python_code stringlengths 0 290k | repo_name stringclasses 30
values | file_path stringlengths 6 125 |
|---|---|---|
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
... | diffusers-main | examples/community/speech_to_image_diffusion.py |
#!/usr/bin/env python3
import torch
from diffusers import DiffusionPipeline
class UnetSchedulerOneForwardPipeline(DiffusionPipeline):
def __init__(self, unet, scheduler):
super().__init__()
self.register_modules(unet=unet, scheduler=scheduler)
def __call__(self):
image = torch.randn... | diffusers-main | examples/community/one_step_unet.py |
from typing import Optional, Tuple, Union
import torch
from einops import rearrange, reduce
from diffusers import DDIMScheduler, DDPMScheduler, DiffusionPipeline, ImagePipelineOutput, UNet2DConditionModel
from diffusers.schedulers.scheduling_ddim import DDIMSchedulerOutput
from diffusers.schedulers.scheduling_ddpm im... | diffusers-main | examples/community/bit_diffusion.py |
import inspect
import re
from typing import Callable, List, Optional, Union
import numpy as np
import PIL.Image
import torch
from packaging import version
from transformers import CLIPImageProcessor, CLIPTokenizer
import diffusers
from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, SchedulerMixin
fro... | diffusers-main | examples/community/lpw_stable_diffusion_onnx.py |
#
# Copyright 2023 The HuggingFace Inc. team.
# SPDX-FileCopyrightText: Copyright (c) 1993-2023 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 Licens... | diffusers-main | examples/community/stable_diffusion_tensorrt_inpaint.py |
import argparse
import atexit
import inspect
import os
import time
import warnings
from typing import Any, Callable, Dict, List, Optional, Union
import numpy as np
import PIL.Image
import pycuda.driver as cuda
import tensorrt as trt
import torch
from PIL import Image
from pycuda.tools import make_default_context
from ... | diffusers-main | examples/community/run_tensorrt_controlnet.py |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# 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 applicabl... | diffusers-main | examples/community/ddim_noise_comparative_analysis.py |
#
# Copyright 2023 The HuggingFace Inc. team.
# SPDX-FileCopyrightText: Copyright (c) 1993-2023 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 Licens... | diffusers-main | examples/community/stable_diffusion_tensorrt_txt2img.py |
# Inspired by: https://github.com/Mikubill/sd-webui-controlnet/discussions/1236 and https://github.com/Mikubill/sd-webui-controlnet/discussions/1280
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import numpy as np
import PIL.Image
import torch
from diffusers import StableDiffusionPipeline
from ... | diffusers-main | examples/community/stable_diffusion_reference.py |
"""
modeled after the textual_inversion.py / train_dreambooth.py and the work
of justinpinkney here: https://github.com/justinpinkney/stable-diffusion/blob/main/notebooks/imagic.ipynb
"""
import inspect
import warnings
from typing import List, Optional, Union
import numpy as np
import PIL.Image
import torch
im... | diffusers-main | examples/community/imagic_stable_diffusion.py |
import inspect
from typing import List, Optional, Union
import torch
from torch import nn
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPImageProcessor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
Diffu... | diffusers-main | examples/community/clip_guided_stable_diffusion.py |
# Inspired by: https://github.com/Mikubill/sd-webui-controlnet/discussions/1236 and https://github.com/Mikubill/sd-webui-controlnet/discussions/1280
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import numpy as np
import PIL.Image
import torch
from diffusers import StableDiffusionControlNetPipe... | diffusers-main | examples/community/stable_diffusion_controlnet_reference.py |
# Based on stable_diffusion_reference.py
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import numpy as np
import PIL.Image
import torch
from diffusers import StableDiffusionXLPipeline
from diffusers.models.attention import BasicTransformerBlock
