python_code stringlengths 0 290k | repo_name stringclasses 30
values | file_path stringlengths 6 125 |
|---|---|---|
# coding=utf-8
# Copyright 2022 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-ft-main | utils/check_dummies.py |
# coding=utf-8
# Copyright 2022 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-ft-main | utils/check_config_docstrings.py |
# coding=utf-8
# Copyright 2020 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-ft-main | utils/check_inits.py |
# coding=utf-8
# Copyright 2022 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-ft-main | utils/check_copies.py |
# coding=utf-8
# Copyright 2021 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-ft-main | utils/custom_init_isort.py |
# coding=utf-8
# Copyright 2020 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-ft-main | utils/check_repo.py |
# coding=utf-8
# Copyright 2020 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-ft-main | utils/check_table.py |
# coding=utf-8
# Copyright 2020 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-ft-main | utils/get_modified_files.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-ft-main | examples/conftest.py |
# coding=utf-8
# Copyright 2022 HuggingFace Inc..
#
# 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 a... | diffusers-ft-main | examples/test_examples.py |
import argparse
import inspect
import math
import os
from pathlib import Path
from typing import Optional
import torch
import torch.nn.functional as F
from accelerate import Accelerator
from accelerate.logging import get_logger
from datasets import load_dataset
from diffusers import DDPMPipeline, DDPMScheduler, UNet2... | diffusers-ft-main | examples/unconditional_image_generation/train_unconditional.py |
import argparse
import math
import os
import torch
import torch.nn.functional as F
from accelerate import Accelerator
from accelerate.logging import get_logger
from datasets import load_dataset
from diffusers import DDPMPipeline, DDPMScheduler, UNet2DModel
from diffusers.hub_utils import init_git_repo, push_to_hub
fr... | diffusers-ft-main | examples/unconditional_image_generation/train_unconditional_ort.py |
import argparse
import itertools
import math
import os
import random
from pathlib import Path
from typing import Optional
import numpy as np
import torch
import torch.nn.functional as F
import torch.utils.checkpoint
from torch.utils.data import Dataset
import PIL
from accelerate import Accelerator
from accelerate.log... | diffusers-ft-main | examples/textual_inversion/textual_inversion.py |
import argparse
import logging
import math
import os
import random
from pathlib import Path
from typing import Optional
import numpy as np
import torch
import torch.utils.checkpoint
from torch.utils.data import Dataset
import jax
import jax.numpy as jnp
import optax
import PIL
import transformers
from diffusers impor... | diffusers-ft-main | examples/textual_inversion/textual_inversion_flax.py |
import argparse
import logging
import math
import os
import random
from pathlib import Path
from typing import Iterable, Optional
import numpy as np
import torch
import torch.nn.functional as F
import torch.utils.checkpoint
from accelerate import Accelerator
from accelerate.logging import get_logger
from accelerate.u... | diffusers-ft-main | examples/text_to_image/train_text_to_image.py |
import argparse
import logging
import math
import os
import random
from pathlib import Path
from typing import Optional
import numpy as np
import torch
import torch.utils.checkpoint
import jax
import jax.numpy as jnp
import optax
import transformers
from datasets import load_dataset
from diffusers import (
FlaxAu... | diffusers-ft-main | examples/text_to_image/train_text_to_image_flax.py |
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
"The `inpainting.py` script is outdated. Please use directly `from diffusers import"
" StableDiffusionInpaintPipeline` instead."
)
| diffusers-ft-main | examples/inference/inpainting.py |
import warnings
from diffusers import StableDiffusionImg2ImgPipeline # noqa F401
warnings.warn(
"The `image_to_image.py` script is outdated. Please use directly `from diffusers import"
" StableDiffusionImg2ImgPipeline` instead."
