diff --git a/.github/workflows/style-checks.yml b/.github/workflows/style-checks.yml
index d29b489418..96e1df406b 100644
--- a/.github/workflows/style-checks.yml
+++ b/.github/workflows/style-checks.yml
@@ -1,6 +1,6 @@
name: style checks
-# just formatting for now
-# TODO: add isort and flake8 later
+# just formatting and flake8 for now
+# TODO: add isort later
on:
pull_request:
@@ -20,8 +20,8 @@ jobs:
- name: Install dependencies with pip
run: |
- pip install black
+ pip install black flake8 Flake8-pyproject
# - run: isort --check-only .
- run: black --check .
- # - run: flake8
+ - run: flake8
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 2b16b274d6..9ef8b79e77 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -8,3 +8,10 @@ repos:
language: system
entry: black
types: [python]
+
+ - id: flake8
+ name: flake8
+ stages: [commit]
+ language: system
+ entry: flake8
+ types: [python]
diff --git a/installer/lib/installer.py b/installer/lib/installer.py
index cc694c2934..aaf5779801 100644
--- a/installer/lib/installer.py
+++ b/installer/lib/installer.py
@@ -407,7 +407,7 @@ def get_pip_from_venv(venv_path: Path) -> str:
:rtype: str
"""
- pip = "Scripts\pip.exe" if OS == "Windows" else "bin/pip"
+ pip = "Scripts\\pip.exe" if OS == "Windows" else "bin/pip"
return str(venv_path.expanduser().resolve() / pip)
diff --git a/installer/lib/main.py b/installer/lib/main.py
index 4f1372652b..5c9e6f8229 100644
--- a/installer/lib/main.py
+++ b/installer/lib/main.py
@@ -49,7 +49,7 @@ if __name__ == "__main__":
try:
inst.install(**args.__dict__)
- except KeyboardInterrupt as exc:
+ except KeyboardInterrupt:
print("\n")
print("Ctrl-C pressed. Aborting.")
print("Come back soon!")
diff --git a/installer/lib/messages.py b/installer/lib/messages.py
index e6362b75d0..c5a39dc91c 100644
--- a/installer/lib/messages.py
+++ b/installer/lib/messages.py
@@ -70,7 +70,7 @@ def confirm_install(dest: Path) -> bool:
)
else:
print(f"InvokeAI will be installed in {dest}")
- dest_confirmed = not Confirm.ask(f"Would you like to pick a different location?", default=False)
+ dest_confirmed = not Confirm.ask("Would you like to pick a different location?", default=False)
console.line()
return dest_confirmed
@@ -90,7 +90,7 @@ def dest_path(dest=None) -> Path:
dest = Path(dest).expanduser().resolve()
else:
dest = Path.cwd().expanduser().resolve()
- prev_dest = dest.expanduser().resolve()
+ prev_dest = init_path = dest
dest_confirmed = confirm_install(dest)
@@ -109,9 +109,9 @@ def dest_path(dest=None) -> Path:
)
console.line()
- print(f"[orange3]Please select the destination directory for the installation:[/] \[{browse_start}]: ")
+ console.print(f"[orange3]Please select the destination directory for the installation:[/] \\[{browse_start}]: ")
selected = prompt(
- f">>> ",
+ ">>> ",
complete_in_thread=True,
completer=path_completer,
default=str(browse_start) + os.sep,
@@ -134,14 +134,14 @@ def dest_path(dest=None) -> Path:
try:
dest.mkdir(exist_ok=True, parents=True)
return dest
- except PermissionError as exc:
- print(
+ except PermissionError:
+ console.print(
f"Failed to create directory {dest} due to insufficient permissions",
style=Style(color="red"),
highlight=True,
)
- except OSError as exc:
- console.print_exception(exc)
+ except OSError:
+ console.print_exception()
if Confirm.ask("Would you like to try again?"):
dest_path(init_path)
diff --git a/invokeai/app/api/dependencies.py b/invokeai/app/api/dependencies.py
index 4aaf7a0272..39642df19b 100644
--- a/invokeai/app/api/dependencies.py
+++ b/invokeai/app/api/dependencies.py
@@ -1,6 +1,5 @@
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
-from typing import Optional
from logging import Logger
from invokeai.app.services.board_image_record_storage import (
SqliteBoardImageRecordStorage,
@@ -45,7 +44,7 @@ def check_internet() -> bool:
try:
urllib.request.urlopen(host, timeout=1)
return True
- except:
+ except Exception:
return False
diff --git a/invokeai/app/api/routers/board_images.py b/invokeai/app/api/routers/board_images.py
index 73607ecb7d..8e36a682d2 100644
--- a/invokeai/app/api/routers/board_images.py
+++ b/invokeai/app/api/routers/board_images.py
@@ -34,7 +34,7 @@ async def add_image_to_board(
board_id=board_id, image_name=image_name
)
return result
- except Exception as e:
+ except Exception:
raise HTTPException(status_code=500, detail="Failed to add image to board")
@@ -53,7 +53,7 @@ async def remove_image_from_board(
try:
result = ApiDependencies.invoker.services.board_images.remove_image_from_board(image_name=image_name)
return result
- except Exception as e:
+ except Exception:
raise HTTPException(status_code=500, detail="Failed to remove image from board")
@@ -79,10 +79,10 @@ async def add_images_to_board(
board_id=board_id, image_name=image_name
)
added_image_names.append(image_name)
- except:
+ except Exception:
pass
return AddImagesToBoardResult(board_id=board_id, added_image_names=added_image_names)
- except Exception as e:
+ except Exception:
raise HTTPException(status_code=500, detail="Failed to add images to board")
@@ -105,8 +105,8 @@ async def remove_images_from_board(
try:
ApiDependencies.invoker.services.board_images.remove_image_from_board(image_name=image_name)
removed_image_names.append(image_name)
- except:
+ except Exception:
pass
return RemoveImagesFromBoardResult(removed_image_names=removed_image_names)
- except Exception as e:
+ except Exception:
raise HTTPException(status_code=500, detail="Failed to remove images from board")
diff --git a/invokeai/app/api/routers/boards.py b/invokeai/app/api/routers/boards.py
index 69f4a8b3a7..630135f236 100644
--- a/invokeai/app/api/routers/boards.py
+++ b/invokeai/app/api/routers/boards.py
@@ -37,7 +37,7 @@ async def create_board(
try:
result = ApiDependencies.invoker.services.boards.create(board_name=board_name)
return result
- except Exception as e:
+ except Exception:
raise HTTPException(status_code=500, detail="Failed to create board")
@@ -50,7 +50,7 @@ async def get_board(
try:
result = ApiDependencies.invoker.services.boards.get_dto(board_id=board_id)
return result
- except Exception as e:
+ except Exception:
raise HTTPException(status_code=404, detail="Board not found")
@@ -73,7 +73,7 @@ async def update_board(
try:
result = ApiDependencies.invoker.services.boards.update(board_id=board_id, changes=changes)
return result
- except Exception as e:
+ except Exception:
raise HTTPException(status_code=500, detail="Failed to update board")
@@ -105,7 +105,7 @@ async def delete_board(
deleted_board_images=deleted_board_images,
deleted_images=[],
)
- except Exception as e:
+ except Exception:
raise HTTPException(status_code=500, detail="Failed to delete board")
diff --git a/invokeai/app/api/routers/images.py b/invokeai/app/api/routers/images.py
index 692dc7fd21..72ce94e9cf 100644
--- a/invokeai/app/api/routers/images.py
+++ b/invokeai/app/api/routers/images.py
@@ -55,7 +55,7 @@ async def upload_image(
if crop_visible:
bbox = pil_image.getbbox()
pil_image = pil_image.crop(bbox)
- except:
+ except Exception:
# Error opening the image
raise HTTPException(status_code=415, detail="Failed to read image")
@@ -73,7 +73,7 @@ async def upload_image(
response.headers["Location"] = image_dto.image_url
return image_dto
- except Exception as e:
+ except Exception:
raise HTTPException(status_code=500, detail="Failed to create image")
@@ -85,7 +85,7 @@ async def delete_image(
try:
ApiDependencies.invoker.services.images.delete(image_name)
- except Exception as e:
+ except Exception:
# TODO: Does this need any exception handling at all?
pass
@@ -97,7 +97,7 @@ async def clear_intermediates() -> int:
try:
count_deleted = ApiDependencies.invoker.services.images.delete_intermediates()
return count_deleted
- except Exception as e:
+ except Exception:
raise HTTPException(status_code=500, detail="Failed to clear intermediates")
pass
@@ -115,7 +115,7 @@ async def update_image(
try:
return ApiDependencies.invoker.services.images.update(image_name, image_changes)
- except Exception as e:
+ except Exception:
raise HTTPException(status_code=400, detail="Failed to update image")
@@ -131,7 +131,7 @@ async def get_image_dto(
try:
return ApiDependencies.invoker.services.images.get_dto(image_name)
- except Exception as e:
+ except Exception:
raise HTTPException(status_code=404)
@@ -147,7 +147,7 @@ async def get_image_metadata(
try:
return ApiDependencies.invoker.services.images.get_metadata(image_name)
- except Exception as e:
+ except Exception:
raise HTTPException(status_code=404)
@@ -183,7 +183,7 @@ async def get_image_full(
)
response.headers["Cache-Control"] = f"max-age={IMAGE_MAX_AGE}"
return response
- except Exception as e:
+ except Exception:
raise HTTPException(status_code=404)
@@ -212,7 +212,7 @@ async def get_image_thumbnail(
response = FileResponse(path, media_type="image/webp", content_disposition_type="inline")
response.headers["Cache-Control"] = f"max-age={IMAGE_MAX_AGE}"
return response
- except Exception as e:
+ except Exception:
raise HTTPException(status_code=404)
@@ -234,7 +234,7 @@ async def get_image_urls(
image_url=image_url,
thumbnail_url=thumbnail_url,
)
- except Exception as e:
+ except Exception:
raise HTTPException(status_code=404)
@@ -282,10 +282,10 @@ async def delete_images_from_list(
try:
ApiDependencies.invoker.services.images.delete(image_name)
deleted_images.append(image_name)
- except:
+ except Exception:
pass
return DeleteImagesFromListResult(deleted_images=deleted_images)
- except Exception as e:
+ except Exception:
raise HTTPException(status_code=500, detail="Failed to delete images")
@@ -303,10 +303,10 @@ async def star_images_in_list(
try:
ApiDependencies.invoker.services.images.update(image_name, changes=ImageRecordChanges(starred=True))
updated_image_names.append(image_name)
- except:
+ except Exception:
pass
return ImagesUpdatedFromListResult(updated_image_names=updated_image_names)
- except Exception as e:
+ except Exception:
raise HTTPException(status_code=500, detail="Failed to star images")
@@ -320,8 +320,8 @@ async def unstar_images_in_list(
try:
ApiDependencies.invoker.services.images.update(image_name, changes=ImageRecordChanges(starred=False))
updated_image_names.append(image_name)
- except:
+ except Exception:
pass
return ImagesUpdatedFromListResult(updated_image_names=updated_image_names)
- except Exception as e:
+ except Exception:
raise HTTPException(status_code=500, detail="Failed to unstar images")
diff --git a/invokeai/app/api/routers/sessions.py b/invokeai/app/api/routers/sessions.py
index e4ba2a353e..d5624048e8 100644
--- a/invokeai/app/api/routers/sessions.py
+++ b/invokeai/app/api/routers/sessions.py
@@ -1,12 +1,13 @@
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
-from typing import Annotated, List, Optional, Union
+from typing import Annotated, Optional, Union
from fastapi import Body, HTTPException, Path, Query, Response
from fastapi.routing import APIRouter
from pydantic.fields import Field
-from ...invocations import *
+# Importing * is bad karma but needed here for node detection
+from ...invocations import * # noqa: F401 F403
from ...invocations.baseinvocation import BaseInvocation
from ...services.graph import (
Edge,
diff --git a/invokeai/app/api_app.py b/invokeai/app/api_app.py
index e5e6e26e88..7ed2dedd44 100644
--- a/invokeai/app/api_app.py
+++ b/invokeai/app/api_app.py
@@ -2,7 +2,6 @@
import asyncio
import logging
import socket
-import sys
from inspect import signature
from pathlib import Path
@@ -16,21 +15,11 @@ from fastapi_events.handlers.local import local_handler
from fastapi_events.middleware import EventHandlerASGIMiddleware
from pydantic.schema import schema
-# This should come early so that modules can log their initialization properly
from .services.config import InvokeAIAppConfig
from ..backend.util.logging import InvokeAILogger
-app_config = InvokeAIAppConfig.get_config()
-app_config.parse_args()
-logger = InvokeAILogger.getLogger(config=app_config)
from invokeai.version.invokeai_version import __version__
-# we call this early so that the message appears before
-# other invokeai initialization messages
-if app_config.version:
- print(f"InvokeAI version {__version__}")
- sys.exit(0)
-
import invokeai.frontend.web as web_dir
import mimetypes
@@ -39,15 +28,19 @@ from .api.routers import sessions, models, images, boards, board_images, app_inf
from .api.sockets import SocketIO
from .invocations.baseinvocation import BaseInvocation, _InputField, _OutputField, UIConfigBase
-
import torch
# noinspection PyUnresolvedReferences
-import invokeai.backend.util.hotfixes
+import invokeai.backend.util.hotfixes # noqa: F401 (monkeypatching on import)
if torch.backends.mps.is_available():
# noinspection PyUnresolvedReferences
- import invokeai.backend.util.mps_fixes
+ import invokeai.backend.util.mps_fixes # noqa: F401 (monkeypatching on import)
+
+
+app_config = InvokeAIAppConfig.get_config()
+app_config.parse_args()
+logger = InvokeAILogger.getLogger(config=app_config)
# fix for windows mimetypes registry entries being borked
# see https://github.com/invoke-ai/InvokeAI/discussions/3684#discussioncomment-6391352
@@ -243,13 +236,16 @@ def invoke_api():
# replace uvicorn's loggers with InvokeAI's for consistent appearance
for logname in ["uvicorn.access", "uvicorn"]:
- l = logging.getLogger(logname)
- l.handlers.clear()
+ log = logging.getLogger(logname)
+ log.handlers.clear()
for ch in logger.handlers:
- l.addHandler(ch)
+ log.addHandler(ch)
loop.run_until_complete(server.serve())
if __name__ == "__main__":
- invoke_api()
+ if app_config.version:
+ print(f"InvokeAI version {__version__}")
+ else:
+ invoke_api()
diff --git a/invokeai/app/cli/completer.py b/invokeai/app/cli/completer.py
index fd10034dd7..086d8713d7 100644
--- a/invokeai/app/cli/completer.py
+++ b/invokeai/app/cli/completer.py
@@ -145,10 +145,10 @@ def set_autocompleter(services: InvocationServices) -> Completer:
completer = Completer(services.model_manager)
readline.set_completer(completer.complete)
- # pyreadline3 does not have a set_auto_history() method
try:
readline.set_auto_history(True)
- except:
+ except AttributeError:
+ # pyreadline3 does not have a set_auto_history() method
pass
readline.set_pre_input_hook(completer._pre_input_hook)
readline.set_completer_delims(" ")
diff --git a/invokeai/app/cli_app.py b/invokeai/app/cli_app.py
index 4558c9219f..dfde3d1f58 100644
--- a/invokeai/app/cli_app.py
+++ b/invokeai/app/cli_app.py
@@ -13,16 +13,8 @@ from pydantic.fields import Field
# This should come early so that the logger can pick up its configuration options
from .services.config import InvokeAIAppConfig
from invokeai.backend.util.logging import InvokeAILogger
-
-config = InvokeAIAppConfig.get_config()
-config.parse_args()
-logger = InvokeAILogger().getLogger(config=config)
from invokeai.version.invokeai_version import __version__
-# we call this early so that the message appears before other invokeai initialization messages
-if config.version:
- print(f"InvokeAI version {__version__}")
- sys.exit(0)
from invokeai.app.services.board_image_record_storage import (
SqliteBoardImageRecordStorage,
@@ -62,10 +54,15 @@ from .services.processor import DefaultInvocationProcessor
from .services.sqlite import SqliteItemStorage
import torch
-import invokeai.backend.util.hotfixes
+import invokeai.backend.util.hotfixes # noqa: F401 (monkeypatching on import)
if torch.backends.mps.is_available():
- import invokeai.backend.util.mps_fixes
+ import invokeai.backend.util.mps_fixes # noqa: F401 (monkeypatching on import)
+
+
+config = InvokeAIAppConfig.get_config()
+config.parse_args()
+logger = InvokeAILogger().getLogger(config=config)
class CliCommand(BaseModel):
@@ -482,4 +479,7 @@ def invoke_cli():
if __name__ == "__main__":
- invoke_cli()
+ if config.version:
+ print(f"InvokeAI version {__version__}")
+ else:
+ invoke_cli()
diff --git a/invokeai/app/invocations/baseinvocation.py b/invokeai/app/invocations/baseinvocation.py
index 363fa357ae..11d9d40047 100644
--- a/invokeai/app/invocations/baseinvocation.py
+++ b/invokeai/app/invocations/baseinvocation.py
@@ -71,6 +71,9 @@ class FieldDescriptions:
safe_mode = "Whether or not to use safe mode"
scribble_mode = "Whether or not to use scribble mode"
scale_factor = "The factor by which to scale"
+ blend_alpha = (
+ "Blending factor. 0.0 = use input A only, 1.0 = use input B only, 0.5 = 50% mix of input A and input B."