from diffusers.models.unet_2d_blocks import (
... | diffusers-main | examples/community/stable_diffusion_xl_reference.py |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# 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 applicabl... | diffusers-main | examples/community/pipeline_prompt2prompt.py |
from typing import List, Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline
from diffusers.configuration_utils import ConfigMixin
from diffusers.pipeline_utils import ImagePipelineOutput
from diffusers.schedulers.scheduling_utils import SchedulerMixin
class IADBScheduler(SchedulerMixin, Con... | diffusers-main | examples/community/iadb.py |
"""
modified based on diffusion library from Huggingface: https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py
"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPText... | diffusers-main | examples/community/seed_resize_stable_diffusion.py |
# -*- coding: utf-8 -*-
import inspect
from typing import Optional, Union
import numpy as np
import PIL.Image
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
Autoenco... | diffusers-main | examples/community/clip_guided_images_mixing_stable_diffusion.py |
## ----------------------------------------------------------
# A SDXL pipeline can take unlimited weighted prompt
#
# Author: Andrew Zhu
# Github: https://github.com/xhinker
# Medium: https://medium.com/@xhinker
## -----------------------------------------------------------
import inspect
import os
from typing import... | diffusers-main | examples/community/lpw_stable_diffusion_xl.py |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# 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 applicabl... | diffusers-main | examples/community/stable_diffusion_ipex.py |
# Inspired by: https://github.com/haofanwang/ControlNet-for-Diffusers/
import inspect
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import numpy as np
import PIL.Image
import torch
import torch.nn.functional as F
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from di... | diffusers-main | examples/community/stable_diffusion_controlnet_inpaint.py |
# Copyright 2023 FABRIC authors and the HuggingFace Team. All rights reserved.
#
# 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 re... | diffusers-main | examples/community/pipeline_fabric.py |
# Copyright 2023 Peter Willemsen <peter@codebuffet.co>. All rights reserved.
#
# 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 requ... | diffusers-main | examples/community/tiled_upscaling.py |
from typing import Any, Callable, Dict, List, Optional, Union
import PIL.Image
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionImg... | diffusers-main | examples/community/stable_diffusion_mega.py |
import types
from typing import List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModelWithProjection, CLIPTokenizer
from transformers.models.clip.modeling_clip import CLIPTextModelOutput
from diffusers.models import PriorTransformer
from diffusers.pipelines import DiffusionPipeline, StableDi... | diffusers-main | examples/community/stable_unclip.py |
from typing import Any, Callable, Dict, List, Optional, Union
import numpy as np
import PIL.Image
import torch
from diffusers import StableDiffusionImg2ImgPipeline
from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
class MaskedStableDiffusionImg2ImgPipeline(StableDiffusionImg2ImgPipeline... | diffusers-main | examples/community/masked_stable_diffusion_img2img.py |
import inspect
from typing import Callable, List, Optional, Tuple, Union
import numpy as np
import PIL.Image
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.configuration_utils import FrozenDict
from diffusers.models import ... | diffusers-main | examples/community/img2img_inpainting.py |
# Inspired by: https://github.com/haofanwang/ControlNet-for-Diffusers/
import inspect
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import numpy as np
import PIL.Image
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, Co... | diffusers-main | examples/community/stable_diffusion_controlnet_img2img.py |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# 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 applicabl... | diffusers-main | examples/community/composable_stable_diffusion.py |