)
| diffusers-ft-main | examples/inference/image_to_image.py |
import argparse
import hashlib
import logging
import math
import os
from pathlib import Path
from typing import Optional
import numpy as np
import torch
import torch.utils.checkpoint
from torch.utils.data import Dataset
import jax
import jax.numpy as jnp
import optax
import transformers
from diffusers import (
Fl... | diffusers-ft-main | examples/dreambooth/train_dreambooth_flax.py |
import argparse
import hashlib
import itertools
import math
import os
from pathlib import Path
from typing import Optional
import torch
import torch.nn.functional as F
import torch.utils.checkpoint
from torch.utils.data import Dataset
from accelerate import Accelerator
from accelerate.logging import get_logger
from a... | diffusers-ft-main | examples/dreambooth/train_dreambooth.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-ft-main | examples/community/sd_text2img_k_diffusion.py |
import inspect
from typing import Callable, List, Optional, Union
import torch
from diffusers.configuration_utils import FrozenDict
from diffusers.models import AutoencoderKL, UNet2DConditionModel
from diffusers.pipeline_utils import DiffusionPipeline
from diffusers.pipelines.stable_diffusion import StableDiffusionPi... | diffusers-ft-main | examples/community/multilingual_stable_diffusion.py |
import inspect
import re
from typing import Callable, List, Optional, Union
import numpy as np
import torch
import PIL
from diffusers.configuration_utils import FrozenDict
from diffusers.models import AutoencoderKL, UNet2DConditionModel
from diffusers.pipeline_utils import DiffusionPipeline
from diffusers.pipelines.s... | diffusers-ft-main | examples/community/lpw_stable_diffusion.py |
import inspect
import os
import random
import re
from dataclasses import dataclass
from typing import Callable, Dict, List, Optional, Union
import torch
from diffusers.configuration_utils import FrozenDict
from diffusers.models import AutoencoderKL, UNet2DConditionModel
from diffusers.pipeline_utils import DiffusionP... | diffusers-ft-main | examples/community/wildcard_stable_diffusion.py |
import inspect
from typing import Callable, List, Optional, Union
import torch
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
UNet2DConditionModel,
)
from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion import Stable... | diffusers-ft-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-ft-main | examples/community/one_step_unet.py |
from typing import Optional, Tuple, Union
import torch
from diffusers import DDIMScheduler, DDPMScheduler, DiffusionPipeline, UNet2DConditionModel
from diffusers.pipeline_utils import ImagePipelineOutput
from diffusers.schedulers.scheduling_ddim import DDIMSchedulerOutput
from diffusers.schedulers.scheduling_ddpm imp... | diffusers-ft-main | examples/community/bit_diffusion.py |
import inspect
import re
from typing import Callable, List, Optional, Union
import numpy as np
import torch
import PIL
from diffusers.onnx_utils import OnnxRuntimeModel
from diffusers.pipeline_utils import DiffusionPipeline
from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
from diffusers.... | diffusers-ft-main | examples/community/lpw_stable_diffusion_onnx.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 torch
import torch.nn.fun... | diffusers-ft-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 diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
UNet2DConditionModel,
)
from diffusers.pipelines.stable_d... | diffusers-ft-main | examples/community/clip_guided_stable_diffusion.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 diffusers.models import AutoencoderKL, UNet2DCo... | diffusers-ft-main | examples/community/seed_resize_stable_diffusion.py |
from typing import Any, Callable, Dict, List, Optional, Union
import torch
import PIL.Image
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionImg2ImgPipeline,
StableDiffusionInpaintPipelineLegacy,
StableDiffusio... | diffusers-ft-main | examples/community/stable_diffusion_mega.py |
import inspect
from typing import Callable, List, Optional, Tuple, Union
import numpy as np
import torch
import PIL
from diffusers.configuration_utils import FrozenDict
from diffusers.models import AutoencoderKL, UNet2DConditionModel
from diffusers.pipeline_utils import DiffusionPipeline
from diffusers.pipelines.stab... | diffusers-ft-main | examples/community/img2img_inpainting.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
import warnings
from typing import List, Optional, Union
import torch
from diffusers.models import AutoencoderKL, UN... | diffusers-ft-main | examples/community/composable_stable_diffusion.py |
import inspect
import time
from pathlib import Path
from typing import Callable, List, Optional, Union
import numpy as np
import torch
from diffusers.configuration_utils import FrozenDict
from diffusers.models import AutoencoderKL, UNet2DConditionModel
from diffusers.pipeline_utils import DiffusionPipeline
from diffu... | diffusers-ft-main | examples/community/interpolate_stable_diffusion.py |
from typing import Callable, List, Optional, Union
import torch
import PIL
from diffusers.configuration_utils import FrozenDict
from diffusers.models import AutoencoderKL, UNet2DConditionModel
from diffusers.pipeline_utils import DiffusionPipeline
from diffusers.pipelines.stable_diffusion import StableDiffusionInpain... | diffusers-ft-main | examples/community/text_inpainting.py |
import d4rl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
config = dict(
n_samples=64,
horizon=32,
num_inference_steps=20,