+ )
num_1 = "The first number"
num_2 = "The second number"
mask = "The mask to use for the operation"
@@ -230,7 +233,7 @@ def InputField(
Internally, there is no difference between SD-1, SD-2 and SDXL model fields, they all use \
`MainModelField`. So to ensure the base-model-specific UI is rendered, you can use \
`UIType.SDXLMainModelField` to indicate that the field is an SDXL main model field.
-
+
:param UIComponent ui_component: [None] Optionally specifies a specific component to use in the UI. \
The UI will always render a suitable component, but sometimes you want something different than the default. \
For example, a `string` field will default to a single-line input, but you may want a multi-line textarea instead. \
diff --git a/invokeai/app/invocations/collections.py b/invokeai/app/invocations/collections.py
index fc7aec3e01..65bce2737e 100644
--- a/invokeai/app/invocations/collections.py
+++ b/invokeai/app/invocations/collections.py
@@ -5,10 +5,10 @@ from typing import Literal
import numpy as np
from pydantic import validator
-from invokeai.app.invocations.primitives import ImageCollectionOutput, ImageField, IntegerCollectionOutput
+from invokeai.app.invocations.primitives import IntegerCollectionOutput
from invokeai.app.util.misc import SEED_MAX, get_random_seed
-from .baseinvocation import BaseInvocation, InputField, InvocationContext, UIType, tags, title
+from .baseinvocation import BaseInvocation, InputField, InvocationContext, tags, title
@title("Integer Range")
diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py
index 0be33ce701..71d5ba779c 100644
--- a/invokeai/app/invocations/compel.py
+++ b/invokeai/app/invocations/compel.py
@@ -12,7 +12,7 @@ from invokeai.backend.stable_diffusion.diffusion.shared_invokeai_diffusion impor
SDXLConditioningInfo,
)
-from ...backend.model_management import ModelPatcher, ModelType
+from ...backend.model_management.models import ModelType
from ...backend.model_management.lora import ModelPatcher
from ...backend.model_management.models import ModelNotFoundException
from ...backend.stable_diffusion.diffusion import InvokeAIDiffuserComponent
@@ -233,7 +233,7 @@ class SDXLPromptInvocationBase:
dtype_for_device_getter=torch_dtype,
truncate_long_prompts=True, # TODO:
returned_embeddings_type=ReturnedEmbeddingsType.PENULTIMATE_HIDDEN_STATES_NON_NORMALIZED, # TODO: clip skip
- requires_pooled=True,
+ requires_pooled=get_pooled,
)
conjunction = Compel.parse_prompt_string(prompt)
diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py
index 811f767dee..c594a84fb3 100644
--- a/invokeai/app/invocations/controlnet_image_processors.py
+++ b/invokeai/app/invocations/controlnet_image_processors.py
@@ -29,7 +29,7 @@ from pydantic import BaseModel, Field, validator
from invokeai.app.invocations.primitives import ImageField, ImageOutput
-from ...backend.model_management import BaseModelType, ModelType
+from ...backend.model_management import BaseModelType
from ..models.image import ImageCategory, ResourceOrigin
from .baseinvocation import (
BaseInvocation,
diff --git a/invokeai/app/invocations/infill.py b/invokeai/app/invocations/infill.py
index 1547191f6c..fea418567b 100644
--- a/invokeai/app/invocations/infill.py
+++ b/invokeai/app/invocations/infill.py
@@ -90,7 +90,7 @@ def tile_fill_missing(im: Image.Image, tile_size: int = 16, seed: Optional[int]
return im
# Find all invalid tiles and replace with a random valid tile
- replace_count = (tiles_mask == False).sum()
+ replace_count = (tiles_mask is False).sum()
rng = np.random.default_rng(seed=seed)
tiles_all[np.logical_not(tiles_mask)] = filtered_tiles[rng.choice(filtered_tiles.shape[0], replace_count), :, :, :]
diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index 40f7af8703..f65a95999d 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -4,6 +4,7 @@ from contextlib import ExitStack
from typing import List, Literal, Optional, Union
import einops
+import numpy as np
import torch
import torchvision.transforms as T
from diffusers.image_processor import VaeImageProcessor
@@ -15,7 +16,7 @@ from diffusers.models.attention_processor import (
)
from diffusers.schedulers import DPMSolverSDEScheduler
from diffusers.schedulers import SchedulerMixin as Scheduler
-from pydantic import BaseModel, Field, validator
+from pydantic import validator
from torchvision.transforms.functional import resize as tv_resize
from invokeai.app.invocations.metadata import CoreMetadata
@@ -30,7 +31,7 @@ from invokeai.app.util.controlnet_utils import prepare_control_image
from invokeai.app.util.step_callback import stable_diffusion_step_callback
from invokeai.backend.model_management.models import ModelType, SilenceWarnings
-from ...backend.model_management import BaseModelType, ModelPatcher
+from ...backend.model_management.models import BaseModelType
from ...backend.model_management.lora import ModelPatcher
from ...backend.stable_diffusion import PipelineIntermediateState
from ...backend.stable_diffusion.diffusers_pipeline import (
@@ -45,12 +46,10 @@ from ...backend.util.devices import choose_precision, choose_torch_device
from ..models.image import ImageCategory, ResourceOrigin
from .baseinvocation import (
BaseInvocation,
- BaseInvocationOutput,
FieldDescriptions,
Input,
InputField,
InvocationContext,
- OutputField,
UIType,
tags,
title,
@@ -722,3 +721,81 @@ class ImageToLatentsInvocation(BaseInvocation):
latents = latents.to("cpu")
context.services.latents.save(name, latents)
return build_latents_output(latents_name=name, latents=latents, seed=None)
+
+
+@title("Blend Latents")
+@tags("latents", "blend")
+class BlendLatentsInvocation(BaseInvocation):
+ """Blend two latents using a given alpha. Latents must have same size."""
+
+ type: Literal["lblend"] = "lblend"
+
+ # Inputs
+ 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.services.latents.get(self.latents_a.latents_name)
+ latents_b = context.services.latents.get(self.latents_b.latents_name)
+
+ if latents_a.shape != latents_b.shape:
+ raise "Latents to blend must be the same size."
+
+ # TODO:
+ device = choose_torch_device()
+
+ def slerp(t, v0, v1, DOT_THRESHOLD=0.9995):
+ """
+ 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.from_numpy(v2).to(device)
+
+ return v2
+
+ # blend
+ blended_latents = slerp(self.alpha, latents_a, latents_b)
+
+ # https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699
+ blended_latents = blended_latents.to("cpu")
+ torch.cuda.empty_cache()
+
+ name = f"{context.graph_execution_state_id}__{self.id}"
+ # context.services.latents.set(name, resized_latents)
+ context.services.latents.save(name, blended_latents)
+ return build_latents_output(latents_name=name, latents=blended_latents)
diff --git a/invokeai/app/invocations/model.py b/invokeai/app/invocations/model.py
index 484a4d71e1..cecca78651 100644
--- a/invokeai/app/invocations/model.py
+++ b/invokeai/app/invocations/model.py
@@ -1,5 +1,5 @@
import copy
-from typing import List, Literal, Optional, Union
+from typing import List, Literal, Optional
from pydantic import BaseModel, Field
diff --git a/invokeai/app/invocations/noise.py b/invokeai/app/invocations/noise.py
index 6fae308fdc..d1dd320ee8 100644
--- a/invokeai/app/invocations/noise.py
+++ b/invokeai/app/invocations/noise.py
@@ -16,7 +16,6 @@ from .baseinvocation import (
InputField,
InvocationContext,
OutputField,
- UIType,
tags,
title,
)
diff --git a/invokeai/app/invocations/onnx.py b/invokeai/app/invocations/onnx.py
index 6cff56fb2e..3e65c1e55d 100644
--- a/invokeai/app/invocations/onnx.py
+++ b/invokeai/app/invocations/onnx.py
@@ -2,14 +2,13 @@
import inspect
import re
-from contextlib import ExitStack
+
+# from contextlib import ExitStack
from typing import List, Literal, Optional, Union
import numpy as np
import torch
-from diffusers import ControlNetModel, DPMSolverMultistepScheduler
from diffusers.image_processor import VaeImageProcessor
-from diffusers.schedulers import SchedulerMixin as Scheduler
from pydantic import BaseModel, Field, validator
from tqdm import tqdm
@@ -72,7 +71,7 @@ class ONNXPromptInvocation(BaseInvocation):
text_encoder_info = context.services.model_manager.get_model(
**self.clip.text_encoder.dict(),
)
- with tokenizer_info as orig_tokenizer, text_encoder_info as text_encoder, ExitStack() as stack:
+ with tokenizer_info as orig_tokenizer, text_encoder_info as text_encoder: # , ExitStack() as stack:
loras = [
(context.services.model_manager.get_model(**lora.dict(exclude={"weight"})).context.model, lora.weight)
for lora in self.clip.loras
@@ -259,7 +258,7 @@ class ONNXTextToLatentsInvocation(BaseInvocation):
unet_info = context.services.model_manager.get_model(**self.unet.unet.dict())
- with unet_info as unet, ExitStack() as stack:
+ with unet_info as unet: # , ExitStack() as stack:
# loras = [(stack.enter_context(context.services.model_manager.get_model(**lora.dict(exclude={"weight"}))), lora.weight) for lora in self.unet.loras]
loras = [
(context.services.model_manager.get_model(**lora.dict(exclude={"weight"})).context.model, lora.weight)
diff --git a/invokeai/app/invocations/param_easing.py b/invokeai/app/invocations/param_easing.py
index 67f96b0c34..70baa85817 100644
--- a/invokeai/app/invocations/param_easing.py
+++ b/invokeai/app/invocations/param_easing.py
@@ -38,13 +38,10 @@ from easing_functions import (
SineEaseInOut,
SineEaseOut,
)
-from matplotlib.figure import Figure
from matplotlib.ticker import MaxNLocator
-from pydantic import BaseModel, Field
from invokeai.app.invocations.primitives import FloatCollectionOutput
-from ...backend.util.logging import InvokeAILogger
from .baseinvocation import BaseInvocation, InputField, InvocationContext, tags, title
diff --git a/invokeai/app/invocations/primitives.py b/invokeai/app/invocations/primitives.py
index 61ef9fa27c..f32cb14f3a 100644
--- a/invokeai/app/invocations/primitives.py
+++ b/invokeai/app/invocations/primitives.py
@@ -1,7 +1,6 @@
# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
-from typing import Literal, Optional, Tuple, Union
-from anyio import Condition
+from typing import Literal, Optional, Tuple
from pydantic import BaseModel, Field
import torch
diff --git a/invokeai/app/invocations/upscale.py b/invokeai/app/invocations/upscale.py
index cd4463e174..6e6d440adf 100644
--- a/invokeai/app/invocations/upscale.py
+++ b/invokeai/app/invocations/upscale.py
@@ -1,6 +1,6 @@
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) & the InvokeAI Team
from pathlib import Path
-from typing import Literal, Union
+from typing import Literal
import cv2 as cv
import numpy as np
diff --git a/invokeai/app/services/board_images.py b/invokeai/app/services/board_images.py
index f41526bfa7..7c6995dfc8 100644
--- a/invokeai/app/services/board_images.py
+++ b/invokeai/app/services/board_images.py
@@ -1,18 +1,14 @@
from abc import ABC, abstractmethod
from logging import Logger
-from typing import List, Union, Optional
+from typing import Optional
from invokeai.app.services.board_image_record_storage import BoardImageRecordStorageBase
from invokeai.app.services.board_record_storage import (
BoardRecord,
BoardRecordStorageBase,
)
-from invokeai.app.services.image_record_storage import (
- ImageRecordStorageBase,
- OffsetPaginatedResults,
-)
+from invokeai.app.services.image_record_storage import ImageRecordStorageBase
from invokeai.app.services.models.board_record import BoardDTO
-from invokeai.app.services.models.image_record import ImageDTO, image_record_to_dto
from invokeai.app.services.urls import UrlServiceBase
diff --git a/invokeai/app/services/board_record_storage.py b/invokeai/app/services/board_record_storage.py
index 2fad7b0ab3..593bb3e7b9 100644
--- a/invokeai/app/services/board_record_storage.py
+++ b/invokeai/app/services/board_record_storage.py
@@ -1,15 +1,14 @@
-from abc import ABC, abstractmethod
-from typing import Optional, cast
-import sqlite3
import threading
-from typing import Optional, Union
import uuid
+from abc import ABC, abstractmethod
+from typing import Optional, Union, cast
+
+import sqlite3
from invokeai.app.services.image_record_storage import OffsetPaginatedResults
from invokeai.app.services.models.board_record import (
BoardRecord,
deserialize_board_record,
)
-
from pydantic import BaseModel, Field, Extra
@@ -230,7 +229,7 @@ class SqliteBoardRecordStorage(BoardRecordStorageBase):
# Change the name of a board
if changes.board_name is not None:
self._cursor.execute(
- f"""--sql
+ """--sql
UPDATE boards
SET board_name = ?
WHERE board_id = ?;
@@ -241,7 +240,7 @@ class SqliteBoardRecordStorage(BoardRecordStorageBase):
# Change the cover image of a board
if changes.cover_image_name is not None:
self._cursor.execute(
- f"""--sql
+ """--sql
UPDATE boards
SET cover_image_name = ?
