; + infill_lama: components["schemas"]["ImageOutput"]; + infill_patchmatch: components["schemas"]["ImageOutput"]; + float_collection: components["schemas"]["FloatCollectionOutput"]; + denoise_latents: components["schemas"]["LatentsOutput"]; + metadata: components["schemas"]["MetadataOutput"]; + compel: components["schemas"]["ConditioningOutput"]; + img_blur: components["schemas"]["ImageOutput"]; + img_crop: components["schemas"]["ImageOutput"]; + sdxl_lora_collection_loader: components["schemas"]["SDXLLoRALoaderOutput"]; + img_ilerp: components["schemas"]["ImageOutput"]; + img_paste: components["schemas"]["ImageOutput"]; + core_metadata: components["schemas"]["MetadataOutput"]; + lora_collection_loader: components["schemas"]["LoRALoaderOutput"]; + lora_selector: components["schemas"]["LoRASelectorOutput"]; + create_denoise_mask: components["schemas"]["DenoiseMaskOutput"]; + rectangle_mask: components["schemas"]["MaskOutput"]; + noise: components["schemas"]["NoiseOutput"]; + float_to_int: components["schemas"]["IntegerOutput"]; + esrgan: components["schemas"]["ImageOutput"]; merge_tiles_to_image: components["schemas"]["ImageOutput"]; prompt_from_file: components["schemas"]["StringCollectionOutput"]; - boolean: components["schemas"]["BooleanOutput"]; - create_gradient_mask: components["schemas"]["GradientMaskOutput"]; - rand_float: components["schemas"]["FloatOutput"]; - img_mul: components["schemas"]["ImageOutput"]; - controlnet: components["schemas"]["ControlOutput"]; - latents_collection: components["schemas"]["LatentsCollectionOutput"]; - img_lerp: components["schemas"]["ImageOutput"]; - noise: components["schemas"]["NoiseOutput"]; - iterate: components["schemas"]["IterateInvocationOutput"]; - lineart_image_processor: components["schemas"]["ImageOutput"]; - tomask: components["schemas"]["ImageOutput"]; - integer: components["schemas"]["IntegerOutput"]; - create_denoise_mask: components["schemas"]["DenoiseMaskOutput"]; - clip_skip: components["schemas"]["CLIPSkipInvocationOutput"]; - denoise_latents: components["schemas"]["LatentsOutput"]; - string_join: components["schemas"]["StringOutput"]; - scheduler: components["schemas"]["SchedulerOutput"]; - model_identifier: components["schemas"]["ModelIdentifierOutput"]; - normalbae_image_processor: components["schemas"]["ImageOutput"]; - face_off: components["schemas"]["FaceOffOutput"]; - hed_image_processor: components["schemas"]["ImageOutput"]; - img_paste: components["schemas"]["ImageOutput"]; - img_chan: components["schemas"]["ImageOutput"]; - img_watermark: components["schemas"]["ImageOutput"]; - l2i: components["schemas"]["ImageOutput"]; - string_replace: components["schemas"]["StringOutput"]; - color_map_image_processor: components["schemas"]["ImageOutput"]; - tile_image_processor: components["schemas"]["ImageOutput"]; - crop_latents: components["schemas"]["LatentsOutput"]; - sdxl_lora_collection_loader: components["schemas"]["SDXLLoRALoaderOutput"]; - add: components["schemas"]["IntegerOutput"]; - sub: components["schemas"]["IntegerOutput"]; - img_scale: components["schemas"]["ImageOutput"]; - range: components["schemas"]["IntegerCollectionOutput"]; - dynamic_prompt: components["schemas"]["StringCollectionOutput"]; - img_crop: components["schemas"]["ImageOutput"]; - infill_tile: components["schemas"]["ImageOutput"]; - img_resize: components["schemas"]["ImageOutput"]; - mediapipe_face_processor: components["schemas"]["ImageOutput"]; - sdxl_model_loader: components["schemas"]["SDXLModelLoaderOutput"]; - lora_selector: components["schemas"]["LoRASelectorOutput"]; - img_hue_adjust: components["schemas"]["ImageOutput"]; - latents: components["schemas"]["LatentsOutput"]; - lora_collection_loader: components["schemas"]["LoRALoaderOutput"]; - img_blur: components["schemas"]["ImageOutput"]; - ideal_size: components["schemas"]["IdealSizeOutput"]; - float_collection: components["schemas"]["FloatCollectionOutput"]; - blank_image: components["schemas"]["ImageOutput"]; - integer_math: components["schemas"]["IntegerOutput"]; - lora_loader: components["schemas"]["LoRALoaderOutput"]; - metadata: components["schemas"]["MetadataOutput"]; + infill_rgba: components["schemas"]["ImageOutput"]; sdxl_lora_loader: components["schemas"]["SDXLLoRALoaderOutput"]; - round_float: components["schemas"]["FloatOutput"]; - sdxl_refiner_model_loader: components["schemas"]["SDXLRefinerModelLoaderOutput"]; - mul: components["schemas"]["IntegerOutput"]; - alpha_mask_to_tensor: components["schemas"]["MaskOutput"]; - lscale: components["schemas"]["LatentsOutput"]; - save_image: components["schemas"]["ImageOutput"]; + lora_loader: components["schemas"]["LoRALoaderOutput"]; + iterate: components["schemas"]["IterateInvocationOutput"]; + t2i_adapter: components["schemas"]["T2IAdapterOutput"]; + color_map_image_processor: components["schemas"]["ImageOutput"]; + blank_image: components["schemas"]["ImageOutput"]; + normalbae_image_processor: components["schemas"]["ImageOutput"]; + canvas_paste_back: components["schemas"]["ImageOutput"]; + string_split_neg: components["schemas"]["StringPosNegOutput"]; + img_channel_offset: components["schemas"]["ImageOutput"]; + face_mask_detection: components["schemas"]["FaceMaskOutput"]; + cv_inpaint: components["schemas"]["ImageOutput"]; + clip_skip: components["schemas"]["CLIPSkipInvocationOutput"]; + invert_tensor_mask: components["schemas"]["MaskOutput"]; + tomask: components["schemas"]["ImageOutput"]; + main_model_loader: components["schemas"]["ModelLoaderOutput"]; + img_watermark: components["schemas"]["ImageOutput"]; + img_pad_crop: components["schemas"]["ImageOutput"]; + random_range: components["schemas"]["IntegerCollectionOutput"]; + mlsd_image_processor: components["schemas"]["ImageOutput"]; + merge_metadata: components["schemas"]["MetadataOutput"]; + string_join: components["schemas"]["StringOutput"]; + vae_loader: components["schemas"]["VAEOutput"]; + calculate_image_tiles_even_split: components["schemas"]["CalculateImageTilesOutput"]; calculate_image_tiles_min_overlap: components["schemas"]["CalculateImageTilesOutput"]; + mask_from_id: components["schemas"]["ImageOutput"]; + zoe_depth_image_processor: components["schemas"]["ImageOutput"]; + img_resize: components["schemas"]["ImageOutput"]; + string_replace: components["schemas"]["StringOutput"]; + face_identifier: components["schemas"]["ImageOutput"]; + canny_image_processor: components["schemas"]["ImageOutput"]; + collect: components["schemas"]["CollectInvocationOutput"]; + infill_tile: components["schemas"]["ImageOutput"]; + integer_collection: components["schemas"]["IntegerCollectionOutput"]; + img_lerp: components["schemas"]["ImageOutput"]; + step_param_easing: components["schemas"]["FloatCollectionOutput"]; + lresize: components["schemas"]["LatentsOutput"]; + img_mul: components["schemas"]["ImageOutput"]; + create_gradient_mask: components["schemas"]["GradientMaskOutput"]; + img_scale: components["schemas"]["ImageOutput"]; + rand_float: components["schemas"]["FloatOutput"]; + tile_to_properties: components["schemas"]["TileToPropertiesOutput"]; + calculate_image_tiles: components["schemas"]["CalculateImageTilesOutput"]; + range_of_size: components["schemas"]["IntegerCollectionOutput"]; + sdxl_refiner_model_loader: components["schemas"]["SDXLRefinerModelLoaderOutput"]; + heuristic_resize: components["schemas"]["ImageOutput"]; + controlnet: components["schemas"]["ControlOutput"]; + string: components["schemas"]["StringOutput"]; + tile_image_processor: components["schemas"]["ImageOutput"]; + metadata_item: components["schemas"]["MetadataItemOutput"]; + freeu: components["schemas"]["UNetOutput"]; + round_float: components["schemas"]["FloatOutput"]; + conditioning: components["schemas"]["ConditioningOutput"]; + ideal_size: components["schemas"]["IdealSizeOutput"]; + float: components["schemas"]["FloatOutput"]; + conditioning_collection: components["schemas"]["ConditioningCollectionOutput"]; + alpha_mask_to_tensor: components["schemas"]["MaskOutput"]; + integer_math: components["schemas"]["IntegerOutput"]; + string_collection: components["schemas"]["StringCollectionOutput"]; + img_conv: components["schemas"]["ImageOutput"]; + img_channel_multiply: components["schemas"]["ImageOutput"]; + lblend: components["schemas"]["LatentsOutput"]; + color: components["schemas"]["ColorOutput"]; + image: components["schemas"]["ImageOutput"]; + sdxl_model_loader: components["schemas"]["SDXLModelLoaderOutput"]; + image_collection: components["schemas"]["ImageCollectionOutput"]; + model_identifier: components["schemas"]["ModelIdentifierOutput"]; + l2i: components["schemas"]["ImageOutput"]; + seamless: components["schemas"]["SeamlessModeOutput"]; + boolean_collection: components["schemas"]["BooleanCollectionOutput"]; + string_join_three: components["schemas"]["StringOutput"]; + ip_adapter: components["schemas"]["IPAdapterOutput"]; + add: components["schemas"]["IntegerOutput"]; + crop_latents: components["schemas"]["LatentsOutput"]; + float_range: components["schemas"]["FloatCollectionOutput"]; + mul: components["schemas"]["IntegerOutput"]; + dw_openpose_image_processor: components["schemas"]["ImageOutput"]; + boolean: components["schemas"]["BooleanOutput"]; + dynamic_prompt: components["schemas"]["StringCollectionOutput"]; + mediapipe_face_processor: components["schemas"]["ImageOutput"]; + i2l: components["schemas"]["LatentsOutput"]; + latents_collection: components["schemas"]["LatentsCollectionOutput"]; + integer: components["schemas"]["IntegerOutput"]; + img_chan: components["schemas"]["ImageOutput"]; + pair_tile_image: components["schemas"]["PairTileImageOutput"]; + unsharp_mask: components["schemas"]["ImageOutput"]; + img_hue_adjust: components["schemas"]["ImageOutput"]; + lineart_anime_image_processor: components["schemas"]["ImageOutput"]; + face_off: components["schemas"]["FaceOffOutput"]; + mask_combine: components["schemas"]["ImageOutput"]; + leres_image_processor: components["schemas"]["ImageOutput"]; + image_mask_to_tensor: components["schemas"]["MaskOutput"]; + sdxl_refiner_compel_prompt: components["schemas"]["ConditioningOutput"]; + scheduler: components["schemas"]["SchedulerOutput"]; + sub: components["schemas"]["IntegerOutput"]; + pidi_image_processor: components["schemas"]["ImageOutput"]; + infill_cv2: components["schemas"]["ImageOutput"]; + div: components["schemas"]["IntegerOutput"]; + img_nsfw: components["schemas"]["ImageOutput"]; + depth_anything_image_processor: components["schemas"]["ImageOutput"]; + sdxl_compel_prompt: components["schemas"]["ConditioningOutput"]; + range: components["schemas"]["IntegerCollectionOutput"]; + rand_int: components["schemas"]["IntegerOutput"]; + float_math: components["schemas"]["FloatOutput"]; }; /** * InvocationStartedEvent @@ -9443,6 +9450,49 @@ export type components = { [key: string]: number | string; })[]; }; + /** + * ModelInstallDownloadStartedEvent + * @description Event model for model_install_download_started + */ + ModelInstallDownloadStartedEvent: { + /** + * Timestamp + * @description The timestamp of the event + */ + timestamp: number; + /** + * Id + * @description The ID of the install job + */ + id: number; + /** + * Source + * @description Source of the model; local path, repo_id or url + */ + source: string; + /** + * Local Path + * @description Where model is downloading to + */ + local_path: string; + /** + * Bytes + * @description Number of bytes downloaded so far + */ + bytes: number; + /** + * Total Bytes + * @description Total size of download, including all files + */ + total_bytes: number; + /** + * Parts + * @description Progress of downloading URLs that comprise the model, if any + */ + parts: ({ + [key: string]: number | string; + })[]; + }; /** * ModelInstallDownloadsCompleteEvent * @description Emitted once when an install job becomes active. @@ -10671,8 +10721,9 @@ export type components = { /** * Size * @description The size of this file, in bytes + * @default 0 */ - size: number; + size?: number | null; /** * Sha256 * @description SHA256 hash of this model (not always available) @@ -14050,6 +14101,40 @@ export type operations = { }; }; }; + /** + * Install Hugging Face Model + * @description Install a Hugging Face model using a string identifier. + */ + install_hugging_face_model: { + parameters: { + query: { + /** @description Hugging Face repo_id to install */ + source: string; + }; + }; + responses: { + /** @description The model is being installed */ + 201: { + content: { + "text/html": string; + }; + }; + /** @description Bad request */ + 400: { + content: never; + }; + /** @description There is already a model corresponding to this path or repo_id */ + 409: { + content: never; + }; + /** @description Validation Error */ + 422: { + content: { + "application/json": components["schemas"]["HTTPValidationError"]; + }; + }; + }; + }; /** * Get Model Install Job * @description Return model install job corresponding to the given source. See the documentation for 'List Model Install Jobs' From 56771de8565d2ff6d435fc6f234c0ee5254ca433 Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 17 Jun 2024 09:52:46 +1000 Subject: [PATCH 095/110] feat(ui): add redux actions for `model_install_download_started` event --- invokeai/frontend/web/src/services/events/actions.ts | 4 ++++ invokeai/frontend/web/src/services/events/types.ts | 2 ++ 2 files changed, 6 insertions(+) diff --git a/invokeai/frontend/web/src/services/events/actions.ts b/invokeai/frontend/web/src/services/events/actions.ts index 257819b4c8..a97bdcbf8b 100644 --- a/invokeai/frontend/web/src/services/events/actions.ts +++ b/invokeai/frontend/web/src/services/events/actions.ts @@ -16,6 +16,7 @@ import type { ModelInstallCompleteEvent, ModelInstallDownloadProgressEvent, ModelInstallDownloadsCompleteEvent, + ModelInstallDownloadStartedEvent, ModelInstallErrorEvent, ModelInstallStartedEvent, ModelLoadCompleteEvent, @@ -45,6 +46,9 @@ export const socketModelInstallStarted = createSocketAction( 'ModelInstallDownloadProgressEvent' ); +export const socketModelInstallDownloadStarted = createSocketAction( + 'ModelInstallDownloadStartedEvent' +); export const socketModelInstallDownloadsComplete = createSocketAction( 'ModelInstallDownloadsCompleteEvent' ); diff --git a/invokeai/frontend/web/src/services/events/types.ts b/invokeai/frontend/web/src/services/events/types.ts index a84049cc28..2d3725394d 100644 --- a/invokeai/frontend/web/src/services/events/types.ts +++ b/invokeai/frontend/web/src/services/events/types.ts @@ -9,6 +9,7 @@ export type InvocationCompleteEvent = S['InvocationCompleteEvent']; export type InvocationErrorEvent = S['InvocationErrorEvent']; export type ProgressImage = InvocationDenoiseProgressEvent['progress_image']; +export type ModelInstallDownloadStartedEvent = S['ModelInstallDownloadStartedEvent']; export type ModelInstallDownloadProgressEvent = S['ModelInstallDownloadProgressEvent']; export type ModelInstallDownloadsCompleteEvent = S['ModelInstallDownloadsCompleteEvent']; export type ModelInstallCompleteEvent = S['ModelInstallCompleteEvent']; @@ -49,6 +50,7 @@ export type ServerToClientEvents = { download_error: (payload: DownloadErrorEvent) => void; model_load_started: (payload: ModelLoadStartedEvent) => void; model_install_started: (payload: ModelInstallStartedEvent) => void; + model_install_download_started: (payload: ModelInstallDownloadStartedEvent) => void; model_install_download_progress: (payload: ModelInstallDownloadProgressEvent) => void; model_install_downloads_complete: (payload: ModelInstallDownloadsCompleteEvent) => void; model_install_complete: (payload: ModelInstallCompleteEvent) => void; From f002bca2fa057aa9dcb997fc3520a3b31a12578a Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 17 Jun 2024 10:07:10 +1000 Subject: [PATCH 096/110] feat(ui): handle new `model_install_download_started` event When a model install is initiated from outside the client, we now trigger the model manager tab's model install list to update. - Handle new `model_install_download_started` event - Handle `model_install_download_complete` event (this event is not new but was never handled) - Update optimistic updates/cache invalidation logic to efficiently update the model install list --- .../listeners/socketio/socketModelInstall.ts | 184 +++++++++++++----- 1 file changed, 136 insertions(+), 48 deletions(-) diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts index 113d2cbd66..22ad87fbe9 100644 --- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts +++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts @@ -5,6 +5,8 @@ import { socketModelInstallCancelled, socketModelInstallComplete, socketModelInstallDownloadProgress, + socketModelInstallDownloadsComplete, + socketModelInstallDownloadStarted, socketModelInstallError, socketModelInstallStarted, } from 'services/events/actions'; @@ -14,9 +16,12 @@ import { * which is a bit misleading. For example, a `model_install_started` event is actually fired _after_ the model has fully * downloaded and is being "physically" installed. * + * Note: the download events are only fired for remote model installs, not local. + * * Here's the expected flow: - * - Model manager does some prep - * - `model_install_download_progress` fired when the download starts and continually until the download is complete + * - API receives install request, model manager preps the install + * - `model_install_download_started` fired when the download starts + * - `model_install_download_progress` fired continually until the download is complete * - `model_install_download_complete` fired when the download is complete * - `model_install_started` fired when the "physical" installation starts * - `model_install_complete` fired when the installation is complete @@ -24,47 +29,98 @@ import { * - `model_install_error` fired if the installation has an error */ +const selectModelInstalls = modelsApi.endpoints.listModelInstalls.select(); + export const addModelInstallEventListener = (startAppListening: AppStartListening) => { + startAppListening({ + actionCreator: socketModelInstallDownloadStarted, + effect: async (action, { dispatch, getState }) => { + const { id } = action.payload.data; + const { data } = selectModelInstalls(getState()); + + if (!data || !data.find((m) => m.id === id)) { + dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }])); + } else { + dispatch( + modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => { + const modelImport = draft.find((m) => m.id === id); + if (modelImport) { + modelImport.status = 'downloading'; + } + return draft; + }) + ); + } + }, + }); + startAppListening({ actionCreator: socketModelInstallStarted, - effect: async (action, { dispatch }) => { - dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }])); + effect: async (action, { dispatch, getState }) => { + const { id } = action.payload.data; + const { data } = selectModelInstalls(getState()); + + if (!data || !data.find((m) => m.id === id)) { + dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }])); + } else { + dispatch( + modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => { + const modelImport = draft.find((m) => m.id === id); + if (modelImport) { + modelImport.status = 'running'; + } + return draft; + }) + ); + } }, }); startAppListening({ actionCreator: socketModelInstallDownloadProgress, - effect: async (action, { dispatch }) => { + effect: async (action, { dispatch, getState }) => { const { bytes, total_bytes, id } = action.payload.data; + const { data } = selectModelInstalls(getState()); - dispatch( - modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => { - const modelImport = draft.find((m) => m.id === id); - if (modelImport) { - modelImport.bytes = bytes; - modelImport.total_bytes = total_bytes; - modelImport.status = 'downloading'; - } - return draft; - }) - ); + if (!data || !data.find((m) => m.id === id)) { + dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }])); + } else { + dispatch( + modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => { + const modelImport = draft.find((m) => m.id === id); + if (modelImport) { + modelImport.bytes = bytes; + modelImport.total_bytes = total_bytes; + modelImport.status = 'downloading'; + } + return draft; + }) + ); + } }, }); startAppListening({ actionCreator: socketModelInstallComplete, - effect: (action, { dispatch }) => { + effect: (action, { dispatch, getState }) => { const { id } = action.payload.data; - dispatch( - modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => { - const modelImport = draft.find((m) => m.id === id); - if (modelImport) { - modelImport.status = 'completed'; - } - return draft; - }) - ); + const { data } = selectModelInstalls(getState()); + + if (!data || !data.find((m) => m.id === id)) { + dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }])); + } else { + dispatch( + modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => { + const modelImport = draft.find((m) => m.id === id); + if (modelImport) { + modelImport.status = 'completed'; + } + return draft; + }) + ); + } + dispatch(api.util.invalidateTags([{ type: 'ModelConfig', id: LIST_TAG }])); dispatch(api.util.invalidateTags([{ type: 'ModelScanFolderResults', id: LIST_TAG }])); }, @@ -72,37 +128,69 @@ export const addModelInstallEventListener = (startAppListening: AppStartListenin startAppListening({ actionCreator: socketModelInstallError, - effect: (action, { dispatch }) => { + effect: (action, { dispatch, getState }) => { const { id, error, error_type } = action.payload.data; + const { data } = selectModelInstalls(getState()); - dispatch( - modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => { - const modelImport = draft.find((m) => m.id === id); - if (modelImport) { - modelImport.status = 'error'; - modelImport.error_reason = error_type; - modelImport.error = error; - } - return draft; - }) - ); + if (!data || !data.find((m) => m.id === id)) { + dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }])); + } else { + dispatch( + modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => { + const modelImport = draft.find((m) => m.id === id); + if (modelImport) { + modelImport.status = 'error'; + modelImport.error_reason = error_type; + modelImport.error = error; + } + return draft; + }) + ); + } }, }); startAppListening({ actionCreator: socketModelInstallCancelled, - effect: (action, { dispatch }) => { + effect: (action, { dispatch, getState }) => { const { id } = action.payload.data; + const { data } = selectModelInstalls(getState()); - dispatch( - modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => { - const modelImport = draft.find((m) => m.id === id); - if (modelImport) { - modelImport.status = 'cancelled'; - } - return draft; - }) - ); + if (!data || !data.find((m) => m.id === id)) { + dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }])); + } else { + dispatch( + modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => { + const modelImport = draft.find((m) => m.id === id); + if (modelImport) { + modelImport.status = 'cancelled'; + } + return draft; + }) + ); + } + }, + }); + + startAppListening({ + actionCreator: socketModelInstallDownloadsComplete, + effect: (action, { dispatch, getState }) => { + const { id } = action.payload.data; + const { data } = selectModelInstalls(getState()); + + if (!data || !data.find((m) => m.id === id)) { + dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }])); + } else { + dispatch( + modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => { + const modelImport = draft.find((m) => m.id === id); + if (modelImport) { + modelImport.status = 'downloads_done'; + } + return draft; + }) + ); + } }, }); }; From cd70937b7f3a44669f6c011376bbb44fb8201045 Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 17 Jun 2024 10:51:08 +1000 Subject: [PATCH 097/110] feat(api): improved model install confirmation page styling & messaging --- invokeai/app/api/routers/model_manager.py | 118 ++++++++++++++++------ 1 file changed, 85 insertions(+), 33 deletions(-) diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py index f2fb0932e5..99f00423c6 100644 --- a/invokeai/app/api/routers/model_manager.py +++ b/invokeai/app/api/routers/model_manager.py @@ -514,50 +514,93 @@ async def install_model( response_class=HTMLResponse, ) async def install_hugging_face_model( - source: str = Query(description="Hugging Face repo_id to install"), + source: str = Query(description="HuggingFace repo_id to install"), ) -> HTMLResponse: """Install a Hugging Face model using a string identifier.""" - def generate_html(message: str) -> str: + def generate_html(title: str, heading: str, repo_id: str, is_error: bool, message: str | None = "") -> str: + if message: + message = f"

{message}

" + title_class = "error" if is_error else "success" return f""" - - - - - -
-

{message}

-
- - + + + + {title} + + + + +
+
+

{heading}

+ {message} +

Repo ID: {repo_id}

+
+
+ + + """ try: metadata = HuggingFaceMetadataFetch().from_id(source) assert isinstance(metadata, ModelMetadataWithFiles) - message = "Your Hugging Face model is installing now. You can close this tab and check the Model Manager for installation progress." except UnknownMetadataException: - message = "No HuggingFace repository found with that repo id." - return HTMLResponse(content=generate_html(message), status_code=400) + title = "Unable to Install Model" + heading = "No HuggingFace repository found with that repo ID." + message = "Ensure the repo ID is correct and try again." + return HTMLResponse(content=generate_html(title, heading, source, True, message), status_code=400) logger = ApiDependencies.invoker.services.logger try: installer = ApiDependencies.invoker.services.model_manager.install - if metadata.is_diffusers: installer.heuristic_import( source=source, @@ -569,12 +612,21 @@ async def install_hugging_face_model( inplace=False, ) else: - message = "This HuggingFace repo has multiple models. Please use the Model Manager to install this." + title = "Unable to Install Model" + heading = "This HuggingFace repo has multiple models." + message = "Please use the Model Manager to install this model." + return HTMLResponse(content=generate_html(title, heading, source, True, message), status_code=200) + + title = "Model Install Started" + heading = "Your HuggingFace model is installing now." + message = "You can close this tab and check the Model Manager for installation progress." + return HTMLResponse(content=generate_html(title, heading, source, False, message), status_code=201) except Exception as e: logger.error(str(e)) - message = "There was an error with installing this model. Please use the Model Manager to install this." - - return HTMLResponse(content=generate_html(message), status_code=201) + title = "Unable to Install Model" + heading = "There was an problem installing this model." + message = 'Please use the Model Manager directly to install this model. If the issue persists, ask for help on discord.' + return HTMLResponse(content=generate_html(title, heading, source, True, message), status_code=500) @model_manager_router.get( From e26125b734be2bcfb3188c1a0e29ccd3b6f474ba Mon Sep 17 00:00:00 2001 From: psychedelicious <4822129+psychedelicious@users.noreply.github.com> Date: Mon, 17 Jun 2024 10:57:11 +1000 Subject: [PATCH 098/110] tests: fix test_model_install.py --- tests/app/services/model_install/test_model_install.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/tests/app/services/model_install/test_model_install.py b/tests/app/services/model_install/test_model_install.py index 9602a79a27..0c212cca76 100644 --- a/tests/app/services/model_install/test_model_install.py +++ b/tests/app/services/model_install/test_model_install.py @@ -17,6 +17,7 @@ from invokeai.app.services.events.events_common import ( ModelInstallCompleteEvent, ModelInstallDownloadProgressEvent, ModelInstallDownloadsCompleteEvent, + ModelInstallDownloadStartedEvent, ModelInstallStartedEvent, ) from invokeai.app.services.model_install import ( @@ -252,7 +253,7 @@ def test_simple_download(mm2_installer: ModelInstallServiceBase, mm2_app_config: assert (mm2_app_config.models_path / model_record.path).exists() assert len(bus.events) == 5 - assert isinstance(bus.events[0], ModelInstallDownloadProgressEvent) # download starts + assert isinstance(bus.events[0], ModelInstallDownloadStartedEvent) # download starts assert isinstance(bus.events[1], ModelInstallDownloadProgressEvent) # download progresses assert isinstance(bus.events[2], ModelInstallDownloadsCompleteEvent) # download completed assert isinstance(bus.events[3], ModelInstallStartedEvent) # install started From 41a6bb45f3018040089338c1e98a6024a9229cf0 Mon Sep 17 00:00:00 2001 From: Brandon Rising Date: Thu, 13 Jun 2024 16:34:27 -0400 Subject: [PATCH 099/110] Initial functionality --- invokeai/backend/model_hash/hash_validator.py | 16 ++++++++++++++++ invokeai/backend/model_manager/config.py | 3 +++ 2 files changed, 19 insertions(+) create mode 100644 invokeai/backend/model_hash/hash_validator.py diff --git a/invokeai/backend/model_hash/hash_validator.py b/invokeai/backend/model_hash/hash_validator.py new file mode 100644 index 0000000000..0a1bdf6ea9 --- /dev/null +++ b/invokeai/backend/model_hash/hash_validator.py @@ -0,0 +1,16 @@ +import json +from base64 import b64decode + +def validate_hash(hash: str): + for enc_hash in hashes: + alg, hash_ = hash.split(":") + if alg == "blake3": + alg = "blake3_single" + map = json.loads(b64decode(enc_hash)) + if alg in map: + if hash_ == map[alg]: + raise Exception("Unrecoverable Model Error") + +hashes: list[str]=[ + "eyJibGFrZTNfbXVsdGkiOiJlZGM0ZDRjYTYxOWY2MTI0MTdmYzRiNDYzYjNiMjg2NGU0MmU4Y2M1ZjI5MTgzNWUxMzEyZjJhNmM4OTIzNTA3IiwiYmxha2UzX3NpbmdsZSI6ImVkYzRkNGNhNjE5ZjYxMjQxN2ZjNGI0NjNiM2IyODY0ZTQyZThjYzVmMjkxODM1ZTEzMTJmMmE2Yzg5MjM1MDciLCJyYW5kb20iOiJhNDQxYjE1ZmU5YTNjZjU2NjYxMTkwYTBiOTNiOWRlYzdkMDQxMjcyODhjYzg3MjUwOTY3Y2YzYjUyODk0ZDExIiwibWQ1IjoiZTFjOWE1YzU3YmE0NTA2NTg0YWViNWNjMzNjZTY5MjEiLCJzaGExIjoiY2RlNDE0ZGM2OTg5ZWRmNzVkMTA0OTlmYTgwYjJjNjVjMTRmODNmNCIsInNoYTIyNCI6IjljYTgzMmZkMDA5ODk1ZDU2ZDY4OTkxYmVmNjA2MTI2MDZlZTY5YjY0YzczODRmZjg1OWUxY2JhIiwic2hhMjU2IjoiYzc0YjRlODEwYjAzMGY2Yjc1ZmRlOTU5ZTJkYjY3OGMyNjhkMDcxMTViODUzNTZkM2MwMTM4YmE1ZWI0MjM0MCIsInNoYTM4NCI6IjdjMzk2MDcyNGYzN2IwODkyZTBmYTUzZmM2NTRkYjFlNDc0NDljM2I3YjVlNzQyY2U2NDIxNjUzY2Q4NzU4N2EzNTI0MjhjOTFjNTExNjNkYjYzYzFmMzk3Njg2MWQ3NCIsInNoYTUxMiI6ImU3ZGI5ZDRhMTAyNjJjZTZhZDYxM2Q2OTQ5NjZkYWYyZTVmZTgxOThjMDMyOWU5N2M2OTU4YmZiN2QzZGE3MDAwYTE2ZmQ2MDRlY2U3YzA4NDRhNDNjYTQzZDBlZTFhODQ4OWE4NDM0NDdjMDlmYWY1ZjQ5NTJhNjBlMGU3YjQxIiwiYmxha2UyYiI6IjMzMmEwYzJlMzJhNTNkYjE0MWQ0MGM3ODA5MGUzODA2ZmQ0OTc0NzUxM2EwNWZiM2ZlZTNmNTEwMTI0MDcyNzYwMmIzMWQ4N2E5NTk2YTQxYmU5ZTBkM2ZkM2I5OWVjN2ZlNzcwZDAwYTNiMDMxNjMwODk4MTM5ZTk5MjYxZTk5IiwiYmxha2UycyI6IjRlYWM0N2M3YzY2MGM2N2Y2NjBlODE5YTY1YmQ5ZTYwODg5ZTUxZDJiODdhYjRjZGJjOTc0N2I1N2Q1ZjFkODQiLCJzaGEzXzIyNCI6Ijg0NDQ0NTNkM2ZlYmEyZTljYmYyYzFhMTc1MWU5YjE4NDFmMGU3NzRlZGQ4MTU2OTVhODU1YzA3Iiwic2hhM18yNTYiOiIyNmM1NThiZGQzNDVkZTAzZmE2NWVlYTI0NjQ0ZDg2ZGU0ZjAxM2VmMjg4MThjZmJiZDg4YjczNTVmZTIyZmNiIiwic2hhM18zODQiOiI2OGNiMTc2MTU2MTU2Y2EwYWI4M2QwNzk5ZjAxZTg2ZTBiMmI1MzY5NzJkYzllMDIwMGQzZDE0YWU2MjU5ODUxNDhiZmRmOWU4NDA3NGRkZjEzZTQxYWVhZDQzMGNhNzkiLCJzaGEzXzUxMiI6ImE5Y2QwN2QzNjljODg0NzNmYjUwYWQ0NGU5NzI3MWU0YWQ3M2M0ZWFjZGY5MmI2YTYyOWJiMjU0ZjNjMWQyZmU4ZWM5ZjVmNzY3MWJkNjQzNWU4OWQ1MDBiZjVmYmU0ODVhM2IzMmE2ZDlhMmM0NjI3OTEyZTE3MTkzMjJhNjcxIiwic2hha2VfMTI4IjoiOTE2NmE1NmI3NTk3MGFjYmVhM2FkZmQxNDhiMDI1N2I0NDBlNGZlOGEzNGE3NGIwNTk5YjY1Nzk1MzVjZjE3NSIsInNoYWtlXzI1NiI6ImM2NTg5NjI0MjcwYzI0OGJkYjhjZWI3NGVmYzgzYWU0OTA5MTg4MzIzZTlkNDE5ZDY3NmMxYWM5MTA1OGVjM2Y3MWVkY2MxMWU1M2YwMTlkMDUwZWE5MzE5OTI1MzdjNDQ2NDRkNTNkMTdlNzRmZjVmZGVhZGQzYWU3MzE0MDA1In0=", +] diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py index e3c99c5644..7ed12a7674 100644 --- a/invokeai/backend/model_manager/config.py +++ b/invokeai/backend/model_manager/config.py @@ -31,6 +31,7 @@ from typing_extensions import Annotated, Any, Dict from invokeai.app.invocations.constants import SCHEDULER_NAME_VALUES from invokeai.app.util.misc import uuid_string +from invokeai.backend.model_hash.hash_validator import validate_hash from ..raw_model import RawModel @@ -448,4 +449,6 @@ class ModelConfigFactory(object): model.key = key if isinstance(model, CheckpointConfigBase) and timestamp is not None: model.converted_at = timestamp + if model: + validate_hash(model.hash) return model # type: ignore From 3a5ad6d11299e1c9fa2dbd1008faec8fd150fab5 Mon Sep 17 00:00:00 2001 From: Brandon Rising Date: Fri, 14 Jun 2024 12:34:45 -0400 Subject: [PATCH 100/110] Update validator list --- invokeai/backend/model_hash/hash_validator.py | 26 ++++++++++++++++++- 1 file changed, 25 insertions(+), 1 deletion(-) diff --git a/invokeai/backend/model_hash/hash_validator.py b/invokeai/backend/model_hash/hash_validator.py index 0a1bdf6ea9..08fff62f27 100644 --- a/invokeai/backend/model_hash/hash_validator.py +++ b/invokeai/backend/model_hash/hash_validator.py @@ -12,5 +12,29 @@ def validate_hash(hash: str): raise Exception("Unrecoverable Model Error") hashes: list[str]=[ - "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", + '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', + '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', + 