import inspect
from typing import List, Optional, Union
import numpy as np
import PIL.Image
import torch
from torch import nn
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
Autoe... | diffusers-main | examples/community/clip_guided_stable_diffusion_img2img.py |
import argparse
import inspect
import os
import time
import warnings
from typing import Any, Callable, Dict, List, Optional, Union
import numpy as np
import PIL.Image
import torch
from PIL import Image
from transformers import CLIPTokenizer
from diffusers import OnnxRuntimeModel, StableDiffusionImg2ImgPipeline, UniPC... | diffusers-main | examples/community/run_onnx_controlnet.py |
from typing import Union
import torch
from PIL import Image
from torchvision import transforms as tfms
from tqdm.auto import tqdm
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
... | diffusers-main | examples/community/magic_mix.py |
import inspect
import time
from pathlib import Path
from typing import Callable, List, Optional, Union
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.configuration_utils import FrozenDict
from diffusers.m... | diffusers-main | examples/community/interpolate_stable_diffusion.py |
from typing import Callable, List, Optional, Union
import PIL.Image
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_utils import FrozenDic... | diffusers-main | examples/community/text_inpainting.py |
import inspect
from typing import List, Optional, Tuple, Union
import torch
from torch.nn import functional as F
from transformers import CLIPTextModelWithProjection, CLIPTokenizer
from transformers.models.clip.modeling_clip import CLIPTextModelOutput
from diffusers import (
DiffusionPipeline,
ImagePipelineOu... | diffusers-main | examples/community/unclip_text_interpolation.py |
from typing import Optional
import torch
from PIL import Image
from tqdm.auto import tqdm
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, DiffusionPipeline, UNet2DConditionModel
from diffusers.image_processor import VaeImageProcessor
from diffusers.utils impor... | diffusers-main | examples/community/edict_pipeline.py |
import glob
import os
from typing import Dict, List, Union
import safetensors.torch
import torch
from huggingface_hub import snapshot_download
from diffusers import DiffusionPipeline, __version__
from diffusers.schedulers.scheduling_utils import SCHEDULER_CONFIG_NAME
from diffusers.utils import CONFIG_NAME, DIFFUSERS... | diffusers-main | examples/community/checkpoint_merger.py |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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... | diffusers-main | scripts/convert_original_audioldm2_to_diffusers.py |
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def convert_ldm_original(checkpoint_path, config_path, output_path):
config = OmegaConf.load(config_path)
state_dict = torch.load(checkpoint_path, map_location="cpu")["model"]
keys = lis... | diffusers-main | scripts/conversion_ldm_uncond.py |
import argparse
import time
from pathlib import Path
from typing import Any, Dict, Literal
import torch
from diffusers import AsymmetricAutoencoderKL
ASYMMETRIC_AUTOENCODER_KL_x_1_5_CONFIG = {
"in_channels": 3,
"out_channels": 3,
"down_block_types": [
"DownEncoderBlock2D",
"DownEncoderBl... | diffusers-main | scripts/convert_asymmetric_vqgan_to_diffusers.py |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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... | diffusers-main | scripts/convert_original_controlnet_to_diffusers.py |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# 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 applicabl... | diffusers-main | scripts/convert_vae_diff_to_onnx.py |
import argparse
import os
import torch
from torchvision.datasets.utils import download_url
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, Transformer2DModel
pretrained_models = {512: "DiT-XL-2-512x512.pt", 256: "DiT-XL-2-256x256.pt"}
def download_model(model_name):
"""