WHERE board_id = ?;
diff --git a/invokeai/app/services/config.py b/invokeai/app/services/config.py
index fec07d90ba..746ca3265c 100644
--- a/invokeai/app/services/config.py
+++ b/invokeai/app/services/config.py
@@ -396,7 +396,7 @@ class InvokeAIAppConfig(InvokeAISettings):
free_gpu_mem : bool = Field(default=False, description="If true, purge model from GPU after each generation.", category='Memory/Performance')
max_cache_size : float = Field(default=6.0, gt=0, description="Maximum memory amount used by model cache for rapid switching", category='Memory/Performance')
max_vram_cache_size : float = Field(default=2.75, ge=0, description="Amount of VRAM reserved for model storage", category='Memory/Performance')
- precision : Literal[tuple(['auto','float16','float32','autocast'])] = Field(default='auto',description='Floating point precision', category='Memory/Performance')
+ precision : Literal['auto', 'float16', 'float32', 'autocast'] = Field(default='auto', description='Floating point precision', category='Memory/Performance')
sequential_guidance : bool = Field(default=False, description="Whether to calculate guidance in serial instead of in parallel, lowering memory requirements", category='Memory/Performance')
xformers_enabled : bool = Field(default=True, description="Enable/disable memory-efficient attention", category='Memory/Performance')
tiled_decode : bool = Field(default=False, description="Whether to enable tiled VAE decode (reduces memory consumption with some performance penalty)", category='Memory/Performance')
@@ -417,8 +417,8 @@ class InvokeAIAppConfig(InvokeAISettings):
log_handlers : List[str] = Field(default=["console"], description='Log handler. Valid options are "console", "file=<path>", "syslog=path|address:host:port", "http=<url>"', category="Logging")
# note - would be better to read the log_format values from logging.py, but this creates circular dependencies issues
- log_format : Literal[tuple(['plain','color','syslog','legacy'])] = Field(default="color", description='Log format. Use "plain" for text-only, "color" for colorized output, "legacy" for 2.3-style logging and "syslog" for syslog-style', category="Logging")
- log_level : Literal[tuple(["debug","info","warning","error","critical"])] = Field(default="info", description="Emit logging messages at this level or higher", category="Logging")
+ log_format : Literal['plain', 'color', 'syslog', 'legacy'] = Field(default="color", description='Log format. Use "plain" for text-only, "color" for colorized output, "legacy" for 2.3-style logging and "syslog" for syslog-style', category="Logging")
+ log_level : Literal["debug", "info", "warning", "error", "critical"] = Field(default="info", description="Emit logging messages at this level or higher", category="Logging")
dev_reload : bool = Field(default=False, description="Automatically reload when Python sources are changed.", category="Development")
@@ -442,7 +442,7 @@ class InvokeAIAppConfig(InvokeAISettings):
if conf is None:
try:
conf = OmegaConf.load(self.root_dir / INIT_FILE)
- except:
+ except Exception:
pass
InvokeAISettings.initconf = conf
@@ -461,7 +461,7 @@ class InvokeAIAppConfig(InvokeAISettings):
"""
if (
cls.singleton_config is None
- or type(cls.singleton_config) != cls
+ or type(cls.singleton_config) is not cls
or (kwargs and cls.singleton_init != kwargs)
):
cls.singleton_config = cls(**kwargs)
diff --git a/invokeai/app/services/graph.py b/invokeai/app/services/graph.py
index c412431b43..51cc8a30ae 100644
--- a/invokeai/app/services/graph.py
+++ b/invokeai/app/services/graph.py
@@ -9,7 +9,8 @@ import networkx as nx
from pydantic import BaseModel, root_validator, validator
from pydantic.fields import Field
-from ..invocations import *
+# Importing * is bad karma but needed here for node detection
+from ..invocations import * # noqa: F401 F403
from ..invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
@@ -445,7 +446,7 @@ class Graph(BaseModel):
node = graph.nodes[node_id]
# Ensure the node type matches the new node
- if type(node) != type(new_node):
+ if type(node) is not type(new_node):
raise TypeError(f"Node {node_path} is type {type(node)} but new node is type {type(new_node)}")
# Ensure the new id is either the same or is not in the graph
@@ -632,7 +633,7 @@ class Graph(BaseModel):
[
t
for input_field in input_fields
- for t in ([input_field] if get_origin(input_field) == None else get_args(input_field))
+ for t in ([input_field] if get_origin(input_field) is None else get_args(input_field))
if t != NoneType
]
) # Get unique types
@@ -923,7 +924,7 @@ class GraphExecutionState(BaseModel):
None,
)
- if next_node_id == None:
+ if next_node_id is None:
return None
# Get all parents of the next node
diff --git a/invokeai/app/services/image_file_storage.py b/invokeai/app/services/image_file_storage.py
index fb8563a3e4..2a8bab9c3f 100644
--- a/invokeai/app/services/image_file_storage.py
+++ b/invokeai/app/services/image_file_storage.py
@@ -179,7 +179,7 @@ class DiskImageFileStorage(ImageFileStorageBase):
return None if image_name not in self.__cache else self.__cache[image_name]
def __set_cache(self, image_name: Path, image: PILImageType):
- if not image_name in self.__cache:
+ if image_name not in self.__cache:
self.__cache[image_name] = image
self.__cache_ids.put(image_name) # TODO: this should refresh position for LRU cache
if len(self.__cache) > self.__max_cache_size:
diff --git a/invokeai/app/services/image_record_storage.py b/invokeai/app/services/image_record_storage.py
index aa71431b7f..8f1b25b84a 100644
--- a/invokeai/app/services/image_record_storage.py
+++ b/invokeai/app/services/image_record_storage.py
@@ -282,7 +282,7 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
self._lock.acquire()
self._cursor.execute(
- f"""--sql
+ """--sql
SELECT images.metadata FROM images
WHERE image_name = ?;
""",
@@ -309,7 +309,7 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
# Change the category of the image
if changes.image_category is not None:
self._cursor.execute(
- f"""--sql
+ """--sql
UPDATE images
SET image_category = ?
WHERE image_name = ?;
@@ -320,7 +320,7 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
# Change the session associated with the image
if changes.session_id is not None:
self._cursor.execute(
- f"""--sql
+ """--sql
UPDATE images
SET session_id = ?
WHERE image_name = ?;
@@ -331,7 +331,7 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
# Change the image's `is_intermediate`` flag
if changes.is_intermediate is not None:
self._cursor.execute(
- f"""--sql
+ """--sql
UPDATE images
SET is_intermediate = ?
WHERE image_name = ?;
@@ -342,7 +342,7 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
# Change the image's `starred`` state
if changes.starred is not None:
self._cursor.execute(
- f"""--sql
+ """--sql
UPDATE images
SET starred = ?
WHERE image_name = ?;
diff --git a/invokeai/app/services/images.py b/invokeai/app/services/images.py
index 2240846dac..e5cb6c3319 100644
--- a/invokeai/app/services/images.py
+++ b/invokeai/app/services/images.py
@@ -1,4 +1,3 @@
-import json
from abc import ABC, abstractmethod
from logging import Logger
from typing import TYPE_CHECKING, Optional
@@ -379,10 +378,10 @@ class ImageService(ImageServiceABC):
self._services.image_files.delete(image_name)
self._services.image_records.delete(image_name)
except ImageRecordDeleteException:
- self._services.logger.error(f"Failed to delete image record")
+ self._services.logger.error("Failed to delete image record")
raise
except ImageFileDeleteException:
- self._services.logger.error(f"Failed to delete image file")
+ self._services.logger.error("Failed to delete image file")
raise
except Exception as e:
self._services.logger.error("Problem deleting image record and file")
@@ -395,10 +394,10 @@ class ImageService(ImageServiceABC):
self._services.image_files.delete(image_name)
self._services.image_records.delete_many(image_names)
except ImageRecordDeleteException:
- self._services.logger.error(f"Failed to delete image records")
+ self._services.logger.error("Failed to delete image records")
raise
except ImageFileDeleteException:
- self._services.logger.error(f"Failed to delete image files")
+ self._services.logger.error("Failed to delete image files")
raise
except Exception as e:
self._services.logger.error("Problem deleting image records and files")
@@ -412,10 +411,10 @@ class ImageService(ImageServiceABC):
self._services.image_files.delete(image_name)
return count
except ImageRecordDeleteException:
- self._services.logger.error(f"Failed to delete image records")
+ self._services.logger.error("Failed to delete image records")
raise
except ImageFileDeleteException:
- self._services.logger.error(f"Failed to delete image files")
+ self._services.logger.error("Failed to delete image files")
raise
except Exception as e:
self._services.logger.error("Problem deleting image records and files")
diff --git a/invokeai/app/services/invocation_services.py b/invokeai/app/services/invocation_services.py
index d7d9aae024..d717087958 100644
--- a/invokeai/app/services/invocation_services.py
+++ b/invokeai/app/services/invocation_services.py
@@ -7,6 +7,7 @@ if TYPE_CHECKING:
from invokeai.app.services.board_images import BoardImagesServiceABC
from invokeai.app.services.boards import BoardServiceABC
from invokeai.app.services.images import ImageServiceABC
+ from invokeai.app.services.invocation_stats import InvocationStatsServiceBase
from invokeai.app.services.model_manager_service import ModelManagerServiceBase
from invokeai.app.services.events import EventServiceBase
from invokeai.app.services.latent_storage import LatentsStorageBase
diff --git a/invokeai/app/services/invocation_stats.py b/invokeai/app/services/invocation_stats.py
index 35c3a5e403..e8557c40f7 100644
--- a/invokeai/app/services/invocation_stats.py
+++ b/invokeai/app/services/invocation_stats.py
@@ -1,7 +1,6 @@
# Copyright 2023 Lincoln D. Stein <lincoln.stein@gmail.com>
-"""Utility to collect execution time and GPU usage stats on invocations in flight"""
+"""Utility to collect execution time and GPU usage stats on invocations in flight
-"""
Usage:
statistics = InvocationStatsService(graph_execution_manager)
diff --git a/invokeai/app/services/latent_storage.py b/invokeai/app/services/latent_storage.py
index 7e781c49ec..7c22ea5ba8 100644
--- a/invokeai/app/services/latent_storage.py
+++ b/invokeai/app/services/latent_storage.py
@@ -60,7 +60,7 @@ class ForwardCacheLatentsStorage(LatentsStorageBase):
return None if name not in self.__cache else self.__cache[name]
def __set_cache(self, name: str, data: torch.Tensor):
- if not name in self.__cache:
+ if name not in self.__cache:
self.__cache[name] = data
self.__cache_ids.put(name)
if self.__cache_ids.qsize() > self.__max_cache_size:
diff --git a/invokeai/app/util/controlnet_utils.py b/invokeai/app/util/controlnet_utils.py
index 6f2c49fec2..1578598687 100644
--- a/invokeai/app/util/controlnet_utils.py
+++ b/invokeai/app/util/controlnet_utils.py
@@ -1,3 +1,4 @@
+from typing import Union
import torch
import numpy as np
import cv2
@@ -5,7 +6,7 @@ from PIL import Image
from diffusers.utils import PIL_INTERPOLATION
from einops import rearrange
-from controlnet_aux.util import HWC3, resize_image
+from controlnet_aux.util import HWC3
###################################################################
# Copy of scripts/lvminthin.py from Mikubill/sd-webui-controlnet
@@ -232,7 +233,8 @@ def np_img_resize(np_img: np.ndarray, resize_mode: str, h: int, w: int, device:
k0 = float(h) / old_h
k1 = float(w) / old_w
- safeint = lambda x: int(np.round(x))
+ def safeint(x: Union[int, float]) -> int:
+ return int(np.round(x))
# if resize_mode == external_code.ResizeMode.OUTER_FIT:
if resize_mode == "fill_resize": # OUTER_FIT
diff --git a/invokeai/app/util/step_callback.py b/invokeai/app/util/step_callback.py
index 3cadfa1c12..f6cccfb4b8 100644
--- a/invokeai/app/util/step_callback.py
+++ b/invokeai/app/util/step_callback.py
@@ -5,7 +5,6 @@ from invokeai.app.models.image import ProgressImage
from ..invocations.baseinvocation import InvocationContext
from ...backend.util.util import image_to_dataURL
from ...backend.stable_diffusion import PipelineIntermediateState
-from invokeai.app.services.config import InvokeAIAppConfig
from ...backend.model_management.models import BaseModelType
diff --git a/invokeai/backend/__init__.py b/invokeai/backend/__init__.py
index a4e6f180ae..2e77d12eca 100644
--- a/invokeai/backend/__init__.py
+++ b/invokeai/backend/__init__.py
@@ -1,5 +1,5 @@
"""
Initialization file for invokeai.backend
"""
-from .model_management import ModelManager, ModelCache, BaseModelType, ModelType, SubModelType, ModelInfo
-from .model_management.models import SilenceWarnings
+from .model_management import ModelManager, ModelCache, BaseModelType, ModelType, SubModelType, ModelInfo # noqa: F401
+from .model_management.models import SilenceWarnings # noqa: F401
diff --git a/invokeai/backend/image_util/__init__.py b/invokeai/backend/image_util/__init__.py
index 9fa635b389..0be5a78a93 100644
--- a/invokeai/backend/image_util/__init__.py
+++ b/invokeai/backend/image_util/__init__.py
@@ -1,14 +1,16 @@
"""
Initialization file for invokeai.backend.image_util methods.
"""
-from .patchmatch import PatchMatch
-from .pngwriter import PngWriter, PromptFormatter, retrieve_metadata, write_metadata
-from .seamless import configure_model_padding
-from .txt2mask import Txt2Mask
-from .util import InitImageResizer, make_grid
+from .patchmatch import PatchMatch # noqa: F401
+from .pngwriter import PngWriter, PromptFormatter, retrieve_metadata, write_metadata # noqa: F401
+from .seamless import configure_model_padding # noqa: F401
+from .txt2mask import Txt2Mask # noqa: F401
+from .util import InitImageResizer, make_grid # noqa: F401
def debug_image(debug_image, debug_text, debug_show=True, debug_result=False, debug_status=False):
+ from PIL import ImageDraw
+
if not debug_status:
return
diff --git a/invokeai/backend/image_util/pngwriter.py b/invokeai/backend/image_util/pngwriter.py
index d3f53d7e72..47f6a44c28 100644
--- a/invokeai/backend/image_util/pngwriter.py
+++ b/invokeai/backend/image_util/pngwriter.py
@@ -26,7 +26,7 @@ class PngWriter:
dirlist = sorted(os.listdir(self.outdir), reverse=True)
# find the first filename that matches our pattern or return 000000.0.png
existing_name = next(
- (f for f in dirlist if re.match("^(\d+)\..*\.png", f)),
+ (f for f in dirlist if re.match(r"^(\d+)\..*\.png", f)),
"0000000.0.png",
)
basecount = int(existing_name.split(".", 1)[0]) + 1
@@ -98,11 +98,11 @@ class PromptFormatter:
# to do: put model name into the t2i object
# switches.append(f'--model{t2i.model_name}')
if opt.seamless or t2i.seamless:
- switches.append(f"--seamless")
+ switches.append("--seamless")
if opt.init_img:
switches.append(f"-I{opt.init_img}")
if opt.fit:
- switches.append(f"--fit")
+ switches.append("--fit")
if opt.strength and opt.init_img is not None:
switches.append(f"-f{opt.strength or t2i.strength}")
if opt.gfpgan_strength:
diff --git a/invokeai/backend/install/invokeai_configure.py b/invokeai/backend/install/invokeai_configure.py
index 6996b913c2..d7ecb41e9b 100755
--- a/invokeai/backend/install/invokeai_configure.py
+++ b/invokeai/backend/install/invokeai_configure.py
@@ -52,7 +52,6 @@ from invokeai.frontend.install.widgets import (
SingleSelectColumns,
CenteredButtonPress,
FileBox,
- IntTitleSlider,
set_min_terminal_size,
CyclingForm,
MIN_COLS,
@@ -308,7 +307,7 @@ class editOptsForm(CyclingForm, npyscreen.FormMultiPage):
first_time = not (config.root_path / "invokeai.yaml").exists()
access_token = HfFolder.get_token()
window_width, window_height = get_terminal_size()
- label = """Configure startup settings. You can come back and change these later.
+ label = """Configure startup settings. You can come back and change these later.
Use ctrl-N and ctrl-P to move to the <N>ext and <P>revious fields.
Use cursor arrows to make a checkbox selection, and space to toggle.