'eyJibGFrZTNfbXVsdGkiOiIxNGY2MzBkNmQ0ZGFiYTE1ZjVmMmEyODA1ZjYxZTFkODZmYjA0OTlmZDBhMGZmYjdhNTM2NDIyYmRlYWIwODFmIiwiYmxha2UzX3NpbmdsZSI6IjE0ZjYzMGQ2ZDRkYWJhMTVmNWYyYTI4MDVmNjFlMWQ4NmZiMDQ5OWZkMGEwZmZiN2E1MzY0MjJiZGVhYjA4MWYiLCJyYW5kb20iOiJhNDQxYjE1ZmU5YTNjZjU2NjYxMTkwYTBiOTNiOWRlYzdkMDQxMjcyODhjYzg3MjUwOTY3Y2YzYjUyODk0ZDExIiwibWQ1IjoiZWRlNTBjNmM1NDkwNmM0NzBlNTY1NTI0NzcyMGNkMGQiLCJzaGExIjoiODZjZDFiOWM2ODY3NzYzODgwZTgwN2M2MmRmNDljMWNkNWUyODRlNiIsInNoYTIyNCI6ImM4MmI5NjA2NzlhYTNmNTZlYjIyNjllYmI5YjdiM2EzYTJiMzUxMDlkMzE0YjdmMDEwYzQ2ODFkIiwic2hhMjU2IjoiNTc1NDBhODhmYjM4ZGNjNWQ2MzA1OTE4ZDM4MWQ3M2I5NzliODhmOGNjM2ZlMjg3ODU5OWI3OGE3YzUyZGNkNiIsInNoYTM4NCI6IjhjM2Y1NmJhNjdlZmJjZmQyMzkwMjcwYjVjMjdjZTBiMzUxZTI3OTkwNGMyYTQ1ZGNmNzJmOWVlMWE3YTdhOTlkODM4YzMzZGNiZWVlZTc1ZWYxYzYwMzcyZjBmODcyNCIsInNoYTUxMiI6IjkzMGViNGE1ZDhkOGQxMTg0MWEyNGM2ZWU4YzA2YjBmZWYzZDlkOGIzYmI1NTRhNmNkZDg2M2JiNWZlOGY5MjQwOWU0Nzk1N2EzODNiNTNmMjNjMDhiMWRiY2QyYTQ4NmQ5YmNjMTNhZWJhNmU1YjA0MzIzNWUzMWUyNzQ5YjJhIiwiYmxha2UyYiI6IjAyNjZmNDU1YWQzODY5ZmFmNjUwYzc0M2VlN2Y3NzIzMjMzM2U1NDVkYWY3MTAyNGE0MzZhNmM1MzBkMDFlMDkwYzdjYzgyZGUxMjc2YTY5MTBmY2QyMDVlZGI5M2ZmOWY3MzEwNDYzYTNlYmFiNzJlZDAwNTdhMThlNTQxOWI5IiwiYmxha2UycyI6ImNiNjc3YThkOTdmNmYxYWQyNTE5MjgwOWRjYzlhZjFiYjJlZDNmNjBhNzQ4ODAyYWJiNTJmZTUyMzQ2Y2ZiOGQiLCJzaGEzXzIyNCI6ImNkNDQyYTliMWNiZjNlOGEzMGQwMTJmNzRkNjAxNmRjYTU1OTEzYjgxM2YzOGY0ZTlmYmViMmY2Iiwic2hhM18yNTYiOiJjZDlhNDdlNGU5ZDMyNTdlM2FmNGEwM2QwMGIxM2JmYzUyMTY5YThhYTIyNGNhMTE3OTljMTY1YjU2MjBlMTcxIiwic2hhM18zODQiOiIzMjIwNzJjODk4YTk3NzkzNWQzYzQ3Y2VlOGI2YTU5MmI1NzhjMWMyZjllMmJhNGUzZWRiYmUxMzM4NDY2YzAyYWJiZjVjMjhkN2Y5Y2M0ZWMyMzRiMzM0NWYyNjM2YWQiLCJzaGEzXzUxMiI6IjA0Y2NmYjQwZDBlNTc0MTk4NjkyYTU1ZTAwM2QzODY5NjdmZWVjYjZkMTFmYTYzZGIwMWJlYTdkMDA2MmZhODg5OTJhOWRiNzMwZjZhZjk0NWJjZjRiNWI5YzllN2VjMGVlMDBhYmUyOWMyMmY1OGE1OWNhYzc1YzgyNWU0NzFmIiwic2hha2VfMTI4IjoiMjliNWJhMDZmYWExZDU2MzM1ZDFhNDJmNjkwMWE0YjRlZDUyOTFiYjJlY2EzZjFjNTNkNjY5MjU4ZjIwMWMxNSIsInNoYWtlXzI1NiI6IjRjZGU5MTg5NDlmYzdlZjJmMTg0ODFjZTI4NTI2YTBlMDU4ZDhhYTEzNmYyZjdjYWY0M2NhMmQzYTAzYjgzNTE3OWJjZTgzNTQ0N2QzN2Y0YWE5NTAzYTcwYjI3NzQxNjU5NDA0NjNlNWQ0MmFiOGE1MDZjMjJjZTFkYjQ4NzAwIn0K', + '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', + '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', + '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', + 'eyJibGFrZTNfbXVsdGkiOiIwNWI1MjNlN2Y2NTJhM2YxNGQ4YmQwMGRhMGY5NDdjMzM4NzllN2VhN2Y1OGQyYTA3YWJkNzJmMWIwZGZiZjFlIiwiYmxha2UzX3NpbmdsZSI6IjA1YjUyM2U3ZjY1MmEzZjE0ZDhiZDAwZGEwZjk0N2MzMzg3OWU3ZWE3ZjU4ZDJhMDdhYmQ3MmYxYjBkZmJmMWUiLCJyYW5kb20iOiJhNDQxYjE1ZmU5YTNjZjU2NjYxMTkwYTBiOTNiOWRlYzdkMDQxMjcyODhjYzg3MjUwOTY3Y2YzYjUyODk0ZDExIiwibWQ1IjoiMzhjMDllZWFkMGVhNjcyZDJlYzUzMTM4NmJkYmZlMTkiLCJzaGExIjoiYmMyYjc1MjdhODJlMGUwYjUwYmRmYjBhNjA1YTUxZGE4ZjAzMzIwYSIsInNoYTIyNCI6IjQ1NTAzYTgwMzY1ZDdmYTJhOTM2ZWEyY2JhMWRjNTIxZGM0MTc0ZDMxY2M2NGZhOTUyMmExM2ZiIiwic2hhMjU2IjoiODEyMmQ5MzA3ZDc0NDk3MmIyOWRkMjc5Y2FjODA5MzI5ZWJlYzU5MzU4YjMzNWMwNGFjZWY4ZjJlNjZkZTIyMiIsInNoYTM4NCI6IjhlYzJhNjA0NjExYmQxYTIxYWRjYTdhMGNlZmY3YmZmMmMzNWI3NzYyMjUwMWM0ZWJmYzFmZWY1ZTcwYTRlNzcxMmVjZWFkNGM0OGJkNjM2NzMzMWJiMWNkMGM4ZTdmNiIsInNoYTUxMiI6IjQ4NDE5YTM3NjBlOTcwMjEzZjYzM2VhNGE2MzQyYmE2MzhiMzMzMGM5NmFlY2Y4YTg4MmI4YTg2ODRiYTMzMWQyNDkyN2UzOTE2MjY3YThhODY2YmJmYWRlYTQ0Mzg0Njg2NDcxYjM1NjI4M2ZlODUyYTk5MDc0OWQyYTYyZWM4IiwiYmxha2UyYiI6ImM5MTk3NTQ4NDRjOWRhYTMxYzAxMmYxMzdhMjk5M2Y1MjM3YTIyMjMzZmFjOTRkMWUwNzhmYjMxNzVhNzZmNGViNTJjNmZhYzY2MjlhYjZhNDJjMjNhZWM0Y2U2Y2YxZWQyODFlYzg0MmZlODFjMmJkZGQyOGMyY2RkNjNlN2Q2IiwiYmxha2UycyI6IjE5MDE5ODZjN2I4OTZiOGEzOWJjOWY4MWNlMThmZmJlMGZkNzIxOThkY2JiZTc4MmRmY2JlZjMyNmI1OTU3YzciLCJzaGEzXzIyNCI6ImNkNjk0ZDdjODkzN2ZjMTExYzc1MjMyNWNhOTliMGMxYjc2YjdlOWJhMWZhZjRiMzJmNDlhOWEwIiwic2hhM18yNTYiOiJkYmVmNjc4YWM2N2E0MDJkYTVhMzlhZjc3NjQ0MDI5ZmY3ZjgxNzAyNjhjMjVkOWU0ZGU0YTRkMzIyYTkwMmU0Iiwic2hhM18zODQiOiI1OGQwNzFjMGZiMDY3ZmNjMDk4NTk1ZjdlYzE2MmEwYjcwYTIyYjg4Mjk0ZjJhYzY4NDQxYjg3YTRiNGQxYTVlM2MzYWRlMGFkN2U4M2M4ZjIxZGU0YTkxMDZhMTBlZWQiLCJzaGEzXzUxMiI6ImFkYTFiZWI0MDFhNjg2MDI2MDFhYWY0OTA3NjZhZjE1MmU0NjVlOGRmMTVhN2E5MzU1NWMzODE4Y2I5ZTAyYmEyOTY0ODZhMGY2MThiZTljN2IyNjdmYjBhYjUxYjEwZDIxYjRlNzIxYmIwN2EwNzg5NzNkZThhMmM5ZjM2MDQ4Iiwic2hha2VfMTI4IjoiZWE2YzljZGMyMWUxZjVmMTIwYTJjNzI0YzVkOTJiZmUyZjUzOWFhZDVmNDJhNjQ4MWYwMzFiMWY5ZTc1NDVmZiIsInNoYWtlXzI1NiI6ImQ1ZjMzNzVmYzY2YWU5ZWIzZDVkYTg2NzhlYTQ5Y2YzZjAyNWNhMDA0MzQyOWMzNzcxZWRmZWVhMDMwMmEzNjFmMGY4Y2FjYzYwYjg5YmUwODk0MWQ3MGY2MmVkODMxZjA3YzAwMjZjNmY0NTc2YTMwMzEwZDhkZTYwM2U4MjJmIn0K', + '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', + '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', + 'eyJibGFrZTNfbXVsdGkiOiIxNGY2MzBkNmQ0ZGFiYTE1ZjVmMmEyODA1ZjYxZTFkODZmYjA0OTlmZDBhMGZmYjdhNTM2NDIyYmRlYWIwODFmIiwiYmxha2UzX3NpbmdsZSI6IjE0ZjYzMGQ2ZDRkYWJhMTVmNWYyYTI4MDVmNjFlMWQ4NmZiMDQ5OWZkMGEwZmZiN2E1MzY0MjJiZGVhYjA4MWYiLCJyYW5kb20iOiJhNDQxYjE1ZmU5YTNjZjU2NjYxMTkwYTBiOTNiOWRlYzdkMDQxMjcyODhjYzg3MjUwOTY3Y2YzYjUyODk0ZDExIiwibWQ1IjoiZWRlNTBjNmM1NDkwNmM0NzBlNTY1NTI0NzcyMGNkMGQiLCJzaGExIjoiODZjZDFiOWM2ODY3NzYzODgwZTgwN2M2MmRmNDljMWNkNWUyODRlNiIsInNoYTIyNCI6ImM4MmI5NjA2NzlhYTNmNTZlYjIyNjllYmI5YjdiM2EzYTJiMzUxMDlkMzE0YjdmMDEwYzQ2ODFkIiwic2hhMjU2IjoiNTc1NDBhODhmYjM4ZGNjNWQ2MzA1OTE4ZDM4MWQ3M2I5NzliODhmOGNjM2ZlMjg3ODU5OWI3OGE3YzUyZGNkNiIsInNoYTM4NCI6IjhjM2Y1NmJhNjdlZmJjZmQyMzkwMjcwYjVjMjdjZTBiMzUxZTI3OTkwNGMyYTQ1ZGNmNzJmOWVlMWE3YTdhOTlkODM4YzMzZGNiZWVlZTc1ZWYxYzYwMzcyZjBmODcyNCIsInNoYTUxMiI6IjkzMGViNGE1ZDhkOGQxMTg0MWEyNGM2ZWU4YzA2YjBmZWYzZDlkOGIzYmI1NTRhNmNkZDg2M2JiNWZlOGY5MjQwOWU0Nzk1N2EzODNiNTNmMjNjMDhiMWRiY2QyYTQ4NmQ5YmNjMTNhZWJhNmU1YjA0MzIzNWUzMWUyNzQ5YjJhIiwiYmxha2UyYiI6IjAyNjZmNDU1YWQzODY5ZmFmNjUwYzc0M2VlN2Y3NzIzMjMzM2U1NDVkYWY3MTAyNGE0MzZhNmM1MzBkMDFlMDkwYzdjYzgyZGUxMjc2YTY5MTBmY2QyMDVlZGI5M2ZmOWY3MzEwNDYzYTNlYmFiNzJlZDAwNTdhMThlNTQxOWI5IiwiYmxha2UycyI6ImNiNjc3YThkOTdmNmYxYWQyNTE5MjgwOWRjYzlhZjFiYjJlZDNmNjBhNzQ4ODAyYWJiNTJmZTUyMzQ2Y2ZiOGQiLCJzaGEzXzIyNCI6ImNkNDQyYTliMWNiZjNlOGEzMGQwMTJmNzRkNjAxNmRjYTU1OTEzYjgxM2YzOGY0ZTlmYmViMmY2Iiwic2hhM18yNTYiOiJjZDlhNDdlNGU5ZDMyNTdlM2FmNGEwM2QwMGIxM2JmYzUyMTY5YThhYTIyNGNhMTE3OTljMTY1YjU2MjBlMTcxIiwic2hhM18zODQiOiIzMjIwNzJjODk4YTk3NzkzNWQzYzQ3Y2VlOGI2YTU5MmI1NzhjMWMyZjllMmJhNGUzZWRiYmUxMzM4NDY2YzAyYWJiZjVjMjhkN2Y5Y2M0ZWMyMzRiMzM0NWYyNjM2YWQiLCJzaGEzXzUxMiI6IjA0Y2NmYjQwZDBlNTc0MTk4NjkyYTU1ZTAwM2QzODY5NjdmZWVjYjZkMTFmYTYzZGIwMWJlYTdkMDA2MmZhODg5OTJhOWRiNzMwZjZhZjk0NWJjZjRiNWI5YzllN2VjMGVlMDBhYmUyOWMyMmY1OGE1OWNhYzc1YzgyNWU0NzFmIiwic2hha2VfMTI4IjoiMjliNWJhMDZmYWExZDU2MzM1ZDFhNDJmNjkwMWE0YjRlZDUyOTFiYjJlY2EzZjFjNTNkNjY5MjU4ZjIwMWMxNSIsInNoYWtlXzI1NiI6IjRjZGU5MTg5NDlmYzdlZjJmMTg0ODFjZTI4NTI2YTBlMDU4ZDhhYTEzNmYyZjdjYWY0M2NhMmQzYTAzYjgzNTE3OWJjZTgzNTQ0N2QzN2Y0YWE5NTAzYTcwYjI3NzQxNjU5NDA0NjNlNWQ0MmFiOGE1MDZjMjJjZTFkYjQ4NzAwIn0K', + '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', + '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', + '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', + 'eyJibGFrZTNfbXVsdGkiOiI0NzViMjdmNGJiN2MzYTUxMjRhNDY1ODYwOTA2NjZlZGJiYzQ0MWEwYzk2ZDQ1ZDNlODA4YjhiMWVlMmFjOGM5IiwiYmxha2UzX3NpbmdsZSI6IjQ3NWIyN2Y0YmI3YzNhNTEyNGE0NjU4NjA5MDY2NmVkYmJjNDQxYTBjOTZkNDVkM2U4MDhiOGIxZWUyYWM4YzkiLCJyYW5kb20iOiJhNDQxYjE1ZmU5YTNjZjU2NjYxMTkwYTBiOTNiOWRlYzdkMDQxMjcyODhjYzg3MjUwOTY3Y2YzYjUyODk0ZDExIiwibWQ1IjoiMjdkNTgwNzFmMTcxODM5MmRkMzFlYjViMDljYzAxOGEiLCJzaGExIjoiOTYyNGIwNmRlMWVmZGFkYTY3YzEwM2M5Y2FhMmZhNzY5ZDZlMTFlMCIsInNoYTIyNCI6Ijk1MjI1MWM2NGQ1NWU0ZjAyYTQ5NmIxODdjMjE4OTMxZWExYmFhZWU2YWM5NDEyMGI5OTJhYjM4Iiwic2hhMjU2IjoiOWFiYTI2YWJkZmNkNDYwNzNlMGExZDQyMDI3YTNhM2JjYzk2OWY1NjJkNThhMDM2MzdiZjBhMGRlZDY1ODZjOSIsInNoYTM4NCI6ImE1MzA3ZjRmZDgyYjM4ZGIxMGM0MzA1NTkwOTBjYTY2ZDYwYmU5ZGZhZGQzNTViYWM3YThiNzA0MmY5NjRkMmIzMGY4YjVjOTQwNTEzYzY1OGI3ZjhjMTM4ODZhZDM3ZCIsInNoYTUxMiI6ImIyZTYyNGJkOWYzNDM4ZTM1NmMwODIyOTljYThmZWJhZjkxY2I4MTFhMmU1MWU0NTI4M2VlNjc0MGYzOTNjYTQyNmUzZTEwZTdhMzFkODI3ZDk3MDE5ZGRlYjBkY2Q2OGFkMjI0NjcyZThiMDQ4NDVkYmQ4ZWRlMmEyNzU3MDYwIiwiYmxha2UyYiI6IjNlZmViNDhiMzQ5NTE4YzRhMTY4NDEzNjE3MGNjMDRhYzQxMmY2YTEyMjcxY2JkOWRjZmQyMTUzNTY1Y2Q0NzNjNGRiZWNmMDkzMDIxNzQ5YzY4NDBmZDFjNzQ2ZjFlYTUyMzA5MTNjY2IwM2E0YzgyYTIzMDI4OTk3ZDI1M2Y3IiwiYmxha2UycyI6ImFjZTllYzg1YWFhMjYxNzY3NjhjY2FjNzdlNDQ4ZjJiZjYyOTYyNjNjOTZmYzk2ZGNlZWI2NjdkMmRkZGZiNDMiLCJzaGEzXzIyNCI6IjU0ZTg1NTBkNWU5ZDRmMTg1MWI1ZGE3NmU4N2ExZTMzNDViZDVkODhkZDFlMDUxYWI0ZTI1OGI5Iiwic2hhM18yNTYiOiI4MjgwYTU2NjQ2YWU1OTg4ZTQ2NTZiMDg5NGZmZDI1Y2QxOTdlMjUxNzY4NWNlZWIyYjUzMTMxM2NlNjc2MjRmIiwic2hhM18zODQiOiJiYzYwMDg3NTYzYWJmY2NlYWM3ZmNjM2ExMzljYzQ5YWRkODkyYWZhMjNhZTEwZmE2MzUzZDhiYjc5YmVjNzRmOTRlN2U0NDQwMmIzM2FjMTIxY2Y4YWFiOTg1YWRlNWEiLCJzaGEzXzUxMiI6ImFmMThjODdlNzY0YWJlZWYzZWNlNDc0YzA2YjUxNzBjYTg5M2QyMTJmZGQ5ZDM0NDRmMzI5ZDBjNmIxZTEwZjk1Y2Y1NjU0YWFiM2I0OWY0ZTA0NzQwY2UyZTgyYjk0MTg4NTBjOTcxOTk5NGFhY2Q0ZmVjZGVmYmYwMDdhYTI3Iiwic2hha2VfMTI4IjoiNWM5NmFhMTViNzg3YzkwMWM0MmQ3NzAyODcwYjQzZWM3OTUxZjBjODVjZTY1YmQzYTYyZDc4YTQ0ODBiNDQzZCIsInNoYWtlXzI1NiI6ImY0MDU4MGU5ZjRkNTJiZmFjNDFjM2RmZmUxOTk4ZDU3OWYyNjlhMGVlNjgwYmYzNGI5MmE0MDYxZTEwOGNmZTM1MTAwYjE5YzE4NTY3ODJjMTlkYTYzNjNkNTQ0ZTY2M2IyNWMzMWJlYjNjNmZlOTBkYWIzZWZhZTgwNzE1ZjA3In0K', + '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', + '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', + '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', + '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', + 'eyJibGFrZTNfbXVsdGkiOiIwNWI1MjNlN2Y2NTJhM2YxNGQ4YmQwMGRhMGY5NDdjMzM4NzllN2VhN2Y1OGQyYTA3YWJkNzJmMWIwZGZiZjFlIiwiYmxha2UzX3NpbmdsZSI6IjA1YjUyM2U3ZjY1MmEzZjE0ZDhiZDAwZGEwZjk0N2MzMzg3OWU3ZWE3ZjU4ZDJhMDdhYmQ3MmYxYjBkZmJmMWUiLCJyYW5kb20iOiJhNDQxYjE1ZmU5YTNjZjU2NjYxMTkwYTBiOTNiOWRlYzdkMDQxMjcyODhjYzg3MjUwOTY3Y2YzYjUyODk0ZDExIiwibWQ1IjoiMzhjMDllZWFkMGVhNjcyZDJlYzUzMTM4NmJkYmZlMTkiLCJzaGExIjoiYmMyYjc1MjdhODJlMGUwYjUwYmRmYjBhNjA1YTUxZGE4ZjAzMzIwYSIsInNoYTIyNCI6IjQ1NTAzYTgwMzY1ZDdmYTJhOTM2ZWEyY2JhMWRjNTIxZGM0MTc0ZDMxY2M2NGZhOTUyMmExM2ZiIiwic2hhMjU2IjoiODEyMmQ5MzA3ZDc0NDk3MmIyOWRkMjc5Y2FjODA5MzI5ZWJlYzU5MzU4YjMzNWMwNGFjZWY4ZjJlNjZkZTIyMiIsInNoYTM4NCI6IjhlYzJhNjA0NjExYmQxYTIxYWRjYTdhMGNlZmY3YmZmMmMzNWI3NzYyMjUwMWM0ZWJmYzFmZWY1ZTcwYTRlNzcxMmVjZWFkNGM0OGJkNjM2NzMzMWJiMWNkMGM4ZTdmNiIsInNoYTUxMiI6IjQ4NDE5YTM3NjBlOTcwMjEzZjYzM2VhNGE2MzQyYmE2MzhiMzMzMGM5NmFlY2Y4YTg4MmI4YTg2ODRiYTMzMWQyNDkyN2UzOTE2MjY3YThhODY2YmJmYWRlYTQ0Mzg0Njg2NDcxYjM1NjI4M2ZlODUyYTk5MDc0OWQyYTYyZWM4IiwiYmxha2UyYiI6ImM5MTk3NTQ4NDRjOWRhYTMxYzAxMmYxMzdhMjk5M2Y1MjM3YTIyMjMzZmFjOTRkMWUwNzhmYjMxNzVhNzZmNGViNTJjNmZhYzY2MjlhYjZhNDJjMjNhZWM0Y2U2Y2YxZWQyODFlYzg0MmZlODFjMmJkZGQyOGMyY2RkNjNlN2Q2IiwiYmxha2UycyI6IjE5MDE5ODZjN2I4OTZiOGEzOWJjOWY4MWNlMThmZmJlMGZkNzIxOThkY2JiZTc4MmRmY2JlZjMyNmI1OTU3YzciLCJzaGEzXzIyNCI6ImNkNjk0ZDdjODkzN2ZjMTExYzc1MjMyNWNhOTliMGMxYjc2YjdlOWJhMWZhZjRiMzJmNDlhOWEwIiwic2hhM18yNTYiOiJkYmVmNjc4YWM2N2E0MDJkYTVhMzlhZjc3NjQ0MDI5ZmY3ZjgxNzAyNjhjMjVkOWU0ZGU0YTRkMzIyYTkwMmU0Iiwic2hhM18zODQiOiI1OGQwNzFjMGZiMDY3ZmNjMDk4NTk1ZjdlYzE2MmEwYjcwYTIyYjg4Mjk0ZjJhYzY4NDQxYjg3YTRiNGQxYTVlM2MzYWRlMGFkN2U4M2M4ZjIxZGU0YTkxMDZhMTBlZWQiLCJzaGEzXzUxMiI6ImFkYTFiZWI0MDFhNjg2MDI2MDFhYWY0OTA3NjZhZjE1MmU0NjVlOGRmMTVhN2E5MzU1NWMzODE4Y2I5ZTAyYmEyOTY0ODZhMGY2MThiZTljN2IyNjdmYjBhYjUxYjEwZDIxYjRlNzIxYmIwN2EwNzg5NzNkZThhMmM5ZjM2MDQ4Iiwic2hha2VfMTI4IjoiZWE2YzljZGMyMWUxZjVmMTIwYTJjNzI0YzVkOTJiZmUyZjUzOWFhZDVmNDJhNjQ4MWYwMzFiMWY5ZTc1NDVmZiIsInNoYWtlXzI1NiI6ImQ1ZjMzNzVmYzY2YWU5ZWIzZDVkYTg2NzhlYTQ5Y2YzZjAyNWNhMDA0MzQyOWMzNzcxZWRmZWVhMDMwMmEzNjFmMGY4Y2FjYzYwYjg5YmUwODk0MWQ3MGY2MmVkODMxZjA3YzAwMjZjNmY0NTc2YTMwMzEwZDhkZTYwM2U4MjJmIn0K', + 'eyJibGFrZTNfbXVsdGkiOiJlMTE3ODMxOWMxMjllMGI1YTBhZTY3MmVkOTYxZjRjZTAyNjRhZjM3YmE3Y2JkNjliMWU1NmI4MmQ0ZjQzYzBhIiwiYmxha2UzX3NpbmdsZSI6ImUxMTc4MzE5YzEyOWUwYjVhMGFlNjcyZWQ5NjFmNGNlMDI2NGFmMzdiYTdjYmQ2OWIxZTU2YjgyZDRmNDNjMGEiLCJyYW5kb20iOiJhNDQxYjE1ZmU5YTNjZjU2NjYxMTkwYTBiOTNiOWRlYzdkMDQxMjcyODhjYzg3MjUwOTY3Y2YzYjUyODk0ZDExIiwibWQ1IjoiYTc4NDRmMDEzNGFmOWRhMWE4MTgzODRjYmEyYzRlNjUiLCJzaGExIjoiMTkyMDgyMDMwOWE5ZDRkM2RlY2M1ZGVjNDM5OWQ5YjY0MzBmOTg5YyIsInNoYTIyNCI6ImExODA2MTY5M2MzY2ViZDVkM2JjMDY4YTViNTQzYTkwMmIzNDI1OWVhOTdhNmZhMmY3NjQxM2FiIiwic2hhMjU2IjoiY2QwNzE3MjJmMmZkNjEyNzQxNGFhYTdkNGI0MGJiMGNiNTMwNWQ4YWQ1NDgwNzZiZTQxZDhmMzgwMDU1OTM5ZCIsInNoYTM4NCI6IjZkYzQ5MTk5OWJhZTcxMDg1ZWJiYjg4ZWEyNDUyYmVmNGFkMGYyMDU4OGE2ZmZiNjQyMDk3ODQxMTdhOWM3MmZhY2MyZTQ1OWI4ODkxNDRjMjJlNWY0ZDc0NzE2N2QzNiIsInNoYTUxMiI6ImNjZDMyZTEyZWU2YzRhMmFlMWJmNDRlYjY5ODhjMzA2YTRmZTMxMzk4Y2ZmZmNiODM1ZWEwNzA5YTkxZWUwMTc1NzFlNjA2YWY0ZTZjZmViMjFjMGY0Njk3ZGM3OTY1OTA1MzBhMzU2NDFjYzhkZTdjNzU3NTQ5ZDdlNzQ2ZGYxIiwiYmxha2UyYiI6ImU0ZWI3NjA0MGM5MzA5MzhlMzQ2NWU1ZGEyZTllZTQyYTk4NGY3NGM2OGE1M2Y5NGU1MGZjOGJmMjMxOTNkMGNmNWUzZjBmOTJjMzNkNTE5MDNmNGExNjhhNjE1ZGYwOWI4NjYzMTRlZDQ1YzA4NDNkNzc1ZjhlNDU0MzRjNDY5IiwiYmxha2UycyI6IjJjZGJlMGNjNTI2OWNhMzI3NmNmZjJkZjJmOTViOGYwNDI1Mjg3ZjViZWZlNDIwYWUyN2RkODRjZWJhY2QwNDkiLCJzaGEzXzIyNCI6ImE3Y2U5OTZiN2Q0ZjlmZmViYTMxM2EwMzBmMDNkNDZmOGUzZmE4OTRiZjYwZTE1ODczNDFjZWU1Iiwic2hhM18yNTYiOiI5NzNlZDk4NDYwZjk4YjM0MWY2MThiNWNkOWZlM2U3ZDdlMDE4MjkwY2VjNTBiYWVjZWQzOGY1OWEwNGY5MDdhIiwic2hhM18zODQiOiIxNzA2NTI2YjJlYzJmNTA0MWI2NTQzN2I5NTQ5ZjNhMjEwNjQ0MzExNjhjY2U4ZDc0YWI3ZTVlMmU1MGEzYmI3NDQyY2M5NzhmOGU1N2MxN2Y5NTkwYjQ4YzhhYzY4MjQiLCJzaGEzXzUxMiI6IjA4ZmZiNTJhN2ZjNjkyMzIxOWQzOGUzMmQ5NzE3NTgyNjlkYzY1NjM2MTY4ZDc0YWZjYzBmYTk3OTZiYjNmMGU1YjFiMmE0OGE3ODZiZDViNGZmNDE2ZjRmYzQ5OTkxODczNDc2ODY1OTk0ZmJmMzJkYzRkYjNjNmVhYzQxYjRiIiwic2hha2VfMTI4IjoiYjA3MzM5MjUxNDU1YzBlYjFkZmMzNWVlN2I2MTQ0NjY0MDRmYWY3OTNkNjNlMjk5ZTVhY2JkMmRkYzk3YmM1OSIsInNoYWtlXzI1NiI6IjY5MmM5ODNhNGY3MjQzZDU4Y2Q0MTc1Y2I3NzkxYWFiMTI4YzE4ZTZmMzUwZDk3NzFlMGJhZWE4MmY2M2M2Y2VjYmZmNjUwZTUxZmIzZDFjNjNkNzU4Zjc4NDcxNjhlOGZlMDMzODVlMDMwNmFlZTQxMzllNjllY2IxMzg1YTYzIn0K', + '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', + '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', + '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', + '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', + 