Downloads a pre-tr... | diffusers-main | scripts/convert_dit_to_diffusers.py |
# Script for converting a HF Diffusers saved pipeline to a Stable Diffusion checkpoint.
# *Only* converts the UNet, VAE, and Text Encoder.
# Does not convert optimizer state or any other thing.
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# ========... | diffusers-main | scripts/convert_diffusers_to_original_stable_diffusion.py |
# Run inside root directory of official source code: https://github.com/dome272/wuerstchen/
import os
import torch
from transformers import AutoTokenizer, CLIPTextModel
from vqgan import VQModel
from diffusers import (
DDPMWuerstchenScheduler,
WuerstchenCombinedPipeline,
WuerstchenDecoderPipeline,
Wue... | diffusers-main | scripts/convert_wuerstchen.py |
import argparse
import tempfile
import torch
from accelerate import load_checkpoint_and_dispatch
from diffusers.models.prior_transformer import PriorTransformer
from diffusers.pipelines.shap_e import ShapERenderer
"""
Example - From the diffusers root directory:
Download weights:
```sh
$ wget "https://openaipubli... | diffusers-main | scripts/convert_shap_e_to_diffusers.py |
import argparse
import sys
import tensorrt as trt
def convert_models(onnx_path: str, num_controlnet: int, output_path: str, fp16: bool = False, sd_xl: bool = False):
"""
Function to convert models in stable diffusion controlnet pipeline into TensorRT format
Example:
python convert_stable_diffusion_c... | diffusers-main | scripts/convert_stable_diffusion_controlnet_to_tensorrt.py |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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... | diffusers-main | scripts/convert_original_t2i_adapter.py |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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... | diffusers-main | scripts/convert_ms_text_to_video_to_diffusers.py |
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--dump_path", default=None, type=str, required=True, help="Path to... | diffusers-main | scripts/convert_unclip_txt2img_to_image_variation.py |
diffusers-main | scripts/__init__.py | |
import argparse
import safetensors.torch
from diffusers import AutoencoderTiny
"""
Example - From the diffusers root directory:
Download the weights:
```sh
$ wget -q https://huggingface.co/madebyollin/taesd/resolve/main/taesd_encoder.safetensors
$ wget -q https://huggingface.co/madebyollin/taesd/resolve/main/taesd... | diffusers-main | scripts/convert_tiny_autoencoder_to_diffusers.py |
import argparse
import json
import torch
from diffusers import AutoencoderKL, DDPMPipeline, DDPMScheduler, UNet2DModel, VQModel
def shave_segments(path, n_shave_prefix_segments=1):
"""
Removes segments. Positive values shave the first segments, negative shave the last segments.
"""
if n_shave_prefix... | diffusers-main | scripts/convert_ddpm_original_checkpoint_to_diffusers.py |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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... | diffusers-main | scripts/convert_ldm_original_checkpoint_to_diffusers.py |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# 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 applicabl... | diffusers-main | scripts/convert_stable_diffusion_checkpoint_to_onnx.py |
import argparse
import inspect
import os
import numpy as np
import torch
from torch.nn import functional as F
from transformers import CLIPConfig, CLIPImageProcessor, CLIPVisionModelWithProjection, T5EncoderModel, T5Tokenizer
from diffusers import DDPMScheduler, IFPipeline, IFSuperResolutionPipeline, UNet2DConditionM... | diffusers-main | scripts/convert_if.py |
import argparse
import os
import shutil
from pathlib import Path
import onnx
import onnx_graphsurgeon as gs
import torch
from onnx import shape_inference
from packaging import version
from polygraphy.backend.onnx.loader import fold_constants
from torch.onnx import export
from diffusers import (
ControlNetModel,
... | diffusers-main | scripts/convert_stable_diffusion_controlnet_to_onnx.py |
import argparse
import tempfile
import torch
from accelerate import load_checkpoint_and_dispatch
from transformers import CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import UnCLIPPipeline, UNet2DConditionModel, UNet2DModel
from diffusers.models.prior_transformer import PriorTransformer
from diffusers.pi... | diffusers-main | scripts/convert_kakao_brain_unclip_to_diffusers.py |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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... | diffusers-main | scripts/convert_original_audioldm_to_diffusers.py |
"""
This script requires you to build `LAVIS` from source, since the pip version doesn't have BLIP Diffusion. Follow instructions here: https://github.com/salesforce/LAVIS/tree/main.
