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# Copyright 2025 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/src/diffusers/models/unets/unet_2d_condition.py/0
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166
# Copyright 2025 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/src/diffusers/modular_pipelines/flux/before_denoise.py/0
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167
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/src/diffusers/modular_pipelines/wan/__init__.py/0
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168
# coding=utf-8 # Copyright 2025 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/src/diffusers/pipelines/auto_pipeline.py/0
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169
from typing import TYPE_CHECKING from ...utils import ( DIFFUSERS_SLOW_IMPORT, OptionalDependencyNotAvailable, _LazyModule, get_objects_from_module, is_flax_available, is_torch_available, is_transformers_available, ) _dummy_objects = {} _import_structure = {} try: if not (is_transfor...
diffusers/src/diffusers/pipelines/controlnet/__init__.py/0
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170
# Copyright 2025 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/src/diffusers/pipelines/ddpm/pipeline_ddpm.py/0
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171
# Copyright 2022 The Music Spectrogram Diffusion Authors. # Copyright 2025 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...
diffusers/src/diffusers/pipelines/deprecated/spectrogram_diffusion/midi_utils.py/0
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172
# Copyright 2025 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/src/diffusers/pipelines/deprecated/versatile_diffusion/pipeline_versatile_diffusion_image_variation.py/0
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173
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 i...
diffusers/src/diffusers/pipelines/hunyuan_video/__init__.py/0
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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/src/diffusers/pipelines/kandinsky/text_encoder.py/0
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175
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 i...
diffusers/src/diffusers/pipelines/ltx/__init__.py/0
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176
# Copyright 2025 PixArt-Sigma 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 # # Unl...
diffusers/src/diffusers/pipelines/sana/pipeline_sana.py/0
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177
# Copyright 2025 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/src/diffusers/pipelines/stable_diffusion_k_diffusion/pipeline_stable_diffusion_k_diffusion.py/0
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178
from typing import TYPE_CHECKING from ...utils import ( DIFFUSERS_SLOW_IMPORT, OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_transformers_available, is_transformers_version, ) _dummy_objects = {} _import_structure = {} try: if not (is_transformers_available() and is...
diffusers/src/diffusers/pipelines/unclip/__init__.py/0
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179
# Copyright 2025 The Wan Team 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 requ...
diffusers/src/diffusers/pipelines/wan/pipeline_wan_vace.py/0
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180
# Copyright 2025 The HuggingFace Inc. 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 appl...
diffusers/src/diffusers/quantizers/bitsandbytes/utils.py/0
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181
import math from dataclasses import dataclass from typing import List, Optional, Tuple, Union import torch from ..configuration_utils import ConfigMixin, register_to_config from ..utils import BaseOutput from .scheduling_utils import SchedulerMixin def gumbel_noise(t, generator=None): device = generator.device ...
diffusers/src/diffusers/schedulers/scheduling_amused.py/0
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182
# Copyright 2025 TSAIL Team 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 requir...
diffusers/src/diffusers/schedulers/scheduling_dpmsolver_multistep_flax.py/0
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183
# Copyright 2025 NVIDIA 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 required b...
diffusers/src/diffusers/schedulers/scheduling_karras_ve_flax.py/0
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184
# Copyright 2025 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/src/diffusers/schedulers/scheduling_vq_diffusion.py/0
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185
# This file is autogenerated by the command `make fix-copies`, do not edit. from ..utils import DummyObject, requires_backends class LMSDiscreteScheduler(metaclass=DummyObject): _backends = ["torch", "scipy"] def __init__(self, *args, **kwargs): requires_backends(self, ["torch", "scipy"]) @class...
diffusers/src/diffusers/utils/dummy_torch_and_scipy_objects.py/0
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186
# Copyright 2025 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/src/diffusers/utils/outputs.py/0
{ "file_path": "diffusers/src/diffusers/utils/outputs.py", "repo_id": "diffusers", "token_count": 2081 }
187
# Copyright 2025 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 agreed to in writ...
diffusers/tests/hooks/test_group_offloading.py/0
{ "file_path": "diffusers/tests/hooks/test_group_offloading.py", "repo_id": "diffusers", "token_count": 6609 }