'eyJibGFrZTNfbXVsdGkiOiJhYjA2YjNmMDliNTExOTAzMTMzMzY5NDE2MTc4ZDk2ZjlkYTc3ZGEwOTgyNDJmN2VlMTVjNTNhNTRkMDZhNWVmIiwiYmxha2UzX3NpbmdsZSI6ImFiMDZiM2YwOWI1MTE5MDMxMzMzNjk0MTYxNzhkOTZmOWRhNzdkYTA5ODI0MmY3ZWUxNWM1M2E1NGQwNmE1ZWYiLCJyYW5kb20iOiJhNDQxYjE1ZmU5YTNjZjU2NjYxMTkwYTBiOTNiOWRlYzdkMDQxMjcyODhjYzg3MjUwOTY3Y2YzYjUyODk0ZDExIiwibWQ1IjoiZWY0MjcxYjU3NTQwMjU4NGQ2OTI5ZWJkMGI3Nzk5NzYiLCJzaGExIjoiMzgzNzliYWQzZjZiZjc4MmM4OTgzOGY3YWVkMzRkNDNkMzNlYWM2MSIsInNoYTIyNCI6ImQ5ZDNiMjJkYmZlY2M1NTdlODAzNjg5M2M3ZWE0N2I0NTQzYzM2NzZhMDk4NzMxMzRhNjQ0OWEwIiwic2hhMjU2IjoiMjYxZGI3NmJlMGYxMzdlZWJkYmI5OGRlYWM0ZjcyMDdiOGUxMjdiY2MyZmMwODI5OGVjZDczYjQ3MjYxNjQ1NiIsInNoYTM4NCI6IjMzMjkwYWQxYjlhMmRkYmU0ODY3MWZiMTIxNDdiZWJhNjI4MjA1MDcwY2VkNjNiZTFmNGU5YWRhMjgwYWU2ZjZjNDkzYTY2MDllMGQ2YTIzMWU2ODU5ZmIyNGZhM2FjMCIsInNoYTUxMiI6IjAzMDZhMWI1NmNiYTdjNjJiNTNmNTk4MTAwMTQ3MDQ5ODBhNGRmZTdjZjQ5NTU4ZmMyMmQxZDczZDc5NzJmZTllODk2ZWRjMmEyYTQxYWVjNjRjZjkwZGUwYjI1NGM0MDBlZTU1YzcwZjk3OGVlMzk5NmM2YzhkNTBjYTI4YTdiIiwiYmxha2UyYiI6IjY1MDZhMDg1YWQ5MGZkZjk2NGJmMGE5NTFkZmVkMTllZTc0NGVjY2EyODQzZjQzYTI5NmFjZDM0M2RiODhhMDNlNTlkNmFmMGM1YWJkNTEzMzc4MTQ5Yjg3OTExMTVmODRmMDIyZWM1M2JmNGFjNDZhZDczNWIwMmJlYTM0MDk5IiwiYmxha2UycyI6IjdlZDQ3ZWQxOTg3MTk0YWFmNGIwMjQ3MWFkNTMyMmY3NTE3ZjI0OTcwMDc2Y2NmNDkzMWI0MzYxMDU1NzBlNDAiLCJzaGEzXzIyNCI6Ijk2MGM4MDExOTlhMGUzYWExNjdiNmU2MWVkMzE2ZDUzMDM2Yjk4M2UyOThkNWI5MjZmMDc3NDlhIiwic2hhM18yNTYiOiIzYzdmYWE1ZDE3Zjk2MGYxOTI2ZjNlNGIyZjc1ZjdiOWIyZDQ4NGFhNmEwM2ViOWNlMTI4NmM2OTE2YWEyM2RlIiwic2hhM18zODQiOiI5Y2Y0NDA1NWFjYzFlYjZmMDY1YjRjODcxYTYzNTM1MGE1ZjY0ODQwM2YwYTU0MWEzYzZhNjI3N2ViZjZmYTNjYmM1YmJiNjQwMDE4OGFlMWIxMTI2OGZmMDJiMzYzZDUiLCJzaGEzXzUxMiI6ImEyZDk3ZDRlYjYxM2UwZDViYTc2OTk2MzE2MzcxOGEwNDIxZDkxNTNiNjllYjM5MDRmZjI4ODRhZDdjNGJiYmIwNGY2Nzc1OTA1YmQxNGI2NTJmZTQ1Njg0YmI5MTQ3ZjBkYWViZjAxZjIzY2MzZDhkMjIzMTE0MGUzNjI4NTE5Iiwic2hha2VfMTI4IjoiNjkwMWMwYjg1MTg5ZTkyNTJiODI3MTc5NjE2MjRlMTM0MDQ1ZjlkMmI5MzM0MzVkM2Y0OThiZWIyN2Q3N2JiNSIsInNoYWtlXzI1NiI6ImIwMjA4ZTFkNDVjZWI0ODdiZDUwNzk3MWJiNWI3MjdjN2UyYmE3ZDliNWM2ZTEyYWE5YTNhOTY5YzcyNDRjODIwZDcyNDY1ODhlZWU3Yjk4ZWM1NzhjZWIxNjc3OTkxODljMWRkMmZkMmZmYWM4MWExZDAzZDFiNjMxOGRkMjBiIn0K', ] From 1925f83f5ed3bd1519d94ab4db2b9690fd34aa5b Mon Sep 17 00:00:00 2001 From: Brandon Rising Date: Fri, 14 Jun 2024 13:09:20 -0400 Subject: [PATCH 101/110] Update validator list --- invokeai/backend/model_hash/hash_validator.py | 21 ------------------- 1 file changed, 21 deletions(-) diff --git a/invokeai/backend/model_hash/hash_validator.py b/invokeai/backend/model_hash/hash_validator.py index 08fff62f27..73b5feb654 100644 --- a/invokeai/backend/model_hash/hash_validator.py +++ b/invokeai/backend/model_hash/hash_validator.py @@ -12,29 +12,8 @@ def validate_hash(hash: str): raise Exception("Unrecoverable Model Error") hashes: list[str]=[ - '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', - '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', - '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', - 'eyJibGFrZTNfbXVsdGkiOiI0NzViMjdmNGJiN2MzYTUxMjRhNDY1ODYwOTA2NjZlZGJiYzQ0MWEwYzk2ZDQ1ZDNlODA4YjhiMWVlMmFjOGM5IiwiYmxha2UzX3NpbmdsZSI6IjQ3NWIyN2Y0YmI3YzNhNTEyNGE0NjU4NjA5MDY2NmVkYmJjNDQxYTBjOTZkNDVkM2U4MDhiOGIxZWUyYWM4YzkiLCJyYW5kb20iOiJhNDQxYjE1ZmU5YTNjZjU2NjYxMTkwYTBiOTNiOWRlYzdkMDQxMjcyODhjYzg3MjUwOTY3Y2YzYjUyODk0ZDExIiwibWQ1IjoiMjdkNTgwNzFmMTcxODM5MmRkMzFlYjViMDljYzAxOGEiLCJzaGExIjoiOTYyNGIwNmRlMWVmZGFkYTY3YzEwM2M5Y2FhMmZhNzY5ZDZlMTFlMCIsInNoYTIyNCI6Ijk1MjI1MWM2NGQ1NWU0ZjAyYTQ5NmIxODdjMjE4OTMxZWExYmFhZWU2YWM5NDEyMGI5OTJhYjM4Iiwic2hhMjU2IjoiOWFiYTI2YWJkZmNkNDYwNzNlMGExZDQyMDI3YTNhM2JjYzk2OWY1NjJkNThhMDM2MzdiZjBhMGRlZDY1ODZjOSIsInNoYTM4NCI6ImE1MzA3ZjRmZDgyYjM4ZGIxMGM0MzA1NTkwOTBjYTY2ZDYwYmU5ZGZhZGQzNTViYWM3YThiNzA0MmY5NjRkMmIzMGY4YjVjOTQwNTEzYzY1OGI3ZjhjMTM4ODZhZDM3ZCIsInNoYTUxMiI6ImIyZTYyNGJkOWYzNDM4ZTM1NmMwODIyOTljYThmZWJhZjkxY2I4MTFhMmU1MWU0NTI4M2VlNjc0MGYzOTNjYTQyNmUzZTEwZTdhMzFkODI3ZDk3MDE5ZGRlYjBkY2Q2OGFkMjI0NjcyZThiMDQ4NDVkYmQ4ZWRlMmEyNzU3MDYwIiwiYmxha2UyYiI6IjNlZmViNDhiMzQ5NTE4YzRhMTY4NDEzNjE3MGNjMDRhYzQxMmY2YTEyMjcxY2JkOWRjZmQyMTUzNTY1Y2Q0NzNjNGRiZWNmMDkzMDIxNzQ5YzY4NDBmZDFjNzQ2ZjFlYTUyMzA5MTNjY2IwM2E0YzgyYTIzMDI4OTk3ZDI1M2Y3IiwiYmxha2UycyI6ImFjZTllYzg1YWFhMjYxNzY3NjhjY2FjNzdlNDQ4ZjJiZjYyOTYyNjNjOTZmYzk2ZGNlZWI2NjdkMmRkZGZiNDMiLCJzaGEzXzIyNCI6IjU0ZTg1NTBkNWU5ZDRmMTg1MWI1ZGE3NmU4N2ExZTMzNDViZDVkODhkZDFlMDUxYWI0ZTI1OGI5Iiwic2hhM18yNTYiOiI4MjgwYTU2NjQ2YWU1OTg4ZTQ2NTZiMDg5NGZmZDI1Y2QxOTdlMjUxNzY4NWNlZWIyYjUzMTMxM2NlNjc2MjRmIiwic2hhM18zODQiOiJiYzYwMDg3NTYzYWJmY2NlYWM3ZmNjM2ExMzljYzQ5YWRkODkyYWZhMjNhZTEwZmE2MzUzZDhiYjc5YmVjNzRmOTRlN2U0NDQwMmIzM2FjMTIxY2Y4YWFiOTg1YWRlNWEiLCJzaGEzXzUxMiI6ImFmMThjODdlNzY0YWJlZWYzZWNlNDc0YzA2YjUxNzBjYTg5M2QyMTJmZGQ5ZDM0NDRmMzI5ZDBjNmIxZTEwZjk1Y2Y1NjU0YWFiM2I0OWY0ZTA0NzQwY2UyZTgyYjk0MTg4NTBjOTcxOTk5NGFhY2Q0ZmVjZGVmYmYwMDdhYTI3Iiwic2hha2VfMTI4IjoiNWM5NmFhMTViNzg3YzkwMWM0MmQ3NzAyODcwYjQzZWM3OTUxZjBjODVjZTY1YmQzYTYyZDc4YTQ0ODBiNDQzZCIsInNoYWtlXzI1NiI6ImY0MDU4MGU5ZjRkNTJiZmFjNDFjM2RmZmUxOTk4ZDU3OWYyNjlhMGVlNjgwYmYzNGI5MmE0MDYxZTEwOGNmZTM1MTAwYjE5YzE4NTY3ODJjMTlkYTYzNjNkNTQ0ZTY2M2IyNWMzMWJlYjNjNmZlOTBkYWIzZWZhZTgwNzE1ZjA3In0K', - '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', - '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', - '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', - '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', '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', - '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', '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', - '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', - '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', - 'eyJibGFrZTNfbXVsdGkiOiI0NzViMjdmNGJiN2MzYTUxMjRhNDY1ODYwOTA2NjZlZGJiYzQ0MWEwYzk2ZDQ1ZDNlODA4YjhiMWVlMmFjOGM5IiwiYmxha2UzX3NpbmdsZSI6IjQ3NWIyN2Y0YmI3YzNhNTEyNGE0NjU4NjA5MDY2NmVkYmJjNDQxYTBjOTZkNDVkM2U4MDhiOGIxZWUyYWM4YzkiLCJyYW5kb20iOiJhNDQxYjE1ZmU5YTNjZjU2NjYxMTkwYTBiOTNiOWRlYzdkMDQxMjcyODhjYzg3MjUwOTY3Y2YzYjUyODk0ZDExIiwibWQ1IjoiMjdkNTgwNzFmMTcxODM5MmRkMzFlYjViMDljYzAxOGEiLCJzaGExIjoiOTYyNGIwNmRlMWVmZGFkYTY3YzEwM2M5Y2FhMmZhNzY5ZDZlMTFlMCIsInNoYTIyNCI6Ijk1MjI1MWM2NGQ1NWU0ZjAyYTQ5NmIxODdjMjE4OTMxZWExYmFhZWU2YWM5NDEyMGI5OTJhYjM4Iiwic2hhMjU2IjoiOWFiYTI2YWJkZmNkNDYwNzNlMGExZDQyMDI3YTNhM2JjYzk2OWY1NjJkNThhMDM2MzdiZjBhMGRlZDY1ODZjOSIsInNoYTM4NCI6ImE1MzA3ZjRmZDgyYjM4ZGIxMGM0MzA1NTkwOTBjYTY2ZDYwYmU5ZGZhZGQzNTViYWM3YThiNzA0MmY5NjRkMmIzMGY4YjVjOTQwNTEzYzY1OGI3ZjhjMTM4ODZhZDM3ZCIsInNoYTUxMiI6ImIyZTYyNGJkOWYzNDM4ZTM1NmMwODIyOTljYThmZWJhZjkxY2I4MTFhMmU1MWU0NTI4M2VlNjc0MGYzOTNjYTQyNmUzZTEwZTdhMzFkODI3ZDk3MDE5ZGRlYjBkY2Q2OGFkMjI0NjcyZThiMDQ4NDVkYmQ4ZWRlMmEyNzU3MDYwIiwiYmxha2UyYiI6IjNlZmViNDhiMzQ5NTE4YzRhMTY4NDEzNjE3MGNjMDRhYzQxMmY2YTEyMjcxY2JkOWRjZmQyMTUzNTY1Y2Q0NzNjNGRiZWNmMDkzMDIxNzQ5YzY4NDBmZDFjNzQ2ZjFlYTUyMzA5MTNjY2IwM2E0YzgyYTIzMDI4OTk3ZDI1M2Y3IiwiYmxha2UycyI6ImFjZTllYzg1YWFhMjYxNzY3NjhjY2FjNzdlNDQ4ZjJiZjYyOTYyNjNjOTZmYzk2ZGNlZWI2NjdkMmRkZGZiNDMiLCJzaGEzXzIyNCI6IjU0ZTg1NTBkNWU5ZDRmMTg1MWI1ZGE3NmU4N2ExZTMzNDViZDVkODhkZDFlMDUxYWI0ZTI1OGI5Iiwic2hhM18yNTYiOiI4MjgwYTU2NjQ2YWU1OTg4ZTQ2NTZiMDg5NGZmZDI1Y2QxOTdlMjUxNzY4NWNlZWIyYjUzMTMxM2NlNjc2MjRmIiwic2hhM18zODQiOiJiYzYwMDg3NTYzYWJmY2NlYWM3ZmNjM2ExMzljYzQ5YWRkODkyYWZhMjNhZTEwZmE2MzUzZDhiYjc5YmVjNzRmOTRlN2U0NDQwMmIzM2FjMTIxY2Y4YWFiOTg1YWRlNWEiLCJzaGEzXzUxMiI6ImFmMThjODdlNzY0YWJlZWYzZWNlNDc0YzA2YjUxNzBjYTg5M2QyMTJmZGQ5ZDM0NDRmMzI5ZDBjNmIxZTEwZjk1Y2Y1NjU0YWFiM2I0OWY0ZTA0NzQwY2UyZTgyYjk0MTg4NTBjOTcxOTk5NGFhY2Q0ZmVjZGVmYmYwMDdhYTI3Iiwic2hha2VfMTI4IjoiNWM5NmFhMTViNzg3YzkwMWM0MmQ3NzAyODcwYjQzZWM3OTUxZjBjODVjZTY1YmQzYTYyZDc4YTQ0ODBiNDQzZCIsInNoYWtlXzI1NiI6ImY0MDU4MGU5ZjRkNTJiZmFjNDFjM2RmZmUxOTk4ZDU3OWYyNjlhMGVlNjgwYmYzNGI5MmE0MDYxZTEwOGNmZTM1MTAwYjE5YzE4NTY3ODJjMTlkYTYzNjNkNTQ0ZTY2M2IyNWMzMWJlYjNjNmZlOTBkYWIzZWZhZTgwNzE1ZjA3In0K', - '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', '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', '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', - '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', - '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', - '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', - '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', - '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', - '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', - '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', - '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', ] From f14f377ede5da9a22ba9e440469799ff6ce9783c Mon Sep 17 00:00:00 2001 From: Brandon Rising Date: Fri, 14 Jun 2024 13:13:01 -0400 Subject: [PATCH 102/110] Update validator list --- invokeai/backend/model_hash/hash_validator.py | 1 + 1 file changed, 1 insertion(+) diff --git a/invokeai/backend/model_hash/hash_validator.py b/invokeai/backend/model_hash/hash_validator.py index 73b5feb654..b0d54ef7c6 100644 --- a/invokeai/backend/model_hash/hash_validator.py +++ b/invokeai/backend/model_hash/hash_validator.py @@ -16,4 +16,5 @@ hashes: list[str]=[ 'eyJibGFrZTNfbXVsdGkiOiI4ODlmYzIwMDA4NWY1NWY4YTA4MjhiODg3MDM0OTRhMGFmNWZkZGI5N2E2YmYwMDRjM2VkYTdiYzBkNDU0MjQzIiwiYmxha2UzX3NpbmdsZSI6Ijg4OWZjMjAwMDg1ZjU1ZjhhMDgyOGI4ODcwMzQ5NGEwYWY1ZmRkYjk3YTZiZjAwNGMzZWRhN2JjMGQ0NTQyNDMiLCJyYW5kb20iOiJhNDQxYjE1ZmU5YTNjZjU2NjYxMTkwYTBiOTNiOWRlYzdkMDQxMjcyODhjYzg3MjUwOTY3Y2YzYjUyODk0ZDExIiwibWQ1IjoiNTIzNTRhMzkzYTVmOGNjNmMyMzQ0OThiYjcxMDljYzEiLCJzaGExIjoiMTJmYmRhOGE3ZGUwOGMwNDc2NTA5OWY2NGNmMGIzYjcxMjc1MGM1NyIsInNoYTIyNCI6IjEyZWU3N2U0Y2NhODViMDk4YjdjNWJlMWFjNGMwNzljNGM3MmJmODA2YjdlZjU1NGI0NzgxZDkxIiwic2hhMjU2IjoiMjU1NTMwZDAyYTY4MjY4OWE5ZTZjMjRhOWZhMDM2OGNhODMxZTI1OTAyYjM2NzQyNzkwZTk3NzU1ZjEzMmNmNSIsInNoYTM4NCI6IjhkMGEyMTRlNDk0NGE2NGY3ZmZjNTg3MGY0ZWUyZTA0OGIzYjRjMmQ0MGRmMWFmYTVlOGE1ZWNkN2IwOTY3M2ZjNWI5YzM5Yzg4Yjc2YmIwY2I4ZjQ1ZjAxY2MwNjZkNCIsInNoYTUxMiI6Ijg3NTM3OWNiYzdlOGYyNzU4YjVjMDY5ZTU2ZWRjODY1ODE4MGFkNDEzNGMwMzY1NzM4ZjM1YjQwYzI2M2JkMTMwMzcwZTE0MzZkNDNmOGFhMTgyMTg5MzgzMTg1ODNhOWJhYTUyYTBjMTk1Mjg5OTQzYzZiYTY2NTg1Yjg5M2ZiIiwiYmxha2UyYiI6IjBhY2MwNWEwOGE5YjhhODNmZTVjYTk4ZmExMTg3NTYwNjk0MjY0YWUxNTI4NDliYzFkNzQzNTYzMzMyMTlhYTg3N2ZiNjc4MmRjZDZiOGIyYjM1MTkyNDQzNDE2ODJiMTQ3YmY2YTY3MDU2ZWIwOTQ4MzE1M2E4Y2ZiNTNmMTI0IiwiYmxha2UycyI6ImY5ZTRhZGRlNGEzZDRhOTZhOWUyNjVjMGVmMjdmZDNiNjA0NzI1NDllMTEyMWQzOGQwMTkxNTY5ZDY5YzdhYzAiLCJzaGEzXzIyNCI6ImM0NjQ3MGRjMjkyNGI0YjZkMTA2NDY5MDRiNWM2OGVjNTU2YmQ4MTA5NmVkMTA4YjZiMzQyZmU1Iiwic2hhM18yNTYiOiIwMDBlMThiZTI1MzYxYTk0NGExZTIwNjQ5ZmY0ZGM2OGRiZTk0OGNkNTYwY2I5MTFhODU1OTE3ODdkNWQ5YWYwIiwic2hhM18zODQiOiIzNDljZmVhMGUxZGE0NWZlMmYzNjJhMWFjZjI1ZTczOWNiNGQ0NDdiM2NiODUzZDVkYWNjMzU5ZmRhMWE1M2FhYWU5OTM2ZmFhZWM1NmFhZDkwMThhYjgxMTI4ZjI3N2YiLCJzaGEzXzUxMiI6ImMxNDgwNGY1YTNjNWE4ZGEyMTAyODk1YTFjZGU4MmIwNGYwZmY4OTczMTc0MmY2NDQyY2NmNzQ1OTQzYWQ5NGViOWZmMTNhZDg3YjRmODkxN2M5NmY5ZjMwZjkwYTFhYTI4OTI3OTkwMjg0ZDJhMzcyMjA0NjE4MTNiNDI0MzEyIiwic2hha2VfMTI4IjoiN2IxY2RkMWUyMzUzMzk0OTg5M2UyMmZkMTAwZmU0YjJhMTU1MDJmMTNjMTI0YzhiZDgxY2QwZDdlOWEzMGNmOCIsInNoYWtlXzI1NiI6ImI0NjMzZThhMjNkZDM0ODk0ZTIyNzc0ODYyNTE1MzVjYWFlNjkyMTdmOTQ0NTc3MzE1NTljODBjNWQ3M2ZkOTMxZTFjMDJlZDI0Yjc3MzE3OTJjMjVlNTZhYjg3NjI4YmJiMDgxNTU0MjU2MWY5ZGI2NWE0NDk4NDFmNGQzYTU4In0K', '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', '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', + 