"""
import argparse
import os
import tempfile
import torch
from lavis.models import load_model_and_preprocess
from transformers import ... | diffusers-main | scripts/convert_blipdiffusion_to_diffusers.py |
import argparse
import re
import torch
from transformers import (
CLIPProcessor,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionModelWithProjection,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionGLIGENPipeline,
StableDiffusionGLIGENTextImagePipeline,
UNet2DConditi... | diffusers-main | scripts/convert_gligen_to_diffusers.py |
import json
import os
import torch
from diffusers import UNet1DModel
os.makedirs("hub/hopper-medium-v2/unet/hor32", exist_ok=True)
os.makedirs("hub/hopper-medium-v2/unet/hor128", exist_ok=True)
os.makedirs("hub/hopper-medium-v2/value_function", exist_ok=True)
def unet(hor):
if hor == 128:
down_block_... | diffusers-main | scripts/convert_models_diffuser_to_diffusers.py |
# Script for converting a HF Diffusers saved pipeline to a Stable Diffusion checkpoint.
# *Only* converts the UNet, VAE, and Text Encoder.
# Does not convert optimizer state or any other thing.
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# ========... | diffusers-main | scripts/convert_diffusers_to_original_sdxl.py |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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... | diffusers-main | scripts/convert_ncsnpp_original_checkpoint_to_diffusers.py |
# Convert the original UniDiffuser checkpoints into diffusers equivalents.
import argparse
from argparse import Namespace
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
GPT2Tokenizer... | diffusers-main | scripts/convert_unidiffuser_to_diffusers.py |
"""
This script modified from
https://github.com/huggingface/diffusers/blob/bc691231360a4cbc7d19a58742ebb8ed0f05e027/scripts/convert_original_stable_diffusion_to_diffusers.py
Convert original Zero1to3 checkpoint to diffusers checkpoint.
# run the convert script
$ python convert_zero123_to_diffusers.py \
--checkpoi... | diffusers-main | scripts/convert_zero123_to_diffusers.py |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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... | diffusers-main | scripts/convert_original_musicldm_to_diffusers.py |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNet2DModel
api = HfApi()
results = {}
# fmt: off
results["google_ddpm_cifar10_32"] = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1.3433, -1.1743, -3.7467,
1.2342, -2.2485, 0.4636, 0.8076, -0.7991, 0.3969, 0.849... | diffusers-main | scripts/generate_logits.py |
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNet2DModel,
)
TEST_UNET_CONFIG = {
"sample_size": 32,
"in_channels": 3,
"out_channels": 3,
"layers_per_block": 2,
"num_class_embeds": 1000,
"block_out_channel... | diffusers-main | scripts/convert_consistency_to_diffusers.py |
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae_attention_paths,
renew_v... | diffusers-main | scripts/convert_vae_pt_to_diffusers.py |
#!/usr/bin/env python3
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnet1D
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNet1DModel
MODELS_MAP = {
"gwf-440k": {
... | diffusers-main | scripts/convert_dance_diffusion_to_diffusers.py |
"""
This script ports models from VQ-diffusion (https://github.com/microsoft/VQ-Diffusion) to diffusers.
It currently only supports porting the ITHQ dataset.
ITHQ dataset:
```sh
# From the root directory of diffusers.
# Download the VQVAE checkpoint
$ wget https://facevcstandard.blob.core.windows.net/v-zhictang/Impr... | diffusers-main | scripts/convert_vq_diffusion_to_diffusers.py |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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... | diffusers-main | scripts/convert_versatile_diffusion_to_diffusers.py |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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... | diffusers-main | scripts/convert_original_stable_diffusion_to_diffusers.py |
import argparse
import huggingface_hub
import k_diffusion as K
import torch
from diffusers import UNet2DConditionModel
UPSCALER_REPO = "pcuenq/k-upscaler"
def resnet_to_diffusers_checkpoint(resnet, checkpoint, *, diffusers_resnet_prefix, resnet_prefix):
rv = {
# norm1
f"{diffusers_resnet_prefi... | diffusers-main | scripts/convert_k_upscaler_to_diffusers.py |