188
# Copyright 2025 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 agreed to in writ...
diffusers/tests/lora/test_lora_layers_wanvace.py/0
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189
# coding=utf-8 # Copyright 2025 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 ag...
diffusers/tests/models/autoencoders/test_models_autoencoder_wan.py/0
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190
# coding=utf-8 # Copyright 2025 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 ag...
diffusers/tests/models/transformers/test_models_transformer_aura_flow.py/0
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191
# coding=utf-8 # Copyright 2025 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 ag...
diffusers/tests/models/transformers/test_models_transformer_lumina.py/0
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192
# coding=utf-8 # Copyright 2025 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 ag...
diffusers/tests/models/unets/test_models_unet_controlnetxs.py/0
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193
# coding=utf-8 # Copyright 2025 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 ag...
diffusers/tests/others/test_image_processor.py/0
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194
# coding=utf-8 # Copyright 2025 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 ag...
diffusers/tests/pipelines/audioldm2/test_audioldm2.py/0
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import random import unittest import numpy as np import torch # torch_device, # {{ edit_1 }} Removed unused import from transformers import ( AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel, ) from diffusers import ( AutoencoderKL, FlowMatchEulerDiscreteSchedu...
diffusers/tests/pipelines/controlnet_flux/test_controlnet_flux_inpaint.py/0
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196
import tempfile import numpy as np import torch from transformers import AutoTokenizer, T5EncoderModel from diffusers import DDPMScheduler, UNet2DConditionModel from diffusers.models.attention_processor import AttnAddedKVProcessor from diffusers.pipelines.deepfloyd_if import IFWatermarker from diffusers.utils.testing...
diffusers/tests/pipelines/deepfloyd_if/__init__.py/0
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197
# coding=utf-8 # Copyright 2025 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 ag...
diffusers/tests/pipelines/kandinsky3/test_kandinsky3.py/0
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198
import gc import unittest import numpy as np import torch from transformers import AutoTokenizer from diffusers import AutoencoderKL, FlowMatchEulerDiscreteScheduler, OmniGenPipeline, OmniGenTransformer2DModel from diffusers.utils.testing_utils import ( Expectations, backend_empty_cache, numpy_cosine_simi...
diffusers/tests/pipelines/omnigen/test_pipeline_omnigen.py/0
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199
# Copyright 2025 The HuggingFace 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 law or agreed to in...
diffusers/tests/pipelines/sana/test_sana.py/0
{ "file_path": "diffusers/tests/pipelines/sana/test_sana.py", "repo_id": "diffusers", "token_count": 6414 }
200
# coding=utf-8 # Copyright 2025 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 ag...
diffusers/tests/pipelines/stable_cascade/test_stable_cascade_combined.py/0
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# coding=utf-8 # Copyright 2025 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 ag...
diffusers/tests/pipelines/stable_diffusion_2/test_stable_diffusion_flax_inpaint.py/0
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# coding=utf-8 # Copyright 2025 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 ag...
diffusers/tests/pipelines/stable_diffusion_xl/test_stable_diffusion_xl_img2img.py/0
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import random import tempfile import unittest import numpy as np import torch from PIL import Image from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel import diffusers from diffusers import AutoencoderKL, FlowMatchEulerDiscreteScheduler, FluxTransformer2DModel, Visual...
diffusers/tests/pipelines/visualcloze/test_pipeline_visualcloze_combined.py/0
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import torch from diffusers import DDPMScheduler from .test_schedulers import SchedulerCommonTest class DDPMSchedulerTest(SchedulerCommonTest): scheduler_classes = (DDPMScheduler,) def get_scheduler_config(self, **kwargs): config = { "num_train_timesteps": 1000, "beta_start"...
diffusers/tests/schedulers/test_scheduler_ddpm.py/0
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import tempfile from typing import Dict, List, Tuple import torch from diffusers import LCMScheduler from diffusers.utils.testing_utils import torch_device from .test_schedulers import SchedulerCommonTest class LCMSchedulerTest(SchedulerCommonTest): scheduler_classes = (LCMScheduler,) forward_default_kwarg...
diffusers/tests/schedulers/test_scheduler_lcm.py/0
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206
# coding=utf-8 # Copyright 2025 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 ag...
diffusers/tests/single_file/test_model_motion_adapter_single_file.py/0
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import gc import unittest import torch from diffusers import StableDiffusionXLInstructPix2PixPipeline from diffusers.utils.testing_utils import ( backend_empty_cache, enable_full_determinism, require_torch_accelerator, slow, torch_device, ) enable_full_determinism() @slow @require_torch_accele...