n_guide_steps=2,
scale_grad_by_std=True,
scale=0.1,
eta=0.0,
t_grad_cutoff=2,
device="cpu",
)
if __name__ == "__mai... | diffusers-ft-main | examples/rl/run_diffuser_locomotion.py |
import d4rl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
config = dict(
n_samples=64,
horizon=32,
num_inference_steps=20,
n_guide_steps=0,
scale_grad_by_std=True,
scale=0.1,
eta=0.0,
t_grad_cutoff=2,
device="cpu",
)
if __name__ == "__mai... | diffusers-ft-main | examples/rl/run_diffuser_gen_trajectories.py |
import argparse
import torch
import OmegaConf
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-ft-main | scripts/conversion_ldm_uncond.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 torch
# =================#
# UNet Conversion #
# =================#
unet_con... | diffusers-ft-main | scripts/convert_diffusers_to_original_stable_diffusion.py |
diffusers-ft-main | scripts/__init__.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-ft-main | scripts/convert_ddpm_original_checkpoint_to_diffusers.py |
# coding=utf-8
# Copyright 2022 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-ft-main | scripts/convert_ldm_original_checkpoint_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-ft-main | scripts/convert_stable_diffusion_checkpoint_to_onnx.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-ft-main | scripts/convert_models_diffuser_to_diffusers.py |
# coding=utf-8
# Copyright 2022 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-ft-main | scripts/convert_ncsnpp_original_checkpoint_to_diffusers.py |
import random
import torch
from diffusers import UNet2DModel
from huggingface_hub import HfApi
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-ft-main | scripts/generate_logits.py |
#!/usr/bin/env python3
import argparse
import math
import os
from copy import deepcopy
import torch
from torch import nn
from audio_diffusion.models import DiffusionAttnUnet1D
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNet1DModel
from diffusion import sampling
MODELS_MAP = {
"gwf-440k": {
... | diffusers-ft-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-ft-main | scripts/convert_vq_diffusion_to_diffusers.py |
# coding=utf-8
# Copyright 2022 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-ft-main | scripts/convert_versatile_diffusion_to_diffusers.py |
# coding=utf-8
# Copyright 2022 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-ft-main | scripts/convert_original_stable_diffusion_to_diffusers.py |
# coding=utf-8
# Copyright 2022 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-ft-main | scripts/change_naming_configs_and_checkpoints.py |
# coding=utf-8
# Copyright 2022 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-ft-main | src/diffusers/configuration_utils.py |
# coding=utf-8
# Copyright 2022 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-ft-main | src/diffusers/pipeline_flax_utils.py |
# coding=utf-8
# Copyright 2022 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-ft-main | src/diffusers/modeling_flax_utils.py |
# coding=utf-8
# Copyright 2022 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-ft-main | src/diffusers/modeling_flax_pytorch_utils.py |
# Copyright 2020 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-ft-main | src/diffusers/dependency_versions_check.py |
# coding=utf-8
# Copyright 2022 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-ft-main | src/diffusers/optimization.py |
from .utils import (
is_flax_available,
is_inflect_available,
is_onnx_available,
is_scipy_available,
is_torch_available,
is_transformers_available,
is_unidecode_available,
)
__version__ = "0.9.0"
from .configuration_utils import ConfigMixin
from .onnx_utils import OnnxRuntimeModel
from .u... | diffusers-ft-main | src/diffusers/__init__.py |
# coding=utf-8
# Copyright 2022 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-ft-main | src/diffusers/hub_utils.py |
import copy
import os
import random
import numpy as np
import torch
def enable_full_determinism(seed: int):
"""
Helper function for reproducible behavior during distributed training. See
- https://pytorch.org/docs/stable/notes/randomness.html for pytorch
"""
# set seed first
set_seed(seed)
... | diffusers-ft-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",
"black": "black==22.8",
"datasets": "datasets",
"filelock": "filelock",
"flake8": "flake8>=3.8.3",
"flax... | diffusers-ft-main | src/diffusers/dependency_versions_table.py |
# coding=utf-8
# Copyright 2022 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-ft-main | src/diffusers/modeling_utils.py |
# coding=utf-8
# Copyright 2022 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-ft-main | src/diffusers/dynamic_modules_utils.py |
# coding=utf-8
# Copyright 2022 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-ft-main | src/diffusers/onnx_utils.py |
# coding=utf-8
# Copyright 2022 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-ft-main | src/diffusers/pipeline_utils.py |
from .rl import ValueGuidedRLPipeline
| diffusers-ft-main | src/diffusers/experimental/__init__.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-ft-main | src/diffusers/experimental/rl/value_guided_sampling.py |
from .value_guided_sampling import ValueGuidedRLPipeline
| diffusers-ft-main | src/diffusers/experimental/rl/__init__.py |
from ..utils import is_flax_available, is_onnx_available, is_torch_available, is_transformers_available
if is_torch_available():
from .dance_diffusion import DanceDiffusionPipeline
from .ddim import DDIMPipeline
from .ddpm import DDPMPipeline
from .latent_diffusion import LDMSuperResolutionPipeline