# coding=utf-8
# Copyright 2023, Haofan Wang, Qixun Wang, All rights reserved.
#
# 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 re... | diffusers-main | scripts/convert_lora_safetensor_to_diffusers.py |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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... | diffusers-main | scripts/change_naming_configs_and_checkpoints.py |
import argparse
import os
import tempfile
import torch
from accelerate import load_checkpoint_and_dispatch
from diffusers import UNet2DConditionModel
from diffusers.models.prior_transformer import PriorTransformer
from diffusers.models.vq_model import VQModel
"""
Example - From the diffusers root directory:
Downlo... | diffusers-main | scripts/convert_kandinsky_to_diffusers.py |
#!/usr/bin/env python3
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from t5x import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from diffusers.pipelines.spectrogr... | diffusers-main | scripts/convert_music_spectrogram_to_diffusers.py |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# 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.a... | diffusers-main | src/diffusers/configuration_utils.py |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# 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 applicabl... | diffusers-main | src/diffusers/image_processor.py |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# 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 applicabl... | diffusers-main | src/diffusers/dependency_versions_check.py |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# 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 applicabl... | diffusers-main | src/diffusers/loaders.py |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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... | diffusers-main | src/diffusers/optimization.py |
__version__ = "0.22.0.dev0"
from typing import TYPE_CHECKING
from .utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_k_diffusion_available,
is_librosa_available,
is_note_seq_available,
is_onnx_available,
is_scipy_available,
... | diffusers-main | src/diffusers/__init__.py |
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def set_seed(seed: int):
"""
Args:
Helper function for rep... | diffusers-main | src/diffusers/training_utils.py |
# THIS FILE HAS BEEN AUTOGENERATED. To update:
# 1. modify the `_deps` dict in setup.py
# 2. run `make deps_table_update``
deps = {
"Pillow": "Pillow",
"accelerate": "accelerate>=0.11.0",
"compel": "compel==0.1.8",
"black": "black~=23.1",
"datasets": "datasets",
"filelock": "filelock",
"flax... | diffusers-main | src/diffusers/dependency_versions_table.py |
from .rl import ValueGuidedRLPipeline
| diffusers-main | src/diffusers/experimental/__init__.py |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# 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 applicabl... | diffusers-main | src/diffusers/experimental/rl/value_guided_sampling.py |
from .value_guided_sampling import ValueGuidedRLPipeline
| diffusers-main | src/diffusers/experimental/rl/__init__.py |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# 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.a... | diffusers-main | src/diffusers/pipelines/pipeline_flax_utils.py |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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... | diffusers-main | src/diffusers/pipelines/auto_pipeline.py |
from typing import TYPE_CHECKING
from ..utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
get_objects_from_module,
is_flax_available,
is_k_diffusion_available,
is_librosa_available,
is_note_seq_available,
is_onnx_available,
is_torch_available,
... | diffusers-main | src/diffusers/pipelines/__init__.py |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# 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.a... | diffusers-main | src/diffusers/pipelines/onnx_utils.py |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# 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.a... | diffusers-main | src/diffusers/pipelines/pipeline_utils.py |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# 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 applicabl... | diffusers-main | src/diffusers/pipelines/kandinsky/pipeline_kandinsky_img2img.py |
from typing import TYPE_CHECKING
from ...utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
get_objects_from_module,
is_torch_available,
is_transformers_available,
)
_dummy_objects = {}
_import_structure = {}
try:
if not (is_transformers_available() and is... | diffusers-main | src/diffusers/pipelines/kandinsky/__init__.py |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# 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 applicabl... | diffusers-main | src/diffusers/pipelines/kandinsky/pipeline_kandinsky_prior.py |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# 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 applicabl... | diffusers-main | src/diffusers/pipelines/kandinsky/pipeline_kandinsky_inpaint.py |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# 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 applicabl... | diffusers-main | src/diffusers/pipelines/kandinsky/pipeline_kandinsky.py |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class MCLIPConfig(XLMRobertaConfig):
model_type = "M-CLIP"
def __init__(self, transformerDimSize=1024, imageDimSize=768, **kwargs):
self.transformerDimensions = transformerDimSize
self.numDims = imageDimS... | diffusers-main | src/diffusers/pipelines/kandinsky/text_encoder.py |
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