wehub-resource-sync
120 lines
4.7 KiB
Python
120 lines
4.7 KiB
Python
#
|
|
# SPDX-FileCopyrightText: Copyright (c) 1993-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
|
|
# SPDX-License-Identifier: Apache-2.0
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
#
|
|
"""
|
|
Functions for loading models.
|
|
"""
|
|
from __future__ import annotations
|
|
|
|
import gc
|
|
import glob
|
|
import os
|
|
import sys
|
|
from typing import List, Optional
|
|
|
|
import torch
|
|
|
|
import onnx
|
|
|
|
|
|
def onnx_graph_needs_external_data(onnx_graph: onnx.ModelProto) -> bool:
|
|
"""Return true if ONNX graph needs to store external data."""
|
|
if sys.platform == "win32":
|
|
# ByteSize is broken (wraps around) on Windows, so always assume external data is needed.
|
|
return True
|
|
else:
|
|
TWO_GIGABYTES = 2147483648
|
|
return onnx_graph.ByteSize() > TWO_GIGABYTES
|
|
|
|
|
|
def get_path(version: str, pipeline: "pipeline.DiffusionPipeline", controlnets: Optional[List[str]] = None) -> str:
|
|
"""Return the relative path to the model files directory."""
|
|
if controlnets is not None:
|
|
if version == "xl-1.0":
|
|
return ["diffusers/controlnet-canny-sdxl-1.0"]
|
|
if version == "3.5-large":
|
|
return f"stabilityai/stable-diffusion-3.5-large-controlnet-{controlnets}"
|
|
return ["lllyasviel/sd-controlnet-" + modality for modality in controlnets]
|
|
|
|
elif version == "1.4":
|
|
return "CompVis/stable-diffusion-v1-4"
|
|
elif version == "dreamshaper-7":
|
|
return "Lykon/dreamshaper-7"
|
|
elif version == "xl-1.0" and pipeline.is_sd_xl_base():
|
|
return "stabilityai/stable-diffusion-xl-base-1.0"
|
|
elif version == "xl-1.0" and pipeline.is_sd_xl_refiner():
|
|
return "stabilityai/stable-diffusion-xl-refiner-1.0"
|
|
# TODO SDXL turbo with refiner
|
|
elif version == "xl-turbo" and pipeline.is_sd_xl_base():
|
|
return "stabilityai/sdxl-turbo"
|
|
elif version == "sd3":
|
|
return "stabilityai/stable-diffusion-3-medium"
|
|
elif version == "3.5-medium":
|
|
return "stabilityai/stable-diffusion-3.5-medium"
|
|
elif version == "3.5-large":
|
|
return "stabilityai/stable-diffusion-3.5-large"
|
|
elif version == "svd-xt-1.1" and pipeline.is_img2vid():
|
|
return "stabilityai/stable-video-diffusion-img2vid-xt-1-1"
|
|
elif version == "cascade":
|
|
if pipeline.is_cascade_decoder():
|
|
return "stabilityai/stable-cascade"
|
|
else:
|
|
return "stabilityai/stable-cascade-prior"
|
|
elif version == "flux.1-dev":
|
|
return "black-forest-labs/FLUX.1-dev"
|
|
elif version == "flux.1-schnell":
|
|
return "black-forest-labs/FLUX.1-schnell"
|
|
elif version == "flux.1-dev-canny":
|
|
return "black-forest-labs/FLUX.1-Canny-dev"
|
|
elif version == "flux.1-dev-depth":
|
|
return "black-forest-labs/FLUX.1-Depth-dev"
|
|
elif version == "flux.1-kontext-dev":
|
|
return "black-forest-labs/FLUX.1-Kontext-dev"
|
|
elif version == "wan2.2-t2v-a14b":
|
|
return "Wan-AI/Wan2.2-T2V-A14B-Diffusers"
|
|
elif version == "cosmos-predict2-2b-text2image":
|
|
return "nvidia/Cosmos-Predict2-2B-Text2Image"
|
|
elif version == "cosmos-predict2-14b-text2image":
|
|
return "nvidia/Cosmos-Predict2-14B-Text2Image"
|
|
elif version == "cosmos-predict2-2b-video2world":
|
|
return "nvidia/Cosmos-Predict2-2B-Video2World"
|
|
elif version == "cosmos-predict2-14b-video2world":
|
|
return "nvidia/Cosmos-Predict2-14B-Video2World"
|
|
else:
|
|
raise ValueError(f"Unsupported version {version} + pipeline {pipeline.name}")
|
|
|
|
|
|
# FIXME serialization not supported for torch.compile
|
|
def get_checkpoint_dir(framework_model_dir: str, version: str, pipeline: str, subfolder: str) -> str:
|
|
"""Return the path to the torch model checkpoint directory."""
|
|
return os.path.join(framework_model_dir, version, pipeline, subfolder)
|
|
|
|
|
|
def is_model_cached(model_dir, model_opts, hf_safetensor, model_name="diffusion_pytorch_model") -> bool:
|
|
"""Return True if model was cached."""
|
|
variant = "." + model_opts.get("variant") if "variant" in model_opts else ""
|
|
suffix = ".safetensors" if hf_safetensor else ".bin"
|
|
# WAR with * for larger models that are split into multiple smaller ckpt files
|
|
model_file = model_name + variant + "*" + suffix
|
|
return bool(glob.glob(os.path.join(model_dir, model_file)))
|
|
|
|
|
|
def unload_torch_model(model):
|
|
if model:
|
|
del model
|
|
torch.cuda.empty_cache()
|
|
gc.collect()
|