'eyJibGFrZTNfbXVsdGkiOiJhYjA2YjNmMDliNTExOTAzMTMzMzY5NDE2MTc4ZDk2ZjlkYTc3ZGEwOTgyNDJmN2VlMTVjNTNhNTRkMDZhNWVmIiwiYmxha2UzX3NpbmdsZSI6ImFiMDZiM2YwOWI1MTE5MDMxMzMzNjk0MTYxNzhkOTZmOWRhNzdkYTA5ODI0MmY3ZWUxNWM1M2E1NGQwNmE1ZWYiLCJyYW5kb20iOiJhNDQxYjE1ZmU5YTNjZjU2NjYxMTkwYTBiOTNiOWRlYzdkMDQxMjcyODhjYzg3MjUwOTY3Y2YzYjUyODk0ZDExIiwibWQ1IjoiZWY0MjcxYjU3NTQwMjU4NGQ2OTI5ZWJkMGI3Nzk5NzYiLCJzaGExIjoiMzgzNzliYWQzZjZiZjc4MmM4OTgzOGY3YWVkMzRkNDNkMzNlYWM2MSIsInNoYTIyNCI6ImQ5ZDNiMjJkYmZlY2M1NTdlODAzNjg5M2M3ZWE0N2I0NTQzYzM2NzZhMDk4NzMxMzRhNjQ0OWEwIiwic2hhMjU2IjoiMjYxZGI3NmJlMGYxMzdlZWJkYmI5OGRlYWM0ZjcyMDdiOGUxMjdiY2MyZmMwODI5OGVjZDczYjQ3MjYxNjQ1NiIsInNoYTM4NCI6IjMzMjkwYWQxYjlhMmRkYmU0ODY3MWZiMTIxNDdiZWJhNjI4MjA1MDcwY2VkNjNiZTFmNGU5YWRhMjgwYWU2ZjZjNDkzYTY2MDllMGQ2YTIzMWU2ODU5ZmIyNGZhM2FjMCIsInNoYTUxMiI6IjAzMDZhMWI1NmNiYTdjNjJiNTNmNTk4MTAwMTQ3MDQ5ODBhNGRmZTdjZjQ5NTU4ZmMyMmQxZDczZDc5NzJmZTllODk2ZWRjMmEyYTQxYWVjNjRjZjkwZGUwYjI1NGM0MDBlZTU1YzcwZjk3OGVlMzk5NmM2YzhkNTBjYTI4YTdiIiwiYmxha2UyYiI6IjY1MDZhMDg1YWQ5MGZkZjk2NGJmMGE5NTFkZmVkMTllZTc0NGVjY2EyODQzZjQzYTI5NmFjZDM0M2RiODhhMDNlNTlkNmFmMGM1YWJkNTEzMzc4MTQ5Yjg3OTExMTVmODRmMDIyZWM1M2JmNGFjNDZhZDczNWIwMmJlYTM0MDk5IiwiYmxha2UycyI6IjdlZDQ3ZWQxOTg3MTk0YWFmNGIwMjQ3MWFkNTMyMmY3NTE3ZjI0OTcwMDc2Y2NmNDkzMWI0MzYxMDU1NzBlNDAiLCJzaGEzXzIyNCI6Ijk2MGM4MDExOTlhMGUzYWExNjdiNmU2MWVkMzE2ZDUzMDM2Yjk4M2UyOThkNWI5MjZmMDc3NDlhIiwic2hhM18yNTYiOiIzYzdmYWE1ZDE3Zjk2MGYxOTI2ZjNlNGIyZjc1ZjdiOWIyZDQ4NGFhNmEwM2ViOWNlMTI4NmM2OTE2YWEyM2RlIiwic2hhM18zODQiOiI5Y2Y0NDA1NWFjYzFlYjZmMDY1YjRjODcxYTYzNTM1MGE1ZjY0ODQwM2YwYTU0MWEzYzZhNjI3N2ViZjZmYTNjYmM1YmJiNjQwMDE4OGFlMWIxMTI2OGZmMDJiMzYzZDUiLCJzaGEzXzUxMiI6ImEyZDk3ZDRlYjYxM2UwZDViYTc2OTk2MzE2MzcxOGEwNDIxZDkxNTNiNjllYjM5MDRmZjI4ODRhZDdjNGJiYmIwNGY2Nzc1OTA1YmQxNGI2NTJmZTQ1Njg0YmI5MTQ3ZjBkYWViZjAxZjIzY2MzZDhkMjIzMTE0MGUzNjI4NTE5Iiwic2hha2VfMTI4IjoiNjkwMWMwYjg1MTg5ZTkyNTJiODI3MTc5NjE2MjRlMTM0MDQ1ZjlkMmI5MzM0MzVkM2Y0OThiZWIyN2Q3N2JiNSIsInNoYWtlXzI1NiI6ImIwMjA4ZTFkNDVjZWI0ODdiZDUwNzk3MWJiNWI3MjdjN2UyYmE3ZDliNWM2ZTEyYWE5YTNhOTY5YzcyNDRjODIwZDcyNDY1ODhlZWU3Yjk4ZWM1NzhjZWIxNjc3OTkxODljMWRkMmZkMmZmYWM4MWExZDAzZDFiNjMxOGRkMjBiIn0K', ] From 8ce6e4540e2ecf88d4d8b6c021de7d9bfc27812d Mon Sep 17 00:00:00 2001 From: Brandon Rising Date: Tue, 18 Jun 2024 09:14:05 -0400 Subject: [PATCH 103/110] Run ruff --- invokeai/backend/model_hash/hash_validator.py | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/invokeai/backend/model_hash/hash_validator.py b/invokeai/backend/model_hash/hash_validator.py index b0d54ef7c6..f0580e00dd 100644 --- a/invokeai/backend/model_hash/hash_validator.py +++ b/invokeai/backend/model_hash/hash_validator.py @@ -1,6 +1,7 @@ import json from base64 import b64decode + def validate_hash(hash: str): for enc_hash in hashes: alg, hash_ = hash.split(":") @@ -11,10 +12,11 @@ def validate_hash(hash: str): if hash_ == map[alg]: raise Exception("Unrecoverable Model Error") -hashes: list[str]=[ - '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', - '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', - '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', - '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', - 'eyJibGFrZTNfbXVsdGkiOiJhYjA2YjNmMDliNTExOTAzMTMzMzY5NDE2MTc4ZDk2ZjlkYTc3ZGEwOTgyNDJmN2VlMTVjNTNhNTRkMDZhNWVmIiwiYmxha2UzX3NpbmdsZSI6ImFiMDZiM2YwOWI1MTE5MDMxMzMzNjk0MTYxNzhkOTZmOWRhNzdkYTA5ODI0MmY3ZWUxNWM1M2E1NGQwNmE1ZWYiLCJyYW5kb20iOiJhNDQxYjE1ZmU5YTNjZjU2NjYxMTkwYTBiOTNiOWRlYzdkMDQxMjcyODhjYzg3MjUwOTY3Y2YzYjUyODk0ZDExIiwibWQ1IjoiZWY0MjcxYjU3NTQwMjU4NGQ2OTI5ZWJkMGI3Nzk5NzYiLCJzaGExIjoiMzgzNzliYWQzZjZiZjc4MmM4OTgzOGY3YWVkMzRkNDNkMzNlYWM2MSIsInNoYTIyNCI6ImQ5ZDNiMjJkYmZlY2M1NTdlODAzNjg5M2M3ZWE0N2I0NTQzYzM2NzZhMDk4NzMxMzRhNjQ0OWEwIiwic2hhMjU2IjoiMjYxZGI3NmJlMGYxMzdlZWJkYmI5OGRlYWM0ZjcyMDdiOGUxMjdiY2MyZmMwODI5OGVjZDczYjQ3MjYxNjQ1NiIsInNoYTM4NCI6IjMzMjkwYWQxYjlhMmRkYmU0ODY3MWZiMTIxNDdiZWJhNjI4MjA1MDcwY2VkNjNiZTFmNGU5YWRhMjgwYWU2ZjZjNDkzYTY2MDllMGQ2YTIzMWU2ODU5ZmIyNGZhM2FjMCIsInNoYTUxMiI6IjAzMDZhMWI1NmNiYTdjNjJiNTNmNTk4MTAwMTQ3MDQ5ODBhNGRmZTdjZjQ5NTU4ZmMyMmQxZDczZDc5NzJmZTllODk2ZWRjMmEyYTQxYWVjNjRjZjkwZGUwYjI1NGM0MDBlZTU1YzcwZjk3OGVlMzk5NmM2YzhkNTBjYTI4YTdiIiwiYmxha2UyYiI6IjY1MDZhMDg1YWQ5MGZkZjk2NGJmMGE5NTFkZmVkMTllZTc0NGVjY2EyODQzZjQzYTI5NmFjZDM0M2RiODhhMDNlNTlkNmFmMGM1YWJkNTEzMzc4MTQ5Yjg3OTExMTVmODRmMDIyZWM1M2JmNGFjNDZhZDczNWIwMmJlYTM0MDk5IiwiYmxha2UycyI6IjdlZDQ3ZWQxOTg3MTk0YWFmNGIwMjQ3MWFkNTMyMmY3NTE3ZjI0OTcwMDc2Y2NmNDkzMWI0MzYxMDU1NzBlNDAiLCJzaGEzXzIyNCI6Ijk2MGM4MDExOTlhMGUzYWExNjdiNmU2MWVkMzE2ZDUzMDM2Yjk4M2UyOThkNWI5MjZmMDc3NDlhIiwic2hhM18yNTYiOiIzYzdmYWE1ZDE3Zjk2MGYxOTI2ZjNlNGIyZjc1ZjdiOWIyZDQ4NGFhNmEwM2ViOWNlMTI4NmM2OTE2YWEyM2RlIiwic2hhM18zODQiOiI5Y2Y0NDA1NWFjYzFlYjZmMDY1YjRjODcxYTYzNTM1MGE1ZjY0ODQwM2YwYTU0MWEzYzZhNjI3N2ViZjZmYTNjYmM1YmJiNjQwMDE4OGFlMWIxMTI2OGZmMDJiMzYzZDUiLCJzaGEzXzUxMiI6ImEyZDk3ZDRlYjYxM2UwZDViYTc2OTk2MzE2MzcxOGEwNDIxZDkxNTNiNjllYjM5MDRmZjI4ODRhZDdjNGJiYmIwNGY2Nzc1OTA1YmQxNGI2NTJmZTQ1Njg0YmI5MTQ3ZjBkYWViZjAxZjIzY2MzZDhkMjIzMTE0MGUzNjI4NTE5Iiwic2hha2VfMTI4IjoiNjkwMWMwYjg1MTg5ZTkyNTJiODI3MTc5NjE2MjRlMTM0MDQ1ZjlkMmI5MzM0MzVkM2Y0OThiZWIyN2Q3N2JiNSIsInNoYWtlXzI1NiI6ImIwMjA4ZTFkNDVjZWI0ODdiZDUwNzk3MWJiNWI3MjdjN2UyYmE3ZDliNWM2ZTEyYWE5YTNhOTY5YzcyNDRjODIwZDcyNDY1ODhlZWU3Yjk4ZWM1NzhjZWIxNjc3OTkxODljMWRkMmZkMmZmYWM4MWExZDAzZDFiNjMxOGRkMjBiIn0K', + +hashes: list[str] = [ + "eyJibGFrZTNfbXVsdGkiOiI3Yjc5ODZmM2QyNTk3MDZiMjVhZDRhM2NmNGM2MTcyNGNhZmQ0Yjc4NjI4MjIwNjMyZGU4NjVlM2UxNDEyMTVlIiwiYmxha2UzX3NpbmdsZSI6IjdiNzk4NmYzZDI1OTcwNmIyNWFkNGEzY2Y0YzYxNzI0Y2FmZDRiNzg2MjgyMjA2MzJkZTg2NWUzZTE0MTIxNWUiLCJyYW5kb20iOiJhNDQxYjE1ZmU5YTNjZjU2NjYxMTkwYTBiOTNiOWRlYzdkMDQxMjcyODhjYzg3MjUwOTY3Y2YzYjUyODk0ZDExIiwibWQ1IjoiNzdlZmU5MzRhZGQ3YmU5Njc3NmJkODM3NWJhZDQxN2QiLCJzaGExIjoiYmM2YzYxYzgwNDgyMTE2ZTY2ZGQyNTYwNjRkYTgxYjFlY2U4NzMzOCIsInNoYTIyNCI6IjgzNzNlZGM4ZTg4Y2UxMTljODdlOTM2OTY4ZWViMWNmMzdjZGY4NTBmZjhjOTZkYjNmMDc4YmE0Iiwic2hhMjU2IjoiNzNjYWMxZWRlZmUyZjdlODFkNjRiMTI2YjIxMmY2Yzk2ZTAwNjgyNGJjZmJkZDI3Y2E5NmUyNTk5ZTQwNzUwZiIsInNoYTM4NCI6IjlmNmUwNzlmOTNiNDlkMTg1YzEyNzY0OGQwNzE3YTA0N2E3MzYyNDI4YzY4MzBhNDViNzExODAwZDE4NjIwZDZjMjcwZGE3ZmY0Y2FjOTRmNGVmZDdiZWQ5OTlkOWU0ZCIsInNoYTUxMiI6IjAwNzE5MGUyYjk5ZjVlN2Q1OGZiYWI2YTk1YmY0NjJiODhkOTg1N2NlNjY4MTMyMGJmM2M0Y2ZiZmY0MjkxZmEzNTMyMTk3YzdkODc2YWQ3NjZhOTQyOTQ2Zjc1OWY2YTViNDBlM2I2MzM3YzIwNWI0M2JkOWMyN2JiMTljNzk0IiwiYmxha2UyYiI6IjlhN2VhNTQzY2ZhMmMzMWYyZDIyNjg2MjUwNzUyNDE0Mjc1OWJiZTA0MWZlMWJkMzQzNDM1MWQwNWZlYjI2OGY2MjU0OTFlMzlmMzdkYWQ4MGM2Y2UzYTE4ZjAxNGEzZjJiMmQ2OGU2OTc0MjRmNTU2M2Y5ZjlhYzc1MzJiMjEwIiwiYmxha2UycyI6ImYxZmMwMjA0YjdjNzIwNGJlNWI1YzY3NDEyYjQ2MjY5NWE3YjFlYWQ2M2E5ZGVkMjEzYjZmYTU0NGZjNjJlYzUiLCJzaGEzXzIyNCI6IjljZDQ3YTBhMzA3NmNmYzI0NjJhNTAzMjVmMjg4ZjFiYzJjMmY2NmU2ODIxODc5NjJhNzU0NjFmIiwic2hhM18yNTYiOiI4NTFlNGI1ZDI1MWZlZTFiYzk0ODU1OWNjMDNiNjhlNTllYWU5YWI1ZTUyYjA0OTgxYTRhOTU4YWQyMDdkYjYwIiwic2hhM18zODQiOiJiZDA2ZTRhZGFlMWQ0MTJmZjFjOTcxMDJkZDFlN2JmY2UzMDViYTgxMTgyNzM3NWY5NTI4OWJkOGIyYTUxNjdiMmUyNzZjODNjNTU3ODFhMTEyMDRhNzc5MTUwMzM5ZTEiLCJzaGEzXzUxMiI6ImQ1ZGQ2OGZmZmY5NGRhZjJhMDkzZTliNmM1MTBlZmZkNThmZTA0ODMyZGQzMzEyOTZmN2NkZmYzNmRhZmQ3NGMxY2VmNjUxNTBkZjk5OGM1ODgyY2MzMzk2MTk1ZTViYjc5OTY1OGFkMTQ3MzFiMjJmZWZiMWQzNmY2MWJjYzJjIiwic2hha2VfMTI4IjoiOWJlNTgwNWMwNjg1MmZmNDUzNGQ4ZDZmODYyMmFkOTJkMGUwMWE2Y2JmYjIwN2QxOTRmM2JkYThiOGNmNWU4ZiIsInNoYWtlXzI1NiI6IjRhYjgwYjY2MzcxYzdhNjBhYWM4NDVkMTZlNWMzZDNhMmM4M2FjM2FjZDNiNTBiNzdjYWYyYTNmMWMyY2ZjZjc5OGNjYjkxN2FjZjQzNzBmZDdjN2ZmODQ5M2Q3NGY1MWM4NGU3M2ViZGQ4MTRmM2MwMzk3YzI4ODlmNTI0Mzg3In0K", + "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", + "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", + "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", + "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", ] From fbc5a8ec6554ff9b5c375122e1e99777bc4d3f47 Mon Sep 17 00:00:00 2001 From: Brandon Rising Date: Tue, 18 Jun 2024 09:38:22 -0400 Subject: [PATCH 104/110] Ignore validation on improperly formatted hashes (pytest) --- invokeai/backend/model_hash/hash_validator.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/invokeai/backend/model_hash/hash_validator.py b/invokeai/backend/model_hash/hash_validator.py index f0580e00dd..2064b74a92 100644 --- a/invokeai/backend/model_hash/hash_validator.py +++ b/invokeai/backend/model_hash/hash_validator.py @@ -3,6 +3,8 @@ from base64 import b64decode def validate_hash(hash: str): + if not ":" in hash: + return for enc_hash in hashes: alg, hash_ = hash.split(":") if alg == "blake3": From 63a7e19dbfd2d74a5939e7e9b077cf3051d63cec Mon Sep 17 00:00:00 2001 From: Brandon Rising Date: Tue, 18 Jun 2024 09:40:01 -0400 Subject: [PATCH 105/110] Run ruff --- invokeai/backend/model_hash/hash_validator.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/invokeai/backend/model_hash/hash_validator.py b/invokeai/backend/model_hash/hash_validator.py index 2064b74a92..8c38788514 100644 --- a/invokeai/backend/model_hash/hash_validator.py +++ b/invokeai/backend/model_hash/hash_validator.py @@ -3,7 +3,7 @@ from base64 import b64decode def validate_hash(hash: str): - if not ":" in hash: + if ":" not in hash: return for enc_hash in hashes: alg, hash_ = hash.split(":") From d13aafb5146781539bd88e96f9b883d86da12dff Mon Sep 17 00:00:00 2001 From: Ryan Dick Date: Thu, 6 Jun 2024 09:30:49 -0400 Subject: [PATCH 106/110] Tidy denoise_latents.py imports to all use absolute import paths. --- invokeai/app/invocations/denoise_latents.py | 21 ++++++++++----------- 1 file changed, 10 insertions(+), 11 deletions(-) diff --git a/invokeai/app/invocations/denoise_latents.py b/invokeai/app/invocations/denoise_latents.py index 7260fcb168..41e57ec63e 100644 --- a/invokeai/app/invocations/denoise_latents.py +++ b/invokeai/app/invocations/denoise_latents.py @@ -16,7 +16,9 @@ from pydantic import field_validator from torchvision.transforms.functional import resize as tv_resize from transformers import CLIPVisionModelWithProjection +from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR, SCHEDULER_NAME_VALUES +from invokeai.app.invocations.controlnet_image_processors import ControlField from invokeai.app.invocations.fields import ( ConditioningField, DenoiseMaskField, @@ -27,6 +29,7 @@ from invokeai.app.invocations.fields import ( UIType, ) from invokeai.app.invocations.ip_adapter import IPAdapterField +from invokeai.app.invocations.model import ModelIdentifierField, UNetField from invokeai.app.invocations.primitives import LatentsOutput from invokeai.app.invocations.t2i_adapter import T2IAdapterField from invokeai.app.services.shared.invocation_context import InvocationContext @@ -36,6 +39,11 @@ from invokeai.backend.lora import LoRAModelRaw from invokeai.backend.model_manager import BaseModelType from invokeai.backend.model_patcher import ModelPatcher from invokeai.backend.stable_diffusion import