... | diffusers-ft-main | src/diffusers/pipelines/__init__.py |
from .pipeline_repaint import RePaintPipeline
| diffusers-ft-main | src/diffusers/pipelines/repaint/__init__.py |
# Copyright 2022 ETH Zurich Computer Vision Lab 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... | diffusers-ft-main | src/diffusers/pipelines/repaint/pipeline_repaint.py |
# flake8: noqa
from .pipeline_stochastic_karras_ve import KarrasVePipeline
| diffusers-ft-main | src/diffusers/pipelines/stochastic_karras_ve/__init__.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-ft-main | src/diffusers/pipelines/stochastic_karras_ve/pipeline_stochastic_karras_ve.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-ft-main | src/diffusers/pipelines/ddim/pipeline_ddim.py |
# flake8: noqa
from .pipeline_ddim import DDIMPipeline
| diffusers-ft-main | src/diffusers/pipelines/ddim/__init__.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-ft-main | src/diffusers/pipelines/alt_diffusion/pipeline_alt_diffusion_img2img.py |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
# Copied from diffusers.pipelines.stable_diffusion.__init__.StableDiffusionPipelineOutput with Sta... | diffusers-ft-main | src/diffusers/pipelines/alt_diffusion/__init__.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-ft-main | src/diffusers/pipelines/alt_diffusion/pipeline_alt_diffusion.py |
from dataclasses import dataclass
from typing import Optional, Tuple
import torch
from torch import nn
from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel
from transformers.utils import ModelOutput
@dataclass
class TransformationModelOutput(ModelOutput):
"""
Base class for tex... | diffusers-ft-main | src/diffusers/pipelines/alt_diffusion/modeling_roberta_series.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-ft-main | src/diffusers/pipelines/latent_diffusion_uncond/pipeline_latent_diffusion_uncond.py |
# flake8: noqa
from .pipeline_latent_diffusion_uncond import LDMPipeline
| diffusers-ft-main | src/diffusers/pipelines/latent_diffusion_uncond/__init__.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-ft-main | src/diffusers/pipelines/stable_diffusion_safe/safety_checker.py |
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class SafetyConfig(object):
WEAK = {
"sld_warmup_steps": 15,
... | diffusers-ft-main | src/diffusers/pipelines/stable_diffusion_safe/__init__.py |
import inspect
import warnings
from typing import Callable, List, Optional, Union
import numpy as np
import torch
from packaging import version
from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
from ...configuration_utils import FrozenDict
from ...models import AutoencoderKL, UNet2DConditio... | diffusers-ft-main | src/diffusers/pipelines/stable_diffusion_safe/pipeline_stable_diffusion_safe.py |
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| diffusers-ft-main | src/diffusers/pipelines/vq_diffusion/__init__.py |
# Copyright 2022 Microsoft 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 require... | diffusers-ft-main | src/diffusers/pipelines/vq_diffusion/pipeline_vq_diffusion.py |
import inspect
from typing import Optional, Tuple, Union
import numpy as np
import torch
import torch.utils.checkpoint
import PIL
from ...models import UNet2DModel, VQModel
from ...pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepSchedu... | diffusers-ft-main | src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py |
# flake8: noqa
from ...utils import is_transformers_available
from .pipeline_latent_diffusion_superresolution import LDMSuperResolutionPipeline
if is_transformers_available():
from .pipeline_latent_diffusion import LDMBertModel, LDMTextToImagePipeline
| diffusers-ft-main | src/diffusers/pipelines/latent_diffusion/__init__.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-ft-main | src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion.py |
# flake8: noqa
from .pipeline_dance_diffusion import DanceDiffusionPipeline
| diffusers-ft-main | src/diffusers/pipelines/dance_diffusion/__init__.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-ft-main | src/diffusers/pipelines/dance_diffusion/pipeline_dance_diffusion.py |
# flake8: noqa
from .pipeline_score_sde_ve import ScoreSdeVePipeline
| diffusers-ft-main | src/diffusers/pipelines/score_sde_ve/__init__.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-ft-main | src/diffusers/pipelines/score_sde_ve/pipeline_score_sde_ve.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-ft-main | src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_image_variation.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-ft-main | src/diffusers/pipelines/stable_diffusion/pipeline_flax_stable_diffusion.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-ft-main | src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion.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-ft-main | src/diffusers/pipelines/stable_diffusion/pipeline_cycle_diffusion.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-ft-main | src/diffusers/pipelines/stable_diffusion/safety_checker_flax.py |
import inspect
from typing import Callable, List, Optional, Union
import numpy as np
import torch
import PIL
from transformers import CLIPFeatureExtractor, CLIPTokenizer
from ...configuration_utils import FrozenDict
from ...onnx_utils import OnnxRuntimeModel
from ...pipeline_utils import DiffusionPipeline
from ...sc... | diffusers-ft-main | src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion_inpaint_legacy.py |
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