"""
diff --git a/invokeai/backend/install/migrate_to_3.py b/invokeai/backend/install/migrate_to_3.py
index 0938ed2199..e53f211647 100644
--- a/invokeai/backend/install/migrate_to_3.py
+++ b/invokeai/backend/install/migrate_to_3.py
@@ -525,7 +525,7 @@ def do_migrate(src_directory: Path, dest_directory: Path):
if version_3: # write into the dest directory
try:
shutil.copy(dest_directory / "configs" / "models.yaml", config_file)
- except:
+ except Exception:
MigrateTo3.initialize_yaml(config_file)
mgr = ModelManager(config_file) # important to initialize BEFORE moving the models directory
(dest_directory / "models").replace(dest_models)
@@ -553,7 +553,7 @@ def main():
parser = argparse.ArgumentParser(
prog="invokeai-migrate3",
description="""
-This will copy and convert the models directory and the configs/models.yaml from the InvokeAI 2.3 format
+This will copy and convert the models directory and the configs/models.yaml from the InvokeAI 2.3 format
'--from-directory' root to the InvokeAI 3.0 '--to-directory' root. These may be abbreviated '--from' and '--to'.a
The old models directory and config file will be renamed 'models.orig' and 'models.yaml.orig' respectively.
diff --git a/invokeai/backend/install/model_install_backend.py b/invokeai/backend/install/model_install_backend.py
index 3a6d879bee..e41783ab09 100644
--- a/invokeai/backend/install/model_install_backend.py
+++ b/invokeai/backend/install/model_install_backend.py
@@ -12,7 +12,6 @@ from typing import Optional, List, Dict, Callable, Union, Set
import requests
from diffusers import DiffusionPipeline
from diffusers import logging as dlogging
-import onnx
import torch
from huggingface_hub import hf_hub_url, HfFolder, HfApi
from omegaconf import OmegaConf
diff --git a/invokeai/backend/model_management/__init__.py b/invokeai/backend/model_management/__init__.py
index 8e083c1045..6376585fe5 100644
--- a/invokeai/backend/model_management/__init__.py
+++ b/invokeai/backend/model_management/__init__.py
@@ -1,10 +1,10 @@
"""
Initialization file for invokeai.backend.model_management
"""
-from .model_manager import ModelManager, ModelInfo, AddModelResult, SchedulerPredictionType
-from .model_cache import ModelCache
-from .lora import ModelPatcher, ONNXModelPatcher
-from .models import (
+from .model_manager import ModelManager, ModelInfo, AddModelResult, SchedulerPredictionType # noqa: F401
+from .model_cache import ModelCache # noqa: F401
+from .lora import ModelPatcher, ONNXModelPatcher # noqa: F401
+from .models import ( # noqa: F401
BaseModelType,
ModelType,
SubModelType,
@@ -12,5 +12,4 @@ from .models import (
ModelNotFoundException,
DuplicateModelException,
)
-from .model_merge import ModelMerger, MergeInterpolationMethod
-from .lora import ModelPatcher
+from .model_merge import ModelMerger, MergeInterpolationMethod # noqa: F401
diff --git a/invokeai/backend/model_management/convert_ckpt_to_diffusers.py b/invokeai/backend/model_management/convert_ckpt_to_diffusers.py
index 5fd3669911..8118e28abb 100644
--- a/invokeai/backend/model_management/convert_ckpt_to_diffusers.py
+++ b/invokeai/backend/model_management/convert_ckpt_to_diffusers.py
@@ -20,11 +20,36 @@
import re
from contextlib import nullcontext
from io import BytesIO
-from typing import Optional, Union
from pathlib import Path
+from typing import Optional, Union
import requests
import torch
+from diffusers.models import (
+ AutoencoderKL,
+ ControlNetModel,
+ PriorTransformer,
+ UNet2DConditionModel,
+)
+from diffusers.pipelines.latent_diffusion.pipeline_latent_diffusion import LDMBertConfig, LDMBertModel
+from diffusers.pipelines.paint_by_example import PaintByExampleImageEncoder
+from diffusers.pipelines.pipeline_utils import DiffusionPipeline
+from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
+from diffusers.pipelines.stable_diffusion.stable_unclip_image_normalizer import StableUnCLIPImageNormalizer
+from diffusers.schedulers import (
+ DDIMScheduler,
+ DDPMScheduler,
+ DPMSolverMultistepScheduler,
+ EulerAncestralDiscreteScheduler,
+ EulerDiscreteScheduler,
+ HeunDiscreteScheduler,
+ LMSDiscreteScheduler,
+ PNDMScheduler,
+ UnCLIPScheduler,
+)
+from diffusers.utils import is_accelerate_available, is_omegaconf_available
+from diffusers.utils.import_utils import BACKENDS_MAPPING
+from picklescan.scanner import scan_file_path
from transformers import (
AutoFeatureExtractor,
BertTokenizerFast,
@@ -37,35 +62,8 @@ from transformers import (
CLIPVisionModelWithProjection,
)
-from diffusers.models import (
- AutoencoderKL,
- ControlNetModel,
- PriorTransformer,
- UNet2DConditionModel,
-)
-from diffusers.schedulers import (
- DDIMScheduler,
- DDPMScheduler,
- DPMSolverMultistepScheduler,
- EulerAncestralDiscreteScheduler,
- EulerDiscreteScheduler,
- HeunDiscreteScheduler,
- LMSDiscreteScheduler,
- PNDMScheduler,
- UnCLIPScheduler,
-)
-from diffusers.utils import is_accelerate_available, is_omegaconf_available, is_safetensors_available
-from diffusers.utils.import_utils import BACKENDS_MAPPING
-from diffusers.pipelines.latent_diffusion.pipeline_latent_diffusion import LDMBertConfig, LDMBertModel
-from diffusers.pipelines.paint_by_example import PaintByExampleImageEncoder
-from diffusers.pipelines.pipeline_utils import DiffusionPipeline
-from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
-from diffusers.pipelines.stable_diffusion.stable_unclip_image_normalizer import StableUnCLIPImageNormalizer
-
-from invokeai.backend.util.logging import InvokeAILogger
from invokeai.app.services.config import InvokeAIAppConfig
-
-from picklescan.scanner import scan_file_path
+from invokeai.backend.util.logging import InvokeAILogger
from .models import BaseModelType, ModelVariantType
try:
@@ -1221,9 +1219,6 @@ def download_from_original_stable_diffusion_ckpt(
raise ValueError(BACKENDS_MAPPING["omegaconf"][1])
if from_safetensors:
- if not is_safetensors_available():
- raise ValueError(BACKENDS_MAPPING["safetensors"][1])
-
from safetensors.torch import load_file as safe_load
checkpoint = safe_load(checkpoint_path, device="cpu")
@@ -1662,9 +1657,6 @@ def download_controlnet_from_original_ckpt(
from omegaconf import OmegaConf
if from_safetensors:
- if not is_safetensors_available():
- raise ValueError(BACKENDS_MAPPING["safetensors"][1])
-
from safetensors import safe_open
checkpoint = {}
@@ -1741,7 +1733,7 @@ def convert_ckpt_to_diffusers(
pipe.save_pretrained(
dump_path,
- safe_serialization=use_safetensors and is_safetensors_available(),
+ safe_serialization=use_safetensors,
)
@@ -1757,7 +1749,4 @@ def convert_controlnet_to_diffusers(
"""
pipe = download_controlnet_from_original_ckpt(checkpoint_path, **kwargs)
- pipe.save_pretrained(
- dump_path,
- safe_serialization=is_safetensors_available(),
- )
+ pipe.save_pretrained(dump_path, safe_serialization=True)
diff --git a/invokeai/backend/model_management/lora.py b/invokeai/backend/model_management/lora.py
index 3da27988dc..d0d8d4226c 100644
--- a/invokeai/backend/model_management/lora.py
+++ b/invokeai/backend/model_management/lora.py
@@ -5,21 +5,16 @@ from contextlib import contextmanager
from typing import Optional, Dict, Tuple, Any, Union, List
from pathlib import Path
-import torch
-from safetensors.torch import load_file
-from torch.utils.hooks import RemovableHandle
-
-from diffusers.models import UNet2DConditionModel
-from transformers import CLIPTextModel
-from onnx import numpy_helper
-from onnxruntime import OrtValue
import numpy as np
-
+import torch
from compel.embeddings_provider import BaseTextualInversionManager
from diffusers.models import UNet2DConditionModel
from safetensors.torch import load_file
from transformers import CLIPTextModel, CLIPTokenizer
+from .models.lora import LoRAModel
+
+
"""
loras = [
(lora_model1, 0.7),
@@ -52,7 +47,7 @@ class ModelPatcher:
module = module.get_submodule(submodule_name)
module_key += "." + submodule_name
submodule_name = key_parts.pop(0)
- except:
+ except Exception:
submodule_name += "_" + key_parts.pop(0)
module = module.get_submodule(submodule_name)
@@ -312,7 +307,8 @@ class TextualInversionManager(BaseTextualInversionManager):
class ONNXModelPatcher:
- from .models.base import IAIOnnxRuntimeModel, OnnxRuntimeModel
+ from .models.base import IAIOnnxRuntimeModel
+ from diffusers import OnnxRuntimeModel
@classmethod
@contextmanager
@@ -341,7 +337,7 @@ class ONNXModelPatcher:
def apply_lora(
cls,
model: IAIOnnxRuntimeModel,
- loras: List[Tuple[LoraModel, float]],
+ loras: List[Tuple[LoRAModel, float]],
prefix: str,
):
from .models.base import IAIOnnxRuntimeModel
diff --git a/invokeai/backend/model_management/model_cache.py b/invokeai/backend/model_management/model_cache.py
index a11e0a8a8f..6f3e5bd6a5 100644
--- a/invokeai/backend/model_management/model_cache.py
+++ b/invokeai/backend/model_management/model_cache.py
@@ -273,7 +273,7 @@ class ModelCache(object):
self.cache.logger.debug(f"Locking {self.key} in {self.cache.execution_device}")
self.cache._print_cuda_stats()
- except:
+ except Exception:
self.cache_entry.unlock()
raise
diff --git a/invokeai/backend/model_management/model_manager.py b/invokeai/backend/model_management/model_manager.py
index adc3aaa661..1b10554e69 100644
--- a/invokeai/backend/model_management/model_manager.py
+++ b/invokeai/backend/model_management/model_manager.py
@@ -419,12 +419,12 @@ class ModelManager(object):
base_model_str, model_type_str, model_name = model_key.split("/", 2)
try:
model_type = ModelType(model_type_str)
- except:
+ except Exception:
raise Exception(f"Unknown model type: {model_type_str}")
try:
base_model = BaseModelType(base_model_str)
- except:
+ except Exception:
raise Exception(f"Unknown base model: {base_model_str}")
return (model_name, base_model, model_type)
@@ -855,7 +855,7 @@ class ModelManager(object):
info.pop("config")
result = self.add_model(model_name, base_model, model_type, model_attributes=info, clobber=True)
- except:
+ except Exception:
# something went wrong, so don't leave dangling diffusers model in directory or it will cause a duplicate model error!
rmtree(new_diffusers_path)
raise
@@ -1042,7 +1042,7 @@ class ModelManager(object):
# Patch in the SD VAE from core so that it is available for use by the UI
try:
self.heuristic_import({str(self.resolve_model_path("core/convert/sd-vae-ft-mse"))})
- except:
+ except Exception:
pass
installer = ModelInstall(
diff --git a/invokeai/backend/model_management/model_probe.py b/invokeai/backend/model_management/model_probe.py
index 3045849065..9f56958366 100644
--- a/invokeai/backend/model_management/model_probe.py
+++ b/invokeai/backend/model_management/model_probe.py
@@ -217,9 +217,9 @@ class ModelProbe(object):
raise "The model {model_name} is potentially infected by malware. Aborting import."
-###################################################3
+# ##################################################3
# Checkpoint probing
-###################################################3
+# ##################################################3
class ProbeBase(object):
def get_base_type(self) -> BaseModelType:
pass
@@ -431,7 +431,7 @@ class PipelineFolderProbe(FolderProbeBase):
return ModelVariantType.Depth
elif in_channels == 4:
return ModelVariantType.Normal
- except:
+ except Exception:
pass
return ModelVariantType.Normal
diff --git a/invokeai/backend/model_management/models/__init__.py b/invokeai/backend/model_management/models/__init__.py
index 931da1b159..2de206257b 100644
--- a/invokeai/backend/model_management/models/__init__.py
+++ b/invokeai/backend/model_management/models/__init__.py
@@ -2,7 +2,7 @@ import inspect
from enum import Enum
from pydantic import BaseModel
from typing import Literal, get_origin
-from .base import (
+from .base import ( # noqa: F401
BaseModelType,
ModelType,
SubModelType,
@@ -118,7 +118,7 @@ def get_model_config_enums():
fields = model_config.__annotations__
try:
field = fields["model_format"]
- except:
+ except Exception:
raise Exception("format field not found")
# model_format: None
diff --git a/invokeai/backend/model_management/models/base.py b/invokeai/backend/model_management/models/base.py
index d335b645c8..ed1c2c6098 100644
--- a/invokeai/backend/model_management/models/base.py
+++ b/invokeai/backend/model_management/models/base.py
@@ -3,27 +3,28 @@ import os
import sys
import typing
import inspect
-from enum import Enum
+import warnings
from abc import ABCMeta, abstractmethod
+from contextlib import suppress
+from enum import Enum
from pathlib import Path
from picklescan.scanner import scan_file_path
+
import torch
import numpy as np
-import safetensors.torch
-from pathlib import Path
-from diffusers import DiffusionPipeline, ConfigMixin, OnnxRuntimeModel
-
-from contextlib import suppress
-from pydantic import BaseModel, Field
-from typing import List, Dict, Optional, Type, Literal, TypeVar, Generic, Callable, Any, Union
-
import onnx
+import safetensors.torch
+from diffusers import DiffusionPipeline, ConfigMixin
from onnx import numpy_helper
from onnxruntime import (
InferenceSession,
SessionOptions,
get_available_providers,
)
+from pydantic import BaseModel, Field
+from typing import List, Dict, Optional, Type, Literal, TypeVar, Generic, Callable, Any, Union
+from diffusers import logging as diffusers_logging
+from transformers import logging as transformers_logging
class DuplicateModelException(Exception):
@@ -171,7 +172,7 @@ class ModelBase(metaclass=ABCMeta):
fields = value.__annotations__
try:
field = fields["model_format"]
- except:
+ except Exception:
raise Exception(f"Invalid config definition - format field not found({cls.__qualname__})")
if isinstance(field, type) and issubclass(field, str) and issubclass(field, Enum):
@@ -244,7 +245,7 @@ class DiffusersModel(ModelBase):
try:
config_data = DiffusionPipeline.load_config(self.model_path)
# config_data = json.loads(os.path.join(self.model_path, "model_index.json"))
- except:
+ except Exception:
raise Exception("Invalid diffusers model! (model_index.json not found or invalid)")
config_data.pop("_ignore_files", None)
@@ -343,7 +344,7 @@ def calc_model_size_by_fs(model_path: str, subfolder: Optional[str] = None, vari
with open(os.path.join(model_path, file), "r") as f:
index_data = json.loads(f.read())
return int(index_data["metadata"]["total_size"])
- except:
+ except Exception:
pass
# calculate files size if there is no index file
@@ -440,7 +441,7 @@ def read_checkpoint_meta(path: Union[str, Path], scan: bool = False):
if str(path).endswith(".safetensors"):
try:
checkpoint = _fast_safetensors_reader(path)
- except:
+ except Exception:
# TODO: create issue for support "meta"?
checkpoint = safetensors.torch.load_file(path, device="cpu")
else:
@@ -452,11 +453,6 @@ def read_checkpoint_meta(path: Union[str, Path], scan: bool = False):
return checkpoint
-import warnings
-from diffusers import logging as diffusers_logging
-from transformers import logging as transformers_logging
-
-
class SilenceWarnings(object):
def __init__(self):
self.transformers_verbosity = transformers_logging.get_verbosity()
@@ -639,7 +635,7 @@ class IAIOnnxRuntimeModel:
raise Exception("You should call create_session before running model")
inputs = {k: np.array(v) for k, v in kwargs.items()}
- output_names = self.session.get_outputs()
+ # output_names = self.session.get_outputs()
# for k in inputs:
# self.io_binding.bind_cpu_input(k, inputs[k])
# for name in output_names:
diff --git a/invokeai/backend/model_management/models/controlnet.py b/invokeai/backend/model_management/models/controlnet.py
index 061be7ae49..ebc01399b5 100644
--- a/invokeai/backend/model_management/models/controlnet.py
+++ b/invokeai/backend/model_management/models/controlnet.py
@@ -43,7 +43,7 @@ class ControlNetModel(ModelBase):
try:
config = EmptyConfigLoader.load_config(self.model_path, config_name="config.json")
# config = json.loads(os.path.join(self.model_path, "config.json"))
- except:
+ except Exception:
raise Exception("Invalid controlnet model! (config.json not found or invalid)")
model_class_name = config.get("_class_name", None)
@@ -53,7 +53,7 @@ class ControlNetModel(ModelBase):
try:
self.model_class = self._hf_definition_to_type(["diffusers", model_class_name])
self.model_size = calc_model_size_by_fs(self.model_path)
- except:
+ except Exception:
raise Exception("Invalid ControlNet model!")