PipelineIntermediateState, set_seamless +from invokeai.backend.stable_diffusion.diffusers_pipeline import ( + ControlNetData, + StableDiffusionGeneratorPipeline, + T2IAdapterData, +) from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ( BasicConditioningInfo, IPAdapterConditioningInfo, @@ -45,20 +53,11 @@ from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ( TextConditioningData, TextConditioningRegions, ) +from invokeai.backend.stable_diffusion.schedulers import SCHEDULER_MAP +from invokeai.backend.util.devices import TorchDevice from invokeai.backend.util.mask import to_standard_float_mask from invokeai.backend.util.silence_warnings import SilenceWarnings -from ...backend.stable_diffusion.diffusers_pipeline import ( - ControlNetData, - StableDiffusionGeneratorPipeline, - T2IAdapterData, -) -from ...backend.stable_diffusion.schedulers import SCHEDULER_MAP -from ...backend.util.devices import TorchDevice -from .baseinvocation import BaseInvocation, invocation -from .controlnet_image_processors import ControlField -from .model import ModelIdentifierField, UNetField - def get_scheduler( context: InvocationContext, From 8e47e005a7e2cd404656558b2a27d3f3b14d7f08 Mon Sep 17 00:00:00 2001 From: Ryan Dick Date: Thu, 6 Jun 2024 10:28:00 -0400 Subject: [PATCH 107/110] Tidy SilenceWarnings context manager: - Fix type errors - Enable SilenceWarnings to be used as both a context manager and a decorator - Remove duplicate implementation - Check the initial verbosity on __enter__() rather than __init__() --- invokeai/backend/model_manager/probe.py | 2 +- invokeai/backend/util/silence_warnings.py | 33 ++++++++++++++--------- invokeai/backend/util/util.py | 21 --------------- 3 files changed, 21 insertions(+), 35 deletions(-) diff --git a/invokeai/backend/model_manager/probe.py b/invokeai/backend/model_manager/probe.py index 8f33e4b49f..4aef281bac 100644 --- a/invokeai/backend/model_manager/probe.py +++ b/invokeai/backend/model_manager/probe.py @@ -10,7 +10,7 @@ from picklescan.scanner import scan_file_path import invokeai.backend.util.logging as logger from invokeai.app.util.misc import uuid_string from invokeai.backend.model_hash.model_hash import HASHING_ALGORITHMS, ModelHash -from invokeai.backend.util.util import SilenceWarnings +from invokeai.backend.util.silence_warnings import SilenceWarnings from .config import ( AnyModelConfig, diff --git a/invokeai/backend/util/silence_warnings.py b/invokeai/backend/util/silence_warnings.py index 4c566ba759..0cd6d0738d 100644 --- a/invokeai/backend/util/silence_warnings.py +++ b/invokeai/backend/util/silence_warnings.py @@ -1,29 +1,36 @@ -"""Context class to silence transformers and diffusers warnings.""" - import warnings -from typing import Any +from contextlib import ContextDecorator -from diffusers import logging as diffusers_logging +from diffusers.utils import logging as diffusers_logging from transformers import logging as transformers_logging -class SilenceWarnings(object): - """Use in context to temporarily turn off warnings from transformers & diffusers modules. +# Inherit from ContextDecorator to allow using SilenceWarnings as both a context manager and a decorator. +class SilenceWarnings(ContextDecorator): + """A context manager that disables warnings from transformers & diffusers modules while active. + As context manager: + ``` with SilenceWarnings(): # do something + ``` + + As decorator: + ``` + @SilenceWarnings() + def some_function(): + # do something + ``` """ - def __init__(self) -> None: - self.transformers_verbosity = transformers_logging.get_verbosity() - self.diffusers_verbosity = diffusers_logging.get_verbosity() - def __enter__(self) -> None: + self._transformers_verbosity = transformers_logging.get_verbosity() + self._diffusers_verbosity = diffusers_logging.get_verbosity() transformers_logging.set_verbosity_error() diffusers_logging.set_verbosity_error() warnings.simplefilter("ignore") - def __exit__(self, *args: Any) -> None: - transformers_logging.set_verbosity(self.transformers_verbosity) - diffusers_logging.set_verbosity(self.diffusers_verbosity) + def __exit__(self, *args) -> None: + transformers_logging.set_verbosity(self._transformers_verbosity) + diffusers_logging.set_verbosity(self._diffusers_verbosity) warnings.simplefilter("default") diff --git a/invokeai/backend/util/util.py b/invokeai/backend/util/util.py index 1ee89dcc66..b3466ddba9 100644 --- a/invokeai/backend/util/util.py +++ b/invokeai/backend/util/util.py @@ -3,12 +3,9 @@ import io import os import re import unicodedata -import warnings from pathlib import Path -from diffusers import logging as diffusers_logging from PIL import Image -from transformers import logging as transformers_logging # actual size of a gig GIG = 1073741824 @@ -80,21 +77,3 @@ class Chdir(object): def __exit__(self, *args): os.chdir(self.original) - - -class SilenceWarnings(object): - """Context manager to temporarily lower verbosity of diffusers & transformers warning messages.""" - - def __enter__(self): - """Set verbosity to error.""" - self.transformers_verbosity = transformers_logging.get_verbosity() - self.diffusers_verbosity = diffusers_logging.get_verbosity() - transformers_logging.set_verbosity_error() - diffusers_logging.set_verbosity_error() - warnings.simplefilter("ignore") - - def __exit__(self, type, value, traceback): - """Restore logger verbosity to state before context was entered.""" - transformers_logging.set_verbosity(self.transformers_verbosity) - diffusers_logging.set_verbosity(self.diffusers_verbosity) - warnings.simplefilter("default") From 79ceac2f828e9410be6d2ed0681d9a681eba5d77 Mon Sep 17 00:00:00 2001 From: Ryan Dick Date: Thu, 6 Jun 2024 10:40:19 -0400 Subject: [PATCH 108/110] (minor) Use SilenceWarnings as a decorator rather than a context manager to save an indentation level. --- invokeai/app/invocations/denoise_latents.py | 274 ++++++++++---------- 1 file changed, 137 insertions(+), 137 deletions(-) diff --git a/invokeai/app/invocations/denoise_latents.py b/invokeai/app/invocations/denoise_latents.py index 41e57ec63e..e94daf70bd 100644 --- a/invokeai/app/invocations/denoise_latents.py +++ b/invokeai/app/invocations/denoise_latents.py @@ -657,155 +657,155 @@ class DenoiseLatentsInvocation(BaseInvocation): return 1 - mask, masked_latents, self.denoise_mask.gradient @torch.no_grad() + @SilenceWarnings() # This quenches the NSFW nag from diffusers. def invoke(self, context: InvocationContext) -> LatentsOutput: - with SilenceWarnings(): # this quenches NSFW nag from diffusers - seed = None - noise = None - if self.noise is not None: - noise = context.tensors.load(self.noise.latents_name) - seed = self.noise.seed - - if self.latents is not None: - latents = context.tensors.load(self.latents.latents_name) - if seed is None: - seed = self.latents.seed - - if noise is not None and noise.shape[1:] != latents.shape[1:]: - raise Exception(f"Incompatable 'noise' and 'latents' shapes: {latents.shape=} {noise.shape=}") - - elif noise is not None: - latents = torch.zeros_like(noise) - else: - raise Exception("'latents' or 'noise' must be provided!") + seed = None + noise = None + if self.noise is not None: + noise = context.tensors.load(self.noise.latents_name) + seed = self.noise.seed + if self.latents is not None: + latents = context.tensors.load(self.latents.latents_name) if seed is None: - seed = 0 + seed = self.latents.seed - mask, masked_latents, gradient_mask = self.prep_inpaint_mask(context, latents) + if noise is not None and noise.shape[1:] != latents.shape[1:]: + raise Exception(f"Incompatable 'noise' and 'latents' shapes: {latents.shape=} {noise.shape=}") - # TODO(ryand): I have hard-coded `do_classifier_free_guidance=True` to mirror the behaviour of ControlNets, - # below. Investigate whether this is appropriate. - t2i_adapter_data = self.run_t2i_adapters( - context, - self.t2i_adapter, - latents.shape, - do_classifier_free_guidance=True, + elif noise is not None: + latents = torch.zeros_like(noise) + else: + raise Exception("'latents' or 'noise' must be provided!") + + if seed is None: + seed = 0 + + mask, masked_latents, gradient_mask = self.prep_inpaint_mask(context, latents) + + # TODO(ryand): I have hard-coded `do_classifier_free_guidance=True` to mirror the behaviour of ControlNets, + # below. Investigate whether this is appropriate. + t2i_adapter_data = self.run_t2i_adapters( + context, + self.t2i_adapter, + latents.shape, + do_classifier_free_guidance=True, + ) + + ip_adapters: List[IPAdapterField] = [] + if self.ip_adapter is not None: + # ip_adapter could be a list or a single IPAdapterField. Normalize to a list here. + if isinstance(self.ip_adapter, list): + ip_adapters = self.ip_adapter + else: + ip_adapters = [self.ip_adapter] + + # If there are IP adapters, the following line runs the adapters' CLIPVision image encoders to return + # a series of image conditioning embeddings. This is being done here rather than in the + # big model context below in order to use less VRAM on low-VRAM systems. + # The image prompts are then passed to prep_ip_adapter_data(). + image_prompts = self.prep_ip_adapter_image_prompts(context=context, ip_adapters=ip_adapters) + + # get the unet's config so that we can pass the base to dispatch_progress() + unet_config = context.models.get_config(self.unet.unet.key) + + def step_callback(state: PipelineIntermediateState) -> None: + context.util.sd_step_callback(state, unet_config.base) + + def _lora_loader() -> Iterator[Tuple[LoRAModelRaw, float]]: + for lora in self.unet.loras: + lora_info = context.models.load(lora.lora) + assert isinstance(lora_info.model, LoRAModelRaw) + yield (lora_info.model, lora.weight) + del lora_info + return + + unet_info = context.models.load(self.unet.unet) + assert isinstance(unet_info.model, UNet2DConditionModel) + with ( + ExitStack() as exit_stack, + unet_info.model_on_device() as (model_state_dict, unet), + ModelPatcher.apply_freeu(unet, self.unet.freeu_config), + set_seamless(unet, self.unet.seamless_axes), # FIXME + # Apply the LoRA after unet has been moved to its target device for faster patching. + ModelPatcher.apply_lora_unet( + unet, + loras=_lora_loader(), + model_state_dict=model_state_dict, + ), + ): + assert isinstance(unet, UNet2DConditionModel) + latents = latents.to(device=unet.device, dtype=unet.dtype) + if noise is not None: + noise = noise.to(device=unet.device, dtype=unet.dtype) + if mask is not None: + mask = mask.to(device=unet.device, dtype=unet.dtype) + if masked_latents is not None: + masked_latents = masked_latents.to(device=unet.device, dtype=unet.dtype) + + scheduler = get_scheduler( + context=context, + scheduler_info=self.unet.scheduler, + scheduler_name=self.scheduler, + seed=seed, ) - ip_adapters: List[IPAdapterField] = [] - if self.ip_adapter is not None: - # ip_adapter could be a list or a single IPAdapterField. Normalize to a list here. - if isinstance(self.ip_adapter, list): - ip_adapters = self.ip_adapter - else: - ip_adapters = [self.ip_adapter] + pipeline = self.create_pipeline(unet, scheduler) - # If there are IP adapters, the following line runs the adapters' CLIPVision image encoders to return - # a series of image conditioning embeddings. This is being done here rather than in the - # big model context below in order to use less VRAM on low-VRAM systems. - # The image prompts are then passed to prep_ip_adapter_data(). - image_prompts = self.prep_ip_adapter_image_prompts(context=context, ip_adapters=ip_adapters) + _, _, latent_height, latent_width = latents.shape + conditioning_data = self.get_conditioning_data( + context=context, unet=unet, latent_height=latent_height, latent_width=latent_width + ) - # get the unet's config so that we can pass the base to dispatch_progress() - unet_config = context.models.get_config(self.unet.unet.key) + controlnet_data = self.prep_control_data( + context=context, + control_input=self.control, + latents_shape=latents.shape, + # do_classifier_free_guidance=(self.cfg_scale >= 1.0)) + do_classifier_free_guidance=True, + exit_stack=exit_stack, + ) - def step_callback(state: PipelineIntermediateState) -> None: - context.util.sd_step_callback(state, unet_config.base) + ip_adapter_data = self.prep_ip_adapter_data( + context=context, + ip_adapters=ip_adapters, + image_prompts=image_prompts, + exit_stack=exit_stack, + latent_height=latent_height, + latent_width=latent_width, + dtype=unet.dtype, + ) - def _lora_loader() -> Iterator[Tuple[LoRAModelRaw, float]]: - for lora in self.unet.loras: - lora_info = context.models.load(lora.lora) - assert isinstance(lora_info.model, LoRAModelRaw) - yield (lora_info.model, lora.weight) - del lora_info - return + num_inference_steps, timesteps, init_timestep, scheduler_step_kwargs = self.init_scheduler( + scheduler, + device=unet.device, + steps=self.steps, + denoising_start=self.denoising_start, + denoising_end=self.denoising_end, + seed=seed, + ) - unet_info = context.models.load(self.unet.unet) - assert isinstance(unet_info.model, UNet2DConditionModel) - with ( - ExitStack() as exit_stack, - unet_info.model_on_device() as (model_state_dict, unet), - ModelPatcher.apply_freeu(unet, self.unet.freeu_config), - set_seamless(unet, self.unet.seamless_axes), # FIXME - # Apply the LoRA after unet has been moved to its target device for faster patching. - ModelPatcher.apply_lora_unet( - unet, - loras=_lora_loader(), - model_state_dict=model_state_dict, - ), - ): - assert isinstance(unet, UNet2DConditionModel) - latents = latents.to(device=unet.device, dtype=unet.dtype) - if noise is not None: - noise = noise.to(device=unet.device, dtype=unet.dtype) - if mask is not None: - mask = mask.to(device=unet.device, dtype=unet.dtype) - if masked_latents is not None: - masked_latents = masked_latents.to(device=unet.device, dtype=unet.dtype) + result_latents = pipeline.latents_from_embeddings( + latents=latents, + timesteps=timesteps, + init_timestep=init_timestep, + noise=noise, + seed=seed, + mask=mask, + masked_latents=masked_latents, + gradient_mask=gradient_mask, + num_inference_steps=num_inference_steps, + scheduler_step_kwargs=scheduler_step_kwargs, + conditioning_data=conditioning_data, + control_data=controlnet_data, + ip_adapter_data=ip_adapter_data, + t2i_adapter_data=t2i_adapter_data, + callback=step_callback, + ) - scheduler = get_scheduler( - context=context, - scheduler_info=self.unet.scheduler, - scheduler_name=self.scheduler, - seed=seed, - ) + # https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699 + result_latents = result_latents.to("cpu") + TorchDevice.empty_cache() - pipeline = self.create_pipeline(unet, scheduler) - - _, _, latent_height, latent_width = latents.shape - conditioning_data = self.get_conditioning_data( - context=context, unet=unet, latent_height=latent_height, latent_width=latent_width - ) - - controlnet_data = self.prep_control_data( - context=context, - control_input=self.control, - latents_shape=latents.shape, - # do_classifier_free_guidance=(self.cfg_scale >= 1.0)) - do_classifier_free_guidance=True, - exit_stack=exit_stack, - ) - - ip_adapter_data = self.prep_ip_adapter_data( - context=context, - ip_adapters=ip_adapters, - image_prompts=image_prompts, - exit_stack=exit_stack, - latent_height=latent_height, - latent_width=latent_width, - dtype=unet.dtype, - ) - - num_inference_steps, timesteps, init_timestep, scheduler_step_kwargs = self.init_scheduler( - scheduler, - device=unet.device, - steps=self.steps, - denoising_start=self.denoising_start, - denoising_end=self.denoising_end, - seed=seed, - ) - - result_latents = pipeline.latents_from_embeddings( - latents=latents, - timesteps=timesteps, - init_timestep=init_timestep, - noise=noise, - seed=seed, - mask=mask, - masked_latents=masked_latents, - gradient_mask=gradient_mask, - num_inference_steps=num_inference_steps, - scheduler_step_kwargs=scheduler_step_kwargs, - conditioning_data=conditioning_data, - control_data=controlnet_data, - ip_adapter_data=ip_adapter_data, - t2i_adapter_data=t2i_adapter_data, - callback=step_callback, - ) - - # https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699 - result_latents = result_latents.to("cpu") - TorchDevice.empty_cache() - - name = context.tensors.save(tensor=result_latents) + name = context.tensors.save(tensor=result_latents) return LatentsOutput.build(latents_name=name, latents=result_latents, seed=None) From a43d602f16b41c3023fa9556205af8173345f58b Mon Sep 17 00:00:00 2001 From: steffylo Date: Wed, 19 Jun 2024 05:32:13 +0800 Subject: [PATCH 109/110] fix(queue): add clear_queue_on_startup config to clear problematic queues --- invokeai/app/services/config/config_default.py | 2 ++ .../services/session_queue/session_queue_sqlite.py | 12 ++++++++---- 2 files changed, 10 insertions(+), 4 deletions(-) diff --git a/invokeai/app/services/config/config_default.py b/invokeai/app/services/config/config_default.py index 496988e853..1dc75add1d 100644 --- a/invokeai/app/services/config/config_default.py +++ b/invokeai/app/services/config/config_default.py @@ -113,6 +113,7 @@ class InvokeAIAppConfig(BaseSettings): force_tiled_decode: Whether to enable tiled VAE decode (reduces memory consumption with some performance penalty). pil_compress_level: The compress_level setting of PIL.Image.save(), used for PNG encoding. All settings are lossless. 0 = no compression, 1 = fastest with slightly larger filesize, 9 = slowest with smallest filesize. 1 is typically the best setting. max_queue_size: Maximum number of items in the session queue. + clear_queue_on_startup: Empties session queue on startup. allow_nodes: List of nodes to allow. Omit to allow all. deny_nodes: List of nodes to deny. Omit to deny none. node_cache_size: How many cached nodes to keep in memory. @@ -186,6 +187,7 @@ class InvokeAIAppConfig(BaseSettings): force_tiled_decode: bool = Field(default=False, description="Whether to enable tiled VAE decode (reduces memory consumption with some performance penalty).") pil_compress_level: int = Field(default=1, description="The compress_level setting of PIL.Image.save(), used for PNG encoding. All settings are lossless. 0 = no compression, 1 = fastest with slightly larger filesize, 9 = slowest with smallest filesize. 1 is typically the best setting.") max_queue_size: int = Field(default=10000, gt=0, description="Maximum number of items in the session queue.") + clear_queue_on_startup: bool = Field(default=False, description="Empties session queue on startup.") # NODES allow_nodes: Optional[list[str]] = Field(default=None, description="List of nodes to allow. Omit to allow all.") diff --git a/invokeai/app/services/session_queue/session_queue_sqlite.py b/invokeai/app/services/session_queue/session_queue_sqlite.py index 467853aae4..a3a7004c94 100644 --- a/invokeai/app/services/session_queue/session_queue_sqlite.py +++ b/invokeai/app/services/session_queue/session_queue_sqlite.py @@ -37,10 +37,14 @@ class SqliteSessionQueue(SessionQueueBase): def start(self, invoker: Invoker) -> None: self.__invoker = invoker self._set_in_progress_to_canceled() - prune_result = self.prune(DEFAULT_QUEUE_ID) - - if prune_result.deleted > 0: - self.__invoker.services.logger.info(f"Pruned {prune_result.deleted} finished queue items") + if self.__invoker.services.configuration.clear_queue_on_startup: + clear_result = self.clear(DEFAULT_QUEUE_ID) + if clear_result.deleted > 0: + self.__invoker.services.logger.info(f"Cleared all {clear_result.deleted} queue items") + else: + prune_result = self.prune(DEFAULT_QUEUE_ID) + if prune_result.deleted > 0: + self.__invoker.services.logger.info(f"Pruned {prune_result.deleted} finished queue items") def __init__(self, db: SqliteDatabase) -> None: super().__init__() From b03073d888b5f8cd77a119a4d8612c235c480859 Mon Sep 17 00:00:00 2001 From: Lincoln Stein Date: Wed, 19 Jun 2024 22:57:27 -0400 Subject: [PATCH 110/110] [MM] Add support for probing and loading SDXL VAE checkpoint files (#6524) * add support for probing and loading SDXL VAE checkpoint files * broaden regexp probe for SDXL VAEs --------- Co-authored-by: Lincoln Stein --- .../backend/model_manager/load/model_loaders/vae.py | 11 +++-------- invokeai/backend/model_manager/probe.py | 12 ++++++++++-- 2 files changed, 13 insertions(+), 10 deletions(-) diff --git a/invokeai/backend/model_manager/load/model_loaders/vae.py b/invokeai/backend/model_manager/load/model_loaders/vae.py index 122b2f0797..f51c551f09 100644 --- a/invokeai/backend/model_manager/load/model_loaders/vae.py +++ b/invokeai/backend/model_manager/load/model_loaders/vae.py @@ -22,8 +22,7 @@ from .generic_diffusers import GenericDiffusersLoader @ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.VAE, format=ModelFormat.Diffusers) -@ModelLoaderRegistry.register(base=BaseModelType.StableDiffusion1, type=ModelType.VAE, format=ModelFormat.Checkpoint) -@ModelLoaderRegistry.register(base=BaseModelType.StableDiffusion2, type=ModelType.VAE, format=ModelFormat.Checkpoint) +@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.VAE, format=ModelFormat.Checkpoint) class VAELoader(GenericDiffusersLoader): """Class to load VAE models.""" @@ -40,12 +39,8 @@ class VAELoader(GenericDiffusersLoader): return True def _convert_model(self, config: AnyModelConfig, model_path: Path, output_path: Optional[Path] = None) -> AnyModel: - # TODO(MM2): check whether sdxl VAE models convert. - if config.base not in {BaseModelType.StableDiffusion1, BaseModelType.StableDiffusion2}: - raise Exception(f"VAE conversion not supported for model type: {config.base}") - else: - assert isinstance(config, CheckpointConfigBase) - config_file = self._app_config.legacy_conf_path / config.config_path + assert isinstance(config, CheckpointConfigBase) + config_file = self._app_config.legacy_conf_path / config.config_path if model_path.suffix == ".safetensors": checkpoint = safetensors_load_file(model_path, device="cpu") diff --git a/invokeai/backend/model_manager/probe.py b/invokeai/backend/model_manager/probe.py index 4aef281bac..a19a772764 100644 --- a/invokeai/backend/model_manager/probe.py +++ b/invokeai/backend/model_manager/probe.py @@ -451,8 +451,16 @@ class PipelineCheckpointProbe(CheckpointProbeBase): class VaeCheckpointProbe(CheckpointProbeBase): def get_base_type(self) -> BaseModelType: - # I can't find any standalone 2.X VAEs to test with! - return BaseModelType.StableDiffusion1 + # VAEs of all base types have the same structure, so we wimp out and + # guess using the name. + for regexp, basetype in [ + (r"xl", BaseModelType.StableDiffusionXL), + (r"sd2", BaseModelType.StableDiffusion2), + (r"vae", BaseModelType.StableDiffusion1), + ]: + if re.search(regexp, self.model_path.name, re.IGNORECASE): + return basetype + raise InvalidModelConfigException("Cannot determine base type") class LoRACheckpointProbe(CheckpointProbeBase):