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fix: Make DepthAnything work with Invoke's Model Management

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blessedcoolant
2024-07-31 03:57:54 +05:30
parent f170697ebe
commit 18f89ed5ed
4 changed files with 47 additions and 5 deletions
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5
invokeai/backend/model_manager/config.py
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@ -31,13 +31,16 @@ from pydantic import BaseModel, ConfigDict, Discriminator, Field, Tag, TypeAdapt
from typing_extensions import Annotated, Any, Dict
from invokeai.app.util.misc import uuid_string
from invokeai.backend.image_util.depth_anything.depth_anything_pipeline import DepthAnythingPipeline
from invokeai.backend.model_hash.hash_validator import validate_hash
from invokeai.backend.raw_model import RawModel
from invokeai.backend.stable_diffusion.schedulers.schedulers import SCHEDULER_NAME_VALUES
# ModelMixin is the base class for all diffusers and transformers models
# RawModel is the InvokeAI wrapper class for ip_adapters, loras, textual_inversion and onnx runtime
AnyModel = Union[ModelMixin, RawModel, torch.nn.Module, Dict[str, torch.Tensor], diffusers.DiffusionPipeline]
AnyModel = Union[
ModelMixin, RawModel, torch.nn.Module, Dict[str, torch.Tensor], diffusers.DiffusionPipeline, DepthAnythingPipeline
]
class InvalidModelConfigException(Exception):

5
invokeai/backend/model_manager/load/model_util.py
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@ -11,6 +11,7 @@ from diffusers.pipelines.pipeline_utils import DiffusionPipeline
from diffusers.schedulers.scheduling_utils import SchedulerMixin
from transformers import CLIPTokenizer
from invokeai.backend.image_util.depth_anything.depth_anything_pipeline import DepthAnythingPipeline
from invokeai.backend.ip_adapter.ip_adapter import IPAdapter
from invokeai.backend.lora import LoRAModelRaw
from invokeai.backend.model_manager.config import AnyModel
@ -34,7 +35,9 @@ def calc_model_size_by_data(logger: logging.Logger, model: AnyModel) -> int:
elif isinstance(model, CLIPTokenizer):
# TODO(ryand): Accurately calculate the tokenizer's size. It's small enough that it shouldn't matter for now.
return 0
elif isinstance(model, (TextualInversionModelRaw, IPAdapter, LoRAModelRaw, SpandrelImageToImageModel)):
elif isinstance(
model, (TextualInversionModelRaw, IPAdapter, LoRAModelRaw, SpandrelImageToImageModel, DepthAnythingPipeline)
):
return model.calc_size()
else:
# TODO(ryand): Promote this from a log to an exception once we are confident that we are handling all of the