def get_size(self, child_type: Optional[SubModelType] = None):
@@ -78,7 +78,7 @@ class ControlNetModel(ModelBase):
variant=variant,
)
break
- except:
+ except Exception:
pass
if not model:
raise ModelNotFoundException()
diff --git a/invokeai/backend/model_management/models/stable_diffusion.py b/invokeai/backend/model_management/models/stable_diffusion.py
index a112e8bc96..cc34f14b9c 100644
--- a/invokeai/backend/model_management/models/stable_diffusion.py
+++ b/invokeai/backend/model_management/models/stable_diffusion.py
@@ -330,5 +330,5 @@ def _select_ckpt_config(version: BaseModelType, variant: ModelVariantType):
config_path = config_path.relative_to(app_config.root_path)
return str(config_path)
- except:
+ except Exception:
return None
diff --git a/invokeai/backend/model_management/models/stable_diffusion_onnx.py b/invokeai/backend/model_management/models/stable_diffusion_onnx.py
index 03693e2c3e..2780ba4728 100644
--- a/invokeai/backend/model_management/models/stable_diffusion_onnx.py
+++ b/invokeai/backend/model_management/models/stable_diffusion_onnx.py
@@ -1,25 +1,17 @@
-import os
-import json
from enum import Enum
-from pydantic import Field
-from pathlib import Path
-from typing import Literal, Optional, Union
+from typing import Literal
+
+from diffusers import OnnxRuntimeModel
from .base import (
- ModelBase,
ModelConfigBase,
BaseModelType,
ModelType,
- SubModelType,
ModelVariantType,
DiffusersModel,
SchedulerPredictionType,
- SilenceWarnings,
- read_checkpoint_meta,
classproperty,
- OnnxRuntimeModel,
IAIOnnxRuntimeModel,
)
-from invokeai.app.services.config import InvokeAIAppConfig
class StableDiffusionOnnxModelFormat(str, Enum):
diff --git a/invokeai/backend/model_management/models/vae.py b/invokeai/backend/model_management/models/vae.py
index 957a102ffb..f5dc11b27b 100644
--- a/invokeai/backend/model_management/models/vae.py
+++ b/invokeai/backend/model_management/models/vae.py
@@ -5,7 +5,6 @@ from typing import Optional
import safetensors
import torch
-from diffusers.utils import is_safetensors_available
from omegaconf import OmegaConf
from invokeai.app.services.config import InvokeAIAppConfig
@@ -44,14 +43,14 @@ class VaeModel(ModelBase):
try:
config = EmptyConfigLoader.load_config(self.model_path, config_name="config.json")
# config = json.loads(os.path.join(self.model_path, "config.json"))
- except:
+ except Exception:
raise Exception("Invalid vae model! (config.json not found or invalid)")
try:
vae_class_name = config.get("_class_name", "AutoencoderKL")
self.vae_class = self._hf_definition_to_type(["diffusers", vae_class_name])
self.model_size = calc_model_size_by_fs(self.model_path)
- except:
+ except Exception:
raise Exception("Invalid vae model! (Unkown vae type)")
def get_size(self, child_type: Optional[SubModelType] = None):
@@ -175,5 +174,5 @@ def _convert_vae_ckpt_and_cache(
vae_config=config,
image_size=image_size,
)
- vae_model.save_pretrained(output_path, safe_serialization=is_safetensors_available())
+ vae_model.save_pretrained(output_path, safe_serialization=True)
return output_path
diff --git a/invokeai/backend/stable_diffusion/__init__.py b/invokeai/backend/stable_diffusion/__init__.py
index 21273c6201..a958750802 100644
--- a/invokeai/backend/stable_diffusion/__init__.py
+++ b/invokeai/backend/stable_diffusion/__init__.py
@@ -1,11 +1,15 @@
"""
Initialization file for the invokeai.backend.stable_diffusion package
"""
-from .diffusers_pipeline import (
+from .diffusers_pipeline import ( # noqa: F401
ConditioningData,
PipelineIntermediateState,
StableDiffusionGeneratorPipeline,
)
-from .diffusion import InvokeAIDiffuserComponent
-from .diffusion.cross_attention_map_saving import AttentionMapSaver
-from .diffusion.shared_invokeai_diffusion import PostprocessingSettings, BasicConditioningInfo, SDXLConditioningInfo
+from .diffusion import InvokeAIDiffuserComponent # noqa: F401
+from .diffusion.cross_attention_map_saving import AttentionMapSaver # noqa: F401
+from .diffusion.shared_invokeai_diffusion import ( # noqa: F401
+ PostprocessingSettings,
+ BasicConditioningInfo,
+ SDXLConditioningInfo,
+)
diff --git a/invokeai/backend/stable_diffusion/diffusers_pipeline.py b/invokeai/backend/stable_diffusion/diffusers_pipeline.py
index aa809bc3ec..0180830b76 100644
--- a/invokeai/backend/stable_diffusion/diffusers_pipeline.py
+++ b/invokeai/backend/stable_diffusion/diffusers_pipeline.py
@@ -2,10 +2,8 @@ from __future__ import annotations
import dataclasses
import inspect
-import math
-import secrets
from dataclasses import dataclass, field
-from typing import Any, Callable, Generic, List, Optional, Type, Union
+from typing import Any, Callable, List, Optional, Union
import PIL.Image
import einops
diff --git a/invokeai/backend/stable_diffusion/diffusion/__init__.py b/invokeai/backend/stable_diffusion/diffusion/__init__.py
index 76f338aeaf..2bcc595889 100644
--- a/invokeai/backend/stable_diffusion/diffusion/__init__.py
+++ b/invokeai/backend/stable_diffusion/diffusion/__init__.py
@@ -1,9 +1,9 @@
"""
Initialization file for invokeai.models.diffusion
"""
-from .cross_attention_control import InvokeAICrossAttentionMixin
-from .cross_attention_map_saving import AttentionMapSaver
-from .shared_invokeai_diffusion import (
+from .cross_attention_control import InvokeAICrossAttentionMixin # noqa: F401
+from .cross_attention_map_saving import AttentionMapSaver # noqa: F401
+from .shared_invokeai_diffusion import ( # noqa: F401
InvokeAIDiffuserComponent,
PostprocessingSettings,
BasicConditioningInfo,
diff --git a/invokeai/backend/stable_diffusion/diffusion/cross_attention_control.py b/invokeai/backend/stable_diffusion/diffusion/cross_attention_control.py
index 38763ebbee..35d4800859 100644
--- a/invokeai/backend/stable_diffusion/diffusion/cross_attention_control.py
+++ b/invokeai/backend/stable_diffusion/diffusion/cross_attention_control.py
@@ -4,6 +4,7 @@
import enum
import math
+from dataclasses import dataclass, field
from typing import Callable, Optional
import diffusers
@@ -12,6 +13,11 @@ import torch
from compel.cross_attention_control import Arguments
from diffusers.models.unet_2d_condition import UNet2DConditionModel
from diffusers.models.attention_processor import AttentionProcessor
+from diffusers.models.attention_processor import (
+ Attention,
+ AttnProcessor,
+ SlicedAttnProcessor,
+)
from torch import nn
import invokeai.backend.util.logging as logger
@@ -522,14 +528,6 @@ class AttnProcessor:
return hidden_states
"""
-from dataclasses import dataclass, field
-
-import torch
-from diffusers.models.attention_processor import (
- Attention,
- AttnProcessor,
- SlicedAttnProcessor,
-)
@dataclass
diff --git a/invokeai/backend/stable_diffusion/diffusion/cross_attention_map_saving.py b/invokeai/backend/stable_diffusion/diffusion/cross_attention_map_saving.py
index b0174a455e..abef979b1c 100644
--- a/invokeai/backend/stable_diffusion/diffusion/cross_attention_map_saving.py
+++ b/invokeai/backend/stable_diffusion/diffusion/cross_attention_map_saving.py
@@ -5,8 +5,6 @@ import torch
from torchvision.transforms.functional import InterpolationMode
from torchvision.transforms.functional import resize as tv_resize
-from .cross_attention_control import CrossAttentionType, get_cross_attention_modules
-
class AttentionMapSaver:
def __init__(self, token_ids: range, latents_shape: torch.Size):
diff --git a/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py b/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py
index f16855e775..f05adafca2 100644
--- a/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py
+++ b/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py
@@ -3,15 +3,12 @@ from __future__ import annotations
from contextlib import contextmanager
from dataclasses import dataclass
import math
-from typing import Any, Callable, Dict, Optional, Union, List
+from typing import Any, Callable, Optional, Union
-import numpy as np
import torch
from diffusers import UNet2DConditionModel
-from diffusers.models.attention_processor import AttentionProcessor
from typing_extensions import TypeAlias
-import invokeai.backend.util.logging as logger
from invokeai.app.services.config import InvokeAIAppConfig
from .cross_attention_control import (
@@ -579,7 +576,7 @@ class InvokeAIDiffuserComponent:
latents.to(device="cpu")
if (
- h_symmetry_time_pct != None
+ h_symmetry_time_pct is not None
and self.last_percent_through < h_symmetry_time_pct
and percent_through >= h_symmetry_time_pct
):
@@ -595,7 +592,7 @@ class InvokeAIDiffuserComponent:
)
if (
- v_symmetry_time_pct != None
+ v_symmetry_time_pct is not None
and self.last_percent_through < v_symmetry_time_pct
and percent_through >= v_symmetry_time_pct
):
diff --git a/invokeai/backend/stable_diffusion/image_degradation/__init__.py b/invokeai/backend/stable_diffusion/image_degradation/__init__.py
index c6b3b62ea8..589e266c02 100644
--- a/invokeai/backend/stable_diffusion/image_degradation/__init__.py
+++ b/invokeai/backend/stable_diffusion/image_degradation/__init__.py
@@ -1,6 +1,6 @@
-from ldm.modules.image_degradation.bsrgan import (
+from ldm.modules.image_degradation.bsrgan import ( # noqa: F401
degradation_bsrgan_variant as degradation_fn_bsr,
)
-from ldm.modules.image_degradation.bsrgan_light import (
+from ldm.modules.image_degradation.bsrgan_light import ( # noqa: F401
degradation_bsrgan_variant as degradation_fn_bsr_light,
)
diff --git a/invokeai/backend/stable_diffusion/image_degradation/bsrgan.py b/invokeai/backend/stable_diffusion/image_degradation/bsrgan.py
index 493c8be781..e4d614207b 100644
--- a/invokeai/backend/stable_diffusion/image_degradation/bsrgan.py
+++ b/invokeai/backend/stable_diffusion/image_degradation/bsrgan.py
@@ -573,14 +573,15 @@ def degradation_bsrgan_variant(image, sf=4, isp_model=None):
hq: corresponding high-quality patch, size: (lq_patchsizexsf)X(lq_patchsizexsf)XC, range: [0, 1]
"""
image = util.uint2single(image)
- isp_prob, jpeg_prob, scale2_prob = 0.25, 0.9, 0.25
- sf_ori = sf
+ jpeg_prob, scale2_prob = 0.9, 0.25
+ # isp_prob = 0.25 # uncomment with `if i== 6` block below
+ # sf_ori = sf # uncomment with `if i== 6` block below
h1, w1 = image.shape[:2]
image = image.copy()[: w1 - w1 % sf, : h1 - h1 % sf, ...] # mod crop
h, w = image.shape[:2]
- hq = image.copy()
+ # hq = image.copy() # uncomment with `if i== 6` block below
if sf == 4 and random.random() < scale2_prob: # downsample1
if np.random.rand() < 0.5:
@@ -777,7 +778,7 @@ if __name__ == "__main__":
img_lq_bicubic = albumentations.SmallestMaxSize(max_size=h, interpolation=cv2.INTER_CUBIC)(image=img)["image"]
print(img_lq.shape)
print("bicubic", img_lq_bicubic.shape)
- print(img_hq.shape)
+ # print(img_hq.shape)
lq_nearest = cv2.resize(
util.single2uint(img_lq),
(int(sf * img_lq.shape[1]), int(sf * img_lq.shape[0])),
@@ -788,5 +789,6 @@ if __name__ == "__main__":
(int(sf * img_lq.shape[1]), int(sf * img_lq.shape[0])),
interpolation=0,
)
- img_concat = np.concatenate([lq_bicubic_nearest, lq_nearest, util.single2uint(img_hq)], axis=1)
+ # img_concat = np.concatenate([lq_bicubic_nearest, lq_nearest, util.single2uint(img_hq)], axis=1)
+ img_concat = np.concatenate([lq_bicubic_nearest, lq_nearest], axis=1)
util.imsave(img_concat, str(i) + ".png")
diff --git a/invokeai/backend/stable_diffusion/image_degradation/bsrgan_light.py b/invokeai/backend/stable_diffusion/image_degradation/bsrgan_light.py
index d0e0abadbc..cd74adc519 100644
--- a/invokeai/backend/stable_diffusion/image_degradation/bsrgan_light.py
+++ b/invokeai/backend/stable_diffusion/image_degradation/bsrgan_light.py
@@ -577,14 +577,15 @@ def degradation_bsrgan_variant(image, sf=4, isp_model=None):
hq: corresponding high-quality patch, size: (lq_patchsizexsf)X(lq_patchsizexsf)XC, range: [0, 1]
"""
image = util.uint2single(image)
- isp_prob, jpeg_prob, scale2_prob = 0.25, 0.9, 0.25
- sf_ori = sf
+ jpeg_prob, scale2_prob = 0.9, 0.25
+ # isp_prob = 0.25 # uncomment with `if i== 6` block below
+ # sf_ori = sf # uncomment with `if i== 6` block below
h1, w1 = image.shape[:2]
image = image.copy()[: w1 - w1 % sf, : h1 - h1 % sf, ...] # mod crop
h, w = image.shape[:2]
- hq = image.copy()
+ # hq = image.copy() # uncomment with `if i== 6` block below
if sf == 4 and random.random() < scale2_prob: # downsample1
if np.random.rand() < 0.5:
diff --git a/invokeai/backend/stable_diffusion/image_degradation/utils_image.py b/invokeai/backend/stable_diffusion/image_degradation/utils_image.py
index fb71f85e5a..2a0773c3ed 100644
--- a/invokeai/backend/stable_diffusion/image_degradation/utils_image.py
+++ b/invokeai/backend/stable_diffusion/image_degradation/utils_image.py
@@ -8,8 +8,6 @@ import numpy as np
import torch
from torchvision.utils import make_grid
-# import matplotlib.pyplot as plt # TODO: check with Dominik, also bsrgan.py vs bsrgan_light.py
-
import invokeai.backend.util.logging as logger
os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE"
@@ -50,6 +48,8 @@ def get_timestamp():
def imshow(x, title=None, cbar=False, figsize=None):
+ import matplotlib.pyplot as plt
+
plt.figure(figsize=figsize)
plt.imshow(np.squeeze(x), interpolation="nearest", cmap="gray")
if title:
@@ -60,6 +60,8 @@ def imshow(x, title=None, cbar=False, figsize=None):
def surf(Z, cmap="rainbow", figsize=None):
+ import matplotlib.pyplot as plt
+
plt.figure(figsize=figsize)
ax3 = plt.axes(projection="3d")
diff --git a/invokeai/backend/stable_diffusion/schedulers/__init__.py b/invokeai/backend/stable_diffusion/schedulers/__init__.py
index 29a96eb3a5..a4e9dbf9da 100644
--- a/invokeai/backend/stable_diffusion/schedulers/__init__.py
+++ b/invokeai/backend/stable_diffusion/schedulers/__init__.py
@@ -1 +1 @@
-from .schedulers import SCHEDULER_MAP
+from .schedulers import SCHEDULER_MAP # noqa: F401
diff --git a/invokeai/backend/training/__init__.py b/invokeai/backend/training/__init__.py
index a85842dc72..ed3ceb90ec 100644
--- a/invokeai/backend/training/__init__.py
+++ b/invokeai/backend/training/__init__.py
@@ -1,4 +1,4 @@
"""
Initialization file for invokeai.backend.training
"""
-from .textual_inversion_training import do_textual_inversion_training, parse_args
+from .textual_inversion_training import do_textual_inversion_training, parse_args # noqa: F401
diff --git a/invokeai/backend/util/__init__.py b/invokeai/backend/util/__init__.py
index 2e69af5382..30bb0efc15 100644
--- a/invokeai/backend/util/__init__.py
+++ b/invokeai/backend/util/__init__.py
@@ -1,7 +1,7 @@
"""
Initialization file for invokeai.backend.util
"""
-from .devices import (
+from .devices import ( # noqa: F401
CPU_DEVICE,
CUDA_DEVICE,
MPS_DEVICE,
@@ -10,5 +10,5 @@ from .devices import (
normalize_device,
torch_dtype,
)
-from .log import write_log
-from .util import ask_user, download_with_resume, instantiate_from_config, url_attachment_name, Chdir
+from .log import write_log # noqa: F401
+from .util import ask_user, download_with_resume, instantiate_from_config, url_attachment_name, Chdir # noqa: F401
diff --git a/invokeai/backend/util/hotfixes.py b/invokeai/backend/util/hotfixes.py
index 89b3da5a37..3d7f278f86 100644
--- a/invokeai/backend/util/hotfixes.py
+++ b/invokeai/backend/util/hotfixes.py
@@ -25,10 +25,15 @@ from diffusers.models.unet_2d_condition import UNet2DConditionModel
import diffusers
from diffusers.models.controlnet import ControlNetConditioningEmbedding, ControlNetOutput, zero_module
+from invokeai.backend.util.logging import InvokeAILogger
+
# TODO: create PR to diffusers
# Modified ControlNetModel with encoder_attention_mask argument added
+logger = InvokeAILogger.getLogger(__name__)
+
+
class ControlNetModel(ModelMixin, ConfigMixin, FromOriginalControlnetMixin):
"""
A ControlNet model.
@@ -111,7 +116,7 @@ class ControlNetModel(ModelMixin, ConfigMixin, FromOriginalControlnetMixin):
"DownBlock2D",
),
only_cross_attention: Union[bool, Tuple[bool]] = False,
- block_out_channels: Tuple[int] = (320, 640, 1280, 1280),
+ block_out_channels: Tuple[int, ...] = (320, 640, 1280, 1280),
layers_per_block: int = 2,
downsample_padding: int = 1,
mid_block_scale_factor: float = 1,
diff --git a/invokeai/backend/util/log.py b/invokeai/backend/util/log.py
index 4643f61a6b..3919d456b9 100644
--- a/invokeai/backend/util/log.py
+++ b/invokeai/backend/util/log.py
@@ -27,8 +27,8 @@ def write_log_message(results, output_cntr):
log_lines = [f"{path}: {prompt}\n" for path, prompt in results]
if len(log_lines) > 1:
subcntr = 1
- for l in log_lines:
- print(f"[{output_cntr}.{subcntr}] {l}", end="")
+ for ll in log_lines:
+ print(f"[{output_cntr}.{subcntr}] {ll}", end="")
subcntr += 1
else:
print(f"[{output_cntr}] {log_lines[0]}", end="")
diff --git a/invokeai/backend/util/logging.py b/invokeai/backend/util/logging.py
index 3a8d721aa5..82706d8181 100644
--- a/invokeai/backend/util/logging.py
+++ b/invokeai/backend/util/logging.py
@@ -182,13 +182,13 @@ import urllib.parse
from abc import abstractmethod
from pathlib import Path
-from invokeai.app.services.config import InvokeAIAppConfig, get_invokeai_config
+from invokeai.app.services.config import InvokeAIAppConfig
try:
import syslog
SYSLOG_AVAILABLE = True
-except:
+except ImportError:
SYSLOG_AVAILABLE = False
@@ -417,7 +417,7 @@ class InvokeAILogger(object):
syslog_args["socktype"] = _SOCK_MAP[arg_value[0]]
else:
syslog_args["address"] = arg_name
- except:
+ except Exception:
raise ValueError(f"{args} is not a value argument list for syslog logging")
return logging.handlers.SysLogHandler(**syslog_args)
diff --git a/invokeai/backend/util/mps_fixes.py b/invokeai/backend/util/mps_fixes.py
index 409eff1c8b..8a4e6baab5 100644
--- a/invokeai/backend/util/mps_fixes.py
+++ b/invokeai/backend/util/mps_fixes.py
@@ -191,7 +191,7 @@ class ChunkedSlicedAttnProcessor:
assert value.shape[0] == 1
assert hidden_states.shape[0] == 1
- dtype = query.dtype
+ # dtype = query.dtype
if attn.upcast_attention:
query = query.float()
key = key.float()
diff --git a/invokeai/backend/util/util.py b/invokeai/backend/util/util.py
index f3c182c063..7ef9c72fb0 100644
--- a/invokeai/backend/util/util.py
+++ b/invokeai/backend/util/util.py
@@ -84,7 +84,7 @@ def count_params(model, verbose=False):
def instantiate_from_config(config, **kwargs):
- if not "target" in config:
+ if "target" not in config:
if config == "__is_first_stage__":
return None
elif config == "__is_unconditional__":
@@ -234,16 +234,17 @@ def rand_perlin_2d(shape, res, device, fade=lambda t: 6 * t**5 - 15 * t**4 + 10
.repeat_interleave(d[1], 1)
)
- dot = lambda grad, shift: (
- torch.stack(
- (
- grid[: shape[0], : shape[1], 0] + shift[0],
- grid[: shape[0], : shape[1], 1] + shift[1],
- ),
- dim=-1,
- )
- * grad[: shape[0], : shape[1]]
- ).sum(dim=-1)
+ def dot(grad, shift):
+ return (
+ torch.stack(
+ (
+ grid[: shape[0], : shape[1], 0] + shift[0],
+ grid[: shape[0], : shape[1], 1] + shift[1],
+ ),
+ dim=-1,
+ )
+ * grad[: shape[0], : shape[1]]
+ ).sum(dim=-1)
n00 = dot(tile_grads([0, -1], [0, -1]), [0, 0]).to(device)
n10 = dot(tile_grads([1, None], [0, -1]), [-1, 0]).to(device)
@@ -287,7 +288,7 @@ def download_with_resume(url: str, dest: Path, access_token: str = None) -> Path
if dest.is_dir():
try:
file_name = re.search('filename="(.+)"', resp.headers.get("Content-Disposition")).group(1)
- except:
+ except AttributeError:
file_name = os.path.basename(url)
dest = dest / file_name
else:
@@ -342,7 +343,7 @@ def url_attachment_name(url: str) -> dict:
resp = requests.get(url, stream=True)
match = re.search('filename="(.+)"', resp.headers.get("Content-Disposition"))
return match.group(1)
- except:
+ except Exception:
return None
diff --git a/invokeai/frontend/CLI/__init__.py b/invokeai/frontend/CLI/__init__.py
index 7e48534cb9..f8864bbe66 100644
--- a/invokeai/frontend/CLI/__init__.py
+++ b/invokeai/frontend/CLI/__init__.py
@@ -1,4 +1,4 @@
"""
Initialization file for invokeai.frontend.CLI
"""
-from .CLI import main as invokeai_command_line_interface
+from .CLI import main as invokeai_command_line_interface # noqa: F401
diff --git a/invokeai/frontend/install/invokeai_configure.py b/invokeai/frontend/install/invokeai_configure.py
index 157d57fafc..d200d78555 100644
--- a/invokeai/frontend/install/invokeai_configure.py
+++ b/invokeai/frontend/install/invokeai_configure.py
@@ -1,4 +1,4 @@
"""
Wrapper for invokeai.backend.configure.invokeai_configure
"""
-from ...backend.install.invokeai_configure import main as invokeai_configure
+from ...backend.install.invokeai_configure import main as invokeai_configure # noqa: F401
diff --git a/invokeai/frontend/install/invokeai_update.py b/invokeai/frontend/install/invokeai_update.py
index 3fe6ff1574..3fe9bb6f97 100644
--- a/invokeai/frontend/install/invokeai_update.py
+++ b/invokeai/frontend/install/invokeai_update.py
@@ -80,7 +80,7 @@ def welcome(versions: dict):
def get_extras():
extras = ""
try:
- dist = pkg_resources.get_distribution("xformers")
+ _ = pkg_resources.get_distribution("xformers")
extras = "[xformers]"
except pkg_resources.DistributionNotFound:
pass
@@ -90,7 +90,7 @@ def get_extras():
def main():
versions = get_versions()
if invokeai_is_running():
- print(f":exclamation: [bold red]Please terminate all running instances of InvokeAI before updating.[/red bold]")
+ print(":exclamation: [bold red]Please terminate all running instances of InvokeAI before updating.[/red bold]")
input("Press any key to continue...")
return
@@ -122,9 +122,9 @@ def main():
print("")
print("")
if os.system(cmd) == 0:
- print(f":heavy_check_mark: Upgrade successful")
+ print(":heavy_check_mark: Upgrade successful")
else:
- print(f":exclamation: [bold red]Upgrade failed[/red bold]")
+ print(":exclamation: [bold red]Upgrade failed[/red bold]")
if __name__ == "__main__":
diff --git a/invokeai/frontend/install/model_install.py b/invokeai/frontend/install/model_install.py
index ade3043d96..6e4440abef 100644
--- a/invokeai/frontend/install/model_install.py
+++ b/invokeai/frontend/install/model_install.py
@@ -251,7 +251,7 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
) -> dict[str, npyscreen.widget]:
"""Generic code to create model selection widgets"""
widgets = dict()
- model_list = [x for x in self.all_models if self.all_models[x].model_type == model_type and not x in exclude]
+ model_list = [x for x in self.all_models if self.all_models[x].model_type == model_type and x not in exclude]
model_labels = [self.model_labels[x] for x in model_list]
show_recommended = len(self.installed_models) == 0
@@ -357,14 +357,14 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
try:
v.hidden = True
v.editable = False
- except:
+ except Exception:
pass
for k, v in widgets[selected_tab].items():
try:
v.hidden = False
if not isinstance(v, (npyscreen.FixedText, npyscreen.TitleFixedText, CenteredTitleText)):
v.editable = True
- except:
+ except Exception:
pass
self.__class__.current_tab = selected_tab # for persistence
self.display()
@@ -541,7 +541,7 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
self.ti_models,
]
for section in ui_sections:
- if not "models_selected" in section:
+ if "models_selected" not in section:
continue
selected = set([section["models"][x] for x in section["models_selected"].value])
models_to_install = [x for x in selected if not self.all_models[x].installed]
@@ -637,7 +637,7 @@ def _ask_user_for_pt_tui(model_path: Path, tui_conn: Connection) -> SchedulerPre
return None
else:
return response
- except:
+ except Exception:
return None
@@ -673,8 +673,7 @@ def process_and_execute(
def select_and_download_models(opt: Namespace):
precision = "float32" if opt.full_precision else choose_precision(torch.device(choose_torch_device()))
config.precision = precision
- helper = lambda x: ask_user_for_prediction_type(x)
- installer = ModelInstall(config, prediction_type_helper=helper)
+ installer = ModelInstall(config, prediction_type_helper=ask_user_for_prediction_type)
if opt.list_models:
installer.list_models(opt.list_models)
elif opt.add or opt.delete:
diff --git a/invokeai/frontend/install/widgets.py b/invokeai/frontend/install/widgets.py
index 156503f0b8..79b6280990 100644
--- a/invokeai/frontend/install/widgets.py
+++ b/invokeai/frontend/install/widgets.py
@@ -102,8 +102,8 @@ def set_min_terminal_size(min_cols: int, min_lines: int) -> bool:
class IntSlider(npyscreen.Slider):
def translate_value(self):
stri = "%2d / %2d" % (self.value, self.out_of)
- l = (len(str(self.out_of))) * 2 + 4
- stri = stri.rjust(l)
+ length = (len(str(self.out_of))) * 2 + 4
+ stri = stri.rjust(length)
return stri
@@ -167,8 +167,8 @@ class FloatSlider(npyscreen.Slider):
# this is supposed to adjust display precision, but doesn't
def translate_value(self):
stri = "%3.2f / %3.2f" % (self.value, self.out_of)
- l = (len(str(self.out_of))) * 2 + 4
- stri = stri.rjust(l)
+ length = (len(str(self.out_of))) * 2 + 4
+ stri = stri.rjust(length)
return stri
diff --git a/invokeai/frontend/legacy_launch_invokeai.py b/invokeai/frontend/legacy_launch_invokeai.py
index e4509db6e5..e1e7dc26ab 100644
--- a/invokeai/frontend/legacy_launch_invokeai.py
+++ b/invokeai/frontend/legacy_launch_invokeai.py
@@ -1,4 +1,3 @@
-import os
import sys
import argparse
diff --git a/invokeai/frontend/merge/__init__.py b/invokeai/frontend/merge/__init__.py
index 3a2e4474a5..a18da9c0d4 100644
--- a/invokeai/frontend/merge/__init__.py
+++ b/invokeai/frontend/merge/__init__.py
@@ -1,4 +1,4 @@
"""
Initialization file for invokeai.frontend.merge
"""
-from .merge_diffusers import main as invokeai_merge_diffusers
+from .merge_diffusers import main as invokeai_merge_diffusers # noqa: F401
diff --git a/invokeai/frontend/merge/merge_diffusers.py b/invokeai/frontend/merge/merge_diffusers.py
index f2e211a1b4..ada8eed644 100644
--- a/invokeai/frontend/merge/merge_diffusers.py
+++ b/invokeai/frontend/merge/merge_diffusers.py
@@ -9,19 +9,15 @@ import curses
import sys
from argparse import Namespace
from pathlib import Path
-from typing import List, Union
+from typing import List, Optional
import npyscreen
-from diffusers import DiffusionPipeline
-from diffusers import logging as dlogging
from npyscreen import widget
-from omegaconf import OmegaConf
import invokeai.backend.util.logging as logger
from invokeai.app.services.config import InvokeAIAppConfig
from invokeai.backend.model_management import (
ModelMerger,
- MergeInterpolationMethod,
ModelManager,
ModelType,
BaseModelType,
@@ -318,7 +314,7 @@ class mergeModelsForm(npyscreen.FormMultiPageAction):
else:
return True
- def get_model_names(self, base_model: BaseModelType = None) -> List[str]:
+ def get_model_names(self, base_model: Optional[BaseModelType] = None) -> List[str]:
model_names = [
info["model_name"]
for info in self.model_manager.list_models(model_type=ModelType.Main, base_model=base_model)
diff --git a/invokeai/frontend/training/__init__.py b/invokeai/frontend/training/__init__.py
index db5d69fc7a..d4eff2f7fd 100644
--- a/invokeai/frontend/training/__init__.py
+++ b/invokeai/frontend/training/__init__.py
@@ -1,4 +1,4 @@
"""
Initialization file for invokeai.frontend.training
"""
-from .textual_inversion import main as invokeai_textual_inversion
+from .textual_inversion import main as invokeai_textual_inversion # noqa: F401
diff --git a/invokeai/frontend/training/textual_inversion.py b/invokeai/frontend/training/textual_inversion.py
index 25debf4bdc..12f4db8e7b 100755
--- a/invokeai/frontend/training/textual_inversion.py
+++ b/invokeai/frontend/training/textual_inversion.py
@@ -59,7 +59,7 @@ class textualInversionForm(npyscreen.FormMultiPageAction):
try:
default = self.model_names.index(saved_args["model"])
- except:
+ except Exception:
pass
self.add_widget_intelligent(
@@ -377,7 +377,7 @@ def previous_args() -> dict:
try:
conf = OmegaConf.load(conf_file)
conf["placeholder_token"] = conf["placeholder_token"].strip("<>")
- except:
+ except Exception:
conf = None
return conf
diff --git a/invokeai/frontend/web/src/features/system/store/systemSlice.ts b/invokeai/frontend/web/src/features/system/store/systemSlice.ts
index b22a493868..d789df49a4 100644
--- a/invokeai/frontend/web/src/features/system/store/systemSlice.ts
+++ b/invokeai/frontend/web/src/features/system/store/systemSlice.ts
@@ -4,7 +4,7 @@ import { InvokeLogLevel } from 'app/logging/logger';
import { userInvoked } from 'app/store/actions';
import { nodeTemplatesBuilt } from 'features/nodes/store/nodesSlice';
import { t } from 'i18next';
-import { startCase } from 'lodash-es';
+import { startCase, upperFirst } from 'lodash-es';
import { LogLevelName } from 'roarr';
import {
isAnySessionRejected,
@@ -26,6 +26,7 @@ import {
import { ProgressImage } from 'services/events/types';
import { makeToast } from '../util/makeToast';
import { LANGUAGES } from './constants';
+import { zPydanticValidationError } from './zodSchemas';
export type CancelStrategy = 'immediate' | 'scheduled';
@@ -361,9 +362,24 @@ export const systemSlice = createSlice({
state.progressImage = null;
let errorDescription = undefined;
+ const duration = 5000;
if (action.payload?.status === 422) {
- errorDescription = 'Validation Error';
+ const result = zPydanticValidationError.safeParse(action.payload);
+ if (result.success) {
+ result.data.error.detail.map((e) => {
+ state.toastQueue.push(
+ makeToast({
+ title: upperFirst(e.msg),
+ status: 'error',
+ description: `Path:
+ ${e.loc.slice(3).join('.')}`,
+ duration,
+ })
+ );
+ });
+ return;
+ }
} else if (action.payload?.error) {
errorDescription = action.payload?.error as string;
}
@@ -373,6 +389,7 @@ export const systemSlice = createSlice({
title: t('toast.serverError'),
status: 'error',
description: errorDescription,
+ duration,
})
);
});
diff --git a/invokeai/frontend/web/src/features/system/store/zodSchemas.ts b/invokeai/frontend/web/src/features/system/store/zodSchemas.ts
new file mode 100644
index 0000000000..3a3b950019
--- /dev/null
+++ b/invokeai/frontend/web/src/features/system/store/zodSchemas.ts
@@ -0,0 +1,14 @@
+import { z } from 'zod';
+
+export const zPydanticValidationError = z.object({
+ status: z.literal(422),
+ error: z.object({
+ detail: z.array(
+ z.object({
+ loc: z.array(z.string()),
+ msg: z.string(),
+ type: z.string(),
+ })
+ ),
+ }),
+});
diff --git a/invokeai/version/__init__.py b/invokeai/version/__init__.py
index 21dfcad3ca..90cca7c27f 100644
--- a/invokeai/version/__init__.py
+++ b/invokeai/version/__init__.py
@@ -1,7 +1,7 @@
"""
initialization file for invokeai
"""
-from .invokeai_version import __version__
+from .invokeai_version import __version__ # noqa: F401
__app_id__ = "invoke-ai/InvokeAI"
__app_name__ = "InvokeAI"
diff --git a/notebooks/notebook_helpers.py b/notebooks/notebook_helpers.py
index b87f18ba18..488b3660f8 100644
--- a/notebooks/notebook_helpers.py
+++ b/notebooks/notebook_helpers.py
@@ -8,9 +8,8 @@ from google.colab import files
from IPython.display import Image as ipyimg
import ipywidgets as widgets
from PIL import Image
-from numpy import asarray
from einops import rearrange, repeat
-import torch, torchvision
+import torchvision
from ldm.models.diffusion.ddim import DDIMSampler
from ldm.util import ismap
import time
@@ -68,14 +67,14 @@ def get_custom_cond(mode):
elif mode == "text_conditional":
w = widgets.Text(value="A cake with cream!", disabled=True)
- display(w)
+ display(w) # noqa: F821
with open(f"{dest}/{mode}/custom_{w.value[:20]}.txt", "w") as f:
f.write(w.value)
elif mode == "class_conditional":
w = widgets.IntSlider(min=0, max=1000)
- display(w)
+ display(w) # noqa: F821
with open(f"{dest}/{mode}/custom.txt", "w") as f:
f.write(w.value)
@@ -96,7 +95,7 @@ def select_cond_path(mode):
onlyfiles = [f for f in sorted(os.listdir(path))]
selected = widgets.RadioButtons(options=onlyfiles, description="Select conditioning:", disabled=False)
- display(selected)
+ display(selected) # noqa: F821
selected_path = os.path.join(path, selected.value)
return selected_path
@@ -123,7 +122,7 @@ def get_cond(mode, selected_path):
def visualize_cond_img(path):
- display(ipyimg(filename=path))
+ display(ipyimg(filename=path)) # noqa: F821
def run(model, selected_path, task, custom_steps, resize_enabled=False, classifier_ckpt=None, global_step=None):
@@ -331,7 +330,7 @@ def make_convolutional_sample(
x_sample_noquant = model.decode_first_stage(sample, force_not_quantize=True)
log["sample_noquant"] = x_sample_noquant
log["sample_diff"] = torch.abs(x_sample_noquant - x_sample)
- except:
+ except Exception:
pass
log["sample"] = x_sample
diff --git a/pyproject.toml b/pyproject.toml
index ffa22b839e..9aef66a35f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -40,7 +40,7 @@ dependencies = [
"controlnet-aux>=0.0.6",
"timm==0.6.13", # needed to override timm latest in controlnet_aux, see https://github.com/isl-org/ZoeDepth/issues/26
"datasets",
- "diffusers[torch]~=0.19.3",
+ "diffusers[torch]~=0.20.0",
"dnspython~=2.4.0",
"dynamicprompts",
"easing-functions",
@@ -49,7 +49,7 @@ dependencies = [
"fastapi==0.88.0",
"fastapi-events==0.8.0",
"fastapi-socketio==0.0.10",
- "huggingface-hub>=0.11.1",
+ "huggingface-hub~=0.16.4",
"invisible-watermark~=0.2.0", # needed to install SDXL base and refiner using their repo_ids
"matplotlib", # needed for plotting of Penner easing functions
"mediapipe", # needed for "mediapipeface" controlnet model
@@ -96,7 +96,14 @@ dependencies = [
"jurigged",
"pudb",
]
-"test" = ["pytest>6.0.0", "pytest-cov", "pytest-datadir", "black"]
+"test" = [
+ "black",
+ "flake8",
+ "Flake8-pyproject",
+ "pytest>6.0.0",
+ "pytest-cov",
+ "pytest-datadir",
+]
"xformers" = [
"xformers~=0.0.19; sys_platform!='darwin'",
"triton; sys_platform=='linux'",
@@ -186,6 +193,8 @@ output = "coverage/index.xml"
[tool.flake8]
max-line-length = 120
+ignore = ["E203", "E266", "E501", "W503"]
+select = ["B", "C", "E", "F", "W", "T4"]
[tool.black]
line-length = 120
diff --git a/scripts/create_checkpoint_template.py b/scripts/create_checkpoint_template.py
index 7ff201c841..4b9bfe0ea2 100755
--- a/scripts/create_checkpoint_template.py
+++ b/scripts/create_checkpoint_template.py
@@ -4,7 +4,6 @@ Read a checkpoint/safetensors file and write out a template .json file containin
its metadata for use in fast model probing.
"""
-import sys
import argparse
import json
diff --git a/scripts/dream.py b/scripts/dream.py
index d2735046a4..47fec8c1c6 100755
--- a/scripts/dream.py
+++ b/scripts/dream.py
@@ -3,11 +3,12 @@
import warnings
+from invokeai.app.cli_app import invoke_cli
+
warnings.warn(
"dream.py is being deprecated, please run invoke.py for the " "new UI/API or legacy_api.py for the old API",
DeprecationWarning,
)
-from invokeai.app.cli_app import invoke_cli
invoke_cli()
diff --git a/scripts/images2prompt.py b/scripts/images2prompt.py
index 058fc0da40..fdfe52774b 100755
--- a/scripts/images2prompt.py
+++ b/scripts/images2prompt.py
@@ -2,7 +2,7 @@
"""This script reads the "Invoke" Stable Diffusion prompt embedded in files generated by invoke.py"""
import sys
-from PIL import Image, PngImagePlugin
+from PIL import Image
if len(sys.argv) < 2:
print("Usage: file2prompt.py <file1.png> <file2.png> <file3.png>...")
diff --git a/scripts/invokeai-cli.py b/scripts/invokeai-cli.py
index b32a892261..58aca1b5f3 100755
--- a/scripts/invokeai-cli.py
+++ b/scripts/invokeai-cli.py
@@ -2,13 +2,11 @@
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
+import os
import logging
logging.getLogger("xformers").addFilter(lambda record: "A matching Triton is not available" not in record.getMessage())
-import os
-import sys
-
def main():
# Change working directory to the repo root
diff --git a/scripts/invokeai-web.py b/scripts/invokeai-web.py
index 829cc4b911..ebdf7cfa81 100755
--- a/scripts/invokeai-web.py
+++ b/scripts/invokeai-web.py
@@ -2,13 +2,11 @@
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
+import os
import logging
logging.getLogger("xformers").addFilter(lambda record: "A matching Triton is not available" not in record.getMessage())
-import os
-import sys
-
def main():
# Change working directory to the repo root
diff --git a/scripts/orig_scripts/img2img.py b/scripts/orig_scripts/img2img.py
index 2601bc2562..eb60a144c4 100644
--- a/scripts/orig_scripts/img2img.py
+++ b/scripts/orig_scripts/img2img.py
@@ -1,6 +1,7 @@
"""make variations of input image"""
-import argparse, os, sys, glob
+import argparse
+import os
import PIL
import torch
import numpy as np
@@ -12,7 +13,6 @@ from einops import rearrange, repeat
from torchvision.utils import make_grid
from torch import autocast
from contextlib import nullcontext
-import time
from pytorch_lightning import seed_everything
from ldm.util import instantiate_from_config
@@ -234,7 +234,6 @@ def main():
with torch.no_grad():
with precision_scope(device.type):
with model.ema_scope():
- tic = time.time()
all_samples = list()
for n in trange(opt.n_iter, desc="Sampling"):
for prompts in tqdm(data, desc="data"):
@@ -279,8 +278,6 @@ def main():
Image.fromarray(grid.astype(np.uint8)).save(os.path.join(outpath, f"grid-{grid_count:04}.png"))
grid_count += 1
- toc = time.time()
-
print(f"Your samples are ready and waiting for you here: \n{outpath} \n" f" \nEnjoy.")
diff --git a/scripts/orig_scripts/inpaint.py b/scripts/orig_scripts/inpaint.py
index 8dfbbfb045..9979360b12 100644
--- a/scripts/orig_scripts/inpaint.py
+++ b/scripts/orig_scripts/inpaint.py
@@ -1,4 +1,6 @@
-import argparse, os, sys, glob
+import argparse
+import glob
+import os
from omegaconf import OmegaConf
from PIL import Image
from tqdm import tqdm
diff --git a/scripts/orig_scripts/knn2img.py b/scripts/orig_scripts/knn2img.py
index 845613479b..debdebdaa5 100644
--- a/scripts/orig_scripts/knn2img.py
+++ b/scripts/orig_scripts/knn2img.py
@@ -1,13 +1,13 @@
-import argparse, os, sys, glob
-import clip
+import argparse
+import glob
+import os
import torch
-import torch.nn as nn
import numpy as np
from omegaconf import OmegaConf
from PIL import Image
from tqdm import tqdm, trange
from itertools import islice
-from einops import rearrange, repeat
+from einops import rearrange
from torchvision.utils import make_grid
import scann
import time
@@ -390,8 +390,8 @@ if __name__ == "__main__":
grid = make_grid(grid, nrow=n_rows)
# to image
- grid = 255.0 * rearrange(grid, "c h w -> h w c").cpu().numpy()
- Image.fromarray(grid.astype(np.uint8)).save(os.path.join(outpath, f"grid-{grid_count:04}.png"))
+ grid_np = 255.0 * rearrange(grid, "c h w -> h w c").cpu().numpy()
+ Image.fromarray(grid_np.astype(np.uint8)).save(os.path.join(outpath, f"grid-{grid_count:04}.png"))
grid_count += 1
print(f"Your samples are ready and waiting for you here: \n{outpath} \nEnjoy.")
diff --git a/scripts/orig_scripts/main.py b/scripts/orig_scripts/main.py
index 8269809fbc..e61c5b4593 100644
--- a/scripts/orig_scripts/main.py
+++ b/scripts/orig_scripts/main.py
@@ -1,24 +1,24 @@
-import argparse, os, sys, datetime, glob, importlib, csv
+import argparse
+import datetime
+import glob
+import os
+import sys
+
import numpy as np
import time
import torch
-
import torchvision
import pytorch_lightning as pl
from packaging import version
from omegaconf import OmegaConf
-from torch.utils.data import random_split, DataLoader, Dataset, Subset
+from torch.utils.data import DataLoader, Dataset
from functools import partial
from PIL import Image
from pytorch_lightning import seed_everything
from pytorch_lightning.trainer import Trainer
-from pytorch_lightning.callbacks import (
- ModelCheckpoint,
- Callback,
- LearningRateMonitor,
-)
+from pytorch_lightning.callbacks import Callback
from pytorch_lightning.utilities.distributed import rank_zero_only
from pytorch_lightning.utilities import rank_zero_info
@@ -651,7 +651,7 @@ if __name__ == "__main__":
trainer_config["accelerator"] = "auto"
for k in nondefault_trainer_args(opt):
trainer_config[k] = getattr(opt, k)
- if not "gpus" in trainer_config:
+ if "gpus" not in trainer_config:
del trainer_config["accelerator"]
cpu = True
else:
@@ -803,7 +803,7 @@ if __name__ == "__main__":
trainer_opt.detect_anomaly = False
trainer = Trainer.from_argparse_args(trainer_opt, **trainer_kwargs)
- trainer.logdir = logdir ###
+ trainer.logdir = logdir
# data
config.data.params.train.params.data_root = opt.data_root
diff --git a/scripts/orig_scripts/merge_embeddings.py b/scripts/orig_scripts/merge_embeddings.py
index c2cf1acb1a..f0a18cfae1 100755
--- a/scripts/orig_scripts/merge_embeddings.py
+++ b/scripts/orig_scripts/merge_embeddings.py
@@ -2,7 +2,7 @@ from ldm.modules.encoders.modules import FrozenCLIPEmbedder, BERTEmbedder
from ldm.modules.embedding_manager import EmbeddingManager
from ldm.invoke.globals import Globals
-import argparse, os
+import argparse
from functools import partial
import torch
@@ -108,7 +108,7 @@ if __name__ == "__main__":
manager.load(manager_ckpt)
for placeholder_string in manager.string_to_token_dict:
- if not placeholder_string in string_to_token_dict:
+ if placeholder_string not in string_to_token_dict:
string_to_token_dict[placeholder_string] = manager.string_to_token_dict[placeholder_string]
string_to_param_dict[placeholder_string] = manager.string_to_param_dict[placeholder_string]
diff --git a/scripts/orig_scripts/sample_diffusion.py b/scripts/orig_scripts/sample_diffusion.py
index 9f08b6702a..76a9c1b5e6 100644
--- a/scripts/orig_scripts/sample_diffusion.py
+++ b/scripts/orig_scripts/sample_diffusion.py
@@ -1,6 +1,12 @@
-import argparse, os, sys, glob, datetime, yaml
-import torch
+import argparse
+import datetime
+import glob
+import os
+import sys
import time
+import yaml
+
+import torch
import numpy as np
from tqdm import trange
@@ -10,7 +16,9 @@ from PIL import Image
from ldm.models.diffusion.ddim import DDIMSampler
from ldm.util import instantiate_from_config
-rescale = lambda x: (x + 1.0) / 2.0
+
+def rescale(x: float) -> float:
+ return (x + 1.0) / 2.0
def custom_to_pil(x):
@@ -45,7 +53,7 @@ def logs2pil(logs, keys=["sample"]):
else:
print(f"Unknown format for key {k}. ")
img = None
- except:
+ except Exception:
img = None
imgs[k] = img
return imgs
diff --git a/scripts/orig_scripts/train_searcher.py b/scripts/orig_scripts/train_searcher.py
index 7ba57f1165..5fd2962f59 100644
--- a/scripts/orig_scripts/train_searcher.py
+++ b/scripts/orig_scripts/train_searcher.py
@@ -1,4 +1,5 @@
-import os, sys
+import os
+import sys
import numpy as np
import scann
import argparse
diff --git a/scripts/orig_scripts/txt2img.py b/scripts/orig_scripts/txt2img.py
index 58767c122d..9f5b94f0dd 100644
--- a/scripts/orig_scripts/txt2img.py
+++ b/scripts/orig_scripts/txt2img.py
@@ -1,4 +1,5 @@
-import argparse, os, sys, glob
+import argparse
+import os
import torch
import numpy as np
from omegaconf import OmegaConf
@@ -7,10 +8,9 @@ from tqdm import tqdm, trange
from itertools import islice
from einops import rearrange
from torchvision.utils import make_grid
-import time
from pytorch_lightning import seed_everything
from torch import autocast
-from contextlib import contextmanager, nullcontext
+from contextlib import nullcontext
import k_diffusion as K
import torch.nn as nn
@@ -251,7 +251,6 @@ def main():
with torch.no_grad():
with precision_scope(device.type):
with model.ema_scope():
- tic = time.time()
all_samples = list()
for n in trange(opt.n_iter, desc="Sampling"):
for prompts in tqdm(data, desc="data"):
@@ -310,8 +309,6 @@ def main():
Image.fromarray(grid.astype(np.uint8)).save(os.path.join(outpath, f"grid-{grid_count:04}.png"))
grid_count += 1
- toc = time.time()
-
print(f"Your samples are ready and waiting for you here: \n{outpath} \n" f" \nEnjoy.")
diff --git a/scripts/probe-model.py b/scripts/probe-model.py
index 4cf2c50263..9b4ee6e815 100755
--- a/scripts/probe-model.py
+++ b/scripts/probe-model.py
@@ -1,7 +1,6 @@
#!/bin/env python
import argparse
-import sys
from pathlib import Path
from invokeai.backend.model_management.model_probe import ModelProbe
diff --git a/tests/nodes/test_graph_execution_state.py b/tests/nodes/test_graph_execution_state.py
index 248bc6fee1..cc3cc0288b 100644
--- a/tests/nodes/test_graph_execution_state.py
+++ b/tests/nodes/test_graph_execution_state.py
@@ -90,17 +90,17 @@ def test_graph_state_executes_in_order(simple_graph, mock_services):
def test_graph_is_complete(simple_graph, mock_services):
g = GraphExecutionState(graph=simple_graph)
- n1 = invoke_next(g, mock_services)
- n2 = invoke_next(g, mock_services)
- n3 = g.next()
+ _ = invoke_next(g, mock_services)
+ _ = invoke_next(g, mock_services)
+ _ = g.next()
assert g.is_complete()
def test_graph_is_not_complete(simple_graph, mock_services):
g = GraphExecutionState(graph=simple_graph)
- n1 = invoke_next(g, mock_services)
- n2 = g.next()
+ _ = invoke_next(g, mock_services)
+ _ = g.next()
assert not g.is_complete()
@@ -140,11 +140,11 @@ def test_graph_state_collects(mock_services):
graph.add_edge(create_edge("3", "prompt", "4", "item"))
g = GraphExecutionState(graph=graph)
- n1 = invoke_next(g, mock_services)
- n2 = invoke_next(g, mock_services)
- n3 = invoke_next(g, mock_services)
- n4 = invoke_next(g, mock_services)
- n5 = invoke_next(g, mock_services)
+ _ = invoke_next(g, mock_services)
+ _ = invoke_next(g, mock_services)
+ _ = invoke_next(g, mock_services)
+ _ = invoke_next(g, mock_services)
+ _ = invoke_next(g, mock_services)
n6 = invoke_next(g, mock_services)
assert isinstance(n6[0], CollectInvocation)
@@ -195,10 +195,10 @@ def test_graph_executes_depth_first(mock_services):
graph.add_edge(create_edge("prompt_iterated", "prompt", "prompt_successor", "prompt"))
g = GraphExecutionState(graph=graph)
- n1 = invoke_next(g, mock_services)
- n2 = invoke_next(g, mock_services)
- n3 = invoke_next(g, mock_services)
- n4 = invoke_next(g, mock_services)
+ _ = invoke_next(g, mock_services)
+ _ = invoke_next(g, mock_services)
+ _ = invoke_next(g, mock_services)
+ _ = invoke_next(g, mock_services)
# Because ordering is not guaranteed, we cannot compare results directly.
# Instead, we must count the number of results.
@@ -211,17 +211,17 @@ def test_graph_executes_depth_first(mock_services):
assert get_completed_count(g, "prompt_iterated") == 1
assert get_completed_count(g, "prompt_successor") == 0
- n5 = invoke_next(g, mock_services)
+ _ = invoke_next(g, mock_services)
assert get_completed_count(g, "prompt_iterated") == 1
assert get_completed_count(g, "prompt_successor") == 1
- n6 = invoke_next(g, mock_services)
+ _ = invoke_next(g, mock_services)
assert get_completed_count(g, "prompt_iterated") == 2
assert get_completed_count(g, "prompt_successor") == 1
- n7 = invoke_next(g, mock_services)
+ _ = invoke_next(g, mock_services)
assert get_completed_count(g, "prompt_iterated") == 2
assert get_completed_count(g, "prompt_successor") == 2
diff --git a/tests/nodes/test_node_graph.py b/tests/nodes/test_node_graph.py
index b16eef95c8..f03e23e1c2 100644
--- a/tests/nodes/test_node_graph.py
+++ b/tests/nodes/test_node_graph.py
@@ -17,7 +17,8 @@ from invokeai.app.services.graph import (
IterateInvocation,
)
from invokeai.app.invocations.upscale import ESRGANInvocation
-from invokeai.app.invocations.image import *
+
+from invokeai.app.invocations.image import ShowImageInvocation
from invokeai.app.invocations.math import AddInvocation, SubtractInvocation
from invokeai.app.invocations.primitives import IntegerInvocation
from invokeai.app.services.default_graphs import create_text_to_image
@@ -41,7 +42,7 @@ def test_connections_are_compatible():
result = are_connections_compatible(from_node, from_field, to_node, to_field)
- assert result == True
+ assert result is True
def test_connections_are_incompatible():
@@ -52,7 +53,7 @@ def test_connections_are_incompatible():
result = are_connections_compatible(from_node, from_field, to_node, to_field)
- assert result == False
+ assert result is False
def test_connections_incompatible_with_invalid_fields():
@@ -63,14 +64,14 @@ def test_connections_incompatible_with_invalid_fields():
# From field is invalid
result = are_connections_compatible(from_node, from_field, to_node, to_field)
- assert result == False
+ assert result is False
# To field is invalid
from_field = "image"
to_field = "invalid_field"
result = are_connections_compatible(from_node, from_field, to_node, to_field)
- assert result == False
+ assert result is False
def test_graph_can_add_node():
@@ -394,7 +395,7 @@ def test_graph_validates():
e1 = create_edge("1", "image", "2", "image")
g.add_edge(e1)
- assert g.is_valid() == True
+ assert g.is_valid() is True
def test_graph_invalid_if_edges_reference_missing_nodes():
@@ -404,7 +405,7 @@ def test_graph_invalid_if_edges_reference_missing_nodes():
e1 = create_edge("1", "image", "2", "image")
g.edges.append(e1)
- assert g.is_valid() == False
+ assert g.is_valid() is False
def test_graph_invalid_if_subgraph_invalid():
@@ -419,7 +420,7 @@ def test_graph_invalid_if_subgraph_invalid():
g.nodes[n1.id] = n1
- assert g.is_valid() == False
+ assert g.is_valid() is False
def test_graph_invalid_if_has_cycle():
@@ -433,7 +434,7 @@ def test_graph_invalid_if_has_cycle():
g.edges.append(e1)
g.edges.append(e2)
- assert g.is_valid() == False
+ assert g.is_valid() is False
def test_graph_invalid_with_invalid_connection():
@@ -445,7 +446,7 @@ def test_graph_invalid_with_invalid_connection():
e1 = create_edge("1", "image", "2", "strength")
g.edges.append(e1)
- assert g.is_valid() == False
+ assert g.is_valid() is False
# TODO: Subgraph operations
@@ -536,7 +537,7 @@ def test_graph_fails_to_get_missing_subgraph_node():
g.add_node(n1)
with pytest.raises(NodeNotFoundError):
- result = g.get_node("1.2")
+ _ = g.get_node("1.2")
def test_graph_fails_to_enumerate_non_subgraph_node():
@@ -554,7 +555,7 @@ def test_graph_fails_to_enumerate_non_subgraph_node():
g.add_node(n2)
with pytest.raises(NodeNotFoundError):
- result = g.get_node("2.1")
+ _ = g.get_node("2.1")
def test_graph_gets_networkx_graph():
@@ -584,7 +585,7 @@ def test_graph_can_serialize():
g.add_edge(e)
# Not throwing on this line is sufficient
- json = g.json()
+ _ = g.json()
def test_graph_can_deserialize():
@@ -612,4 +613,4 @@ def test_graph_can_deserialize():
def test_graph_can_generate_schema():
# Not throwing on this line is sufficient
# NOTE: if this test fails, it's PROBABLY because a new invocation type is breaking schema generation
- schema = Graph.schema_json(indent=2)
+ _ = Graph.schema_json(indent=2)
diff --git a/tests/nodes/test_nodes.py b/tests/nodes/test_nodes.py
index 13338e9261..92faa6a0ba 100644
--- a/tests/nodes/test_nodes.py
+++ b/tests/nodes/test_nodes.py
@@ -1,9 +1,7 @@
from typing import Any, Callable, Literal, Union
+from pydantic import Field
from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationContext
from invokeai.app.invocations.image import ImageField
-from invokeai.app.services.invocation_services import InvocationServices
-from pydantic import Field
-import pytest
# Define test invocations before importing anything that uses invocations
@@ -82,8 +80,9 @@ class PromptCollectionTestInvocation(BaseInvocation):
return PromptCollectionTestInvocationOutput(collection=self.collection.copy())
-from invokeai.app.services.events import EventServiceBase
-from invokeai.app.services.graph import Edge, EdgeConnection
+# Importing these at the top breaks previous tests
+from invokeai.app.services.events import EventServiceBase # noqa: E402
+from invokeai.app.services.graph import Edge, EdgeConnection # noqa: E402
def create_edge(from_id: str, from_field: str, to_id: str, to_field: str) -> Edge:
diff --git a/tests/test_config.py b/tests/test_config.py
index 721edce487..0a8d44ad34 100644
--- a/tests/test_config.py
+++ b/tests/test_config.py
@@ -1,13 +1,16 @@
import os
-import pytest
-import sys
+from typing import Any
+import pytest
from omegaconf import OmegaConf
from pathlib import Path
-os.environ["INVOKEAI_ROOT"] = "/tmp"
-from invokeai.app.services.config import InvokeAIAppConfig
+@pytest.fixture
+def patch_rootdir(tmp_path: Path, monkeypatch: Any) -> None:
+ """This may be overkill since the current tests don't need the root dir to exist"""
+ monkeypatch.setenv("INVOKEAI_ROOT", str(tmp_path))
+
init1 = OmegaConf.create(
"""
@@ -32,10 +35,12 @@ InvokeAI:
)
-def test_use_init():
+def test_use_init(patch_rootdir):
# note that we explicitly set omegaconf dict and argv here
# so that the values aren't read from ~invokeai/invokeai.yaml and
# sys.argv respectively.
+ from invokeai.app.services.config import InvokeAIAppConfig
+
conf1 = InvokeAIAppConfig.get_config()
assert conf1
conf1.parse_args(conf=init1, argv=[])
@@ -51,7 +56,9 @@ def test_use_init():
assert not hasattr(conf2, "invalid_attribute")
-def test_argv_override():
+def test_argv_override(patch_rootdir):
+ from invokeai.app.services.config import InvokeAIAppConfig
+
conf = InvokeAIAppConfig.get_config()
conf.parse_args(conf=init1, argv=["--always_use_cpu", "--max_cache=10"])
assert conf.always_use_cpu
@@ -59,14 +66,16 @@ def test_argv_override():
assert conf.outdir == Path("outputs") # this is the default
-def test_env_override():
+def test_env_override(patch_rootdir):
+ from invokeai.app.services.config import InvokeAIAppConfig
+
# argv overrides
conf = InvokeAIAppConfig()
conf.parse_args(conf=init1, argv=["--max_cache=10"])
- assert conf.always_use_cpu == False
+ assert conf.always_use_cpu is False
os.environ["INVOKEAI_always_use_cpu"] = "True"
conf.parse_args(conf=init1, argv=["--max_cache=10"])
- assert conf.always_use_cpu == True
+ assert conf.always_use_cpu is True
# environment variables should be case insensitive
os.environ["InvokeAI_Max_Cache_Size"] = "15"
@@ -76,7 +85,7 @@ def test_env_override():
conf = InvokeAIAppConfig()
conf.parse_args(conf=init1, argv=["--no-always_use_cpu", "--max_cache=10"])
- assert conf.always_use_cpu == False
+ assert conf.always_use_cpu is False
assert conf.max_cache_size == 10
conf = InvokeAIAppConfig.get_config(max_cache_size=20)
@@ -84,7 +93,9 @@ def test_env_override():
assert conf.max_cache_size == 20
-def test_root_resists_cwd():
+def test_root_resists_cwd(patch_rootdir):
+ from invokeai.app.services.config import InvokeAIAppConfig
+
previous = os.environ["INVOKEAI_ROOT"]
cwd = Path(os.getcwd()).resolve()
@@ -99,7 +110,9 @@ def test_root_resists_cwd():
os.chdir(cwd)
-def test_type_coercion():
+def test_type_coercion(patch_rootdir):
+ from invokeai.app.services.config import InvokeAIAppConfig
+
conf = InvokeAIAppConfig().get_config()
conf.parse_args(argv=["--root=/tmp/foobar"])
assert conf.root == Path("/tmp/foobar")