diffusers/tests/single_file/test_stable_diffusion_xl_instruct_pix2pix.py/0
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# Asynchronous Inference With our [SmolVLA](https://huggingface.co/papers/2506.01844) we introduced a new way to run inference on real-world robots, **decoupling action prediction from action execution**. In this tutorial, we'll show how to use asynchronous inference (_async inference_) using a finetuned version of Sm...
lerobot/docs/source/async.mdx/0
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209
# Copyright 2024 The HuggingFace Inc. 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 appl...
lerobot/src/lerobot/configs/train.py/0
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210
# Copyright 2024 The HuggingFace Inc. 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 appl...
lerobot/src/lerobot/datasets/v21/_remove_language_instruction.py/0
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# Copyright 2024 The HuggingFace Inc. 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 appl...
lerobot/src/lerobot/motors/dynamixel/dynamixel.py/0
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#!/usr/bin/env python # Copyright 2024 Columbia Artificial Intelligence, Robotics Lab, # and The HuggingFace Inc. 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 #...
lerobot/src/lerobot/policies/diffusion/modeling_diffusion.py/0
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# !/usr/bin/env python # Copyright 2025 The HuggingFace Inc. 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 # #...
lerobot/src/lerobot/policies/sac/reward_model/configuration_classifier.py/0
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214
from __future__ import annotations from collections.abc import Mapping from dataclasses import dataclass, field from typing import Any import numpy as np import torch from torch import Tensor from lerobot.configs.types import FeatureType, NormalizationMode, PolicyFeature from lerobot.datasets.lerobot_dataset import ...
lerobot/src/lerobot/processor/normalize_processor.py/0
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#!/usr/bin/env python # Copyright 2025 The HuggingFace Inc. 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 # # ...
lerobot/src/lerobot/scripts/rl/actor.py/0
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# Copyright 2024 The HuggingFace Inc. 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 appl...
lerobot/src/lerobot/teleoperate.py/0
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#!/usr/bin/env python # Copyright 2024 The HuggingFace Inc. 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 # # ...
lerobot/src/lerobot/utils/io_utils.py/0
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#!/usr/bin/env python # Copyright 2024 The HuggingFace Inc. 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 # # ...
lerobot/tests/cameras/test_opencv.py/0
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# Copyright 2024 The HuggingFace Inc. 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 appl...
lerobot/tests/fixtures/dataset_factories.py/0
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#!/usr/bin/env python # Copyright 2024 The HuggingFace Inc. 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 # # ...
lerobot/tests/policies/test_policies.py/0
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#!/usr/bin/env python # Copyright 2025 The HuggingFace Inc. 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 # # ...
lerobot/tests/utils/test_encoding_utils.py/0
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# Model arguments model_name_or_path: Qwen/Qwen2.5-1.5B-Instruct model_revision: main torch_dtype: bfloat16 attn_implementation: flash_attention_2 # Data training arguments dataset_name: open-r1/OpenR1-Math-220k dataset_prompt_column: problem system_prompt: "You are a helpful AI Assistant that provides well-reasoned a...
open-r1/recipes/Qwen2.5-1.5B-Instruct/grpo/config_demo.yaml/0
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import argparse from transformers import AutoConfig from math import gcd def get_tensor_parallel_size(model_name: str, revision: str = None, default_tp: int = 8) -> int: try: config = AutoConfig.from_pretrained(model_name, revision=revision, trust_remote_code=True) num_heads = getattr(config, 'num_...
open-r1/scripts/get_tensor_parallel_size.py/0
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# Piston workers (slurm) We have built a [piston](https://github.com/engineer-man/piston) package to run IOI problems. To launch a fleet of piston workers on a slurm cluster, you can adapt the paths in `launch_piston_workers.sh` and `launch_single_piston.sh` and run: ```bash slurm/piston/launch_piston_workers.sh (num...
open-r1/slurm/piston/README.md/0
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import asyncio import os from io import BytesIO from typing import Literal from async_lru import alru_cache from .piston_client import PistonClient from .utils import batched async def score_single_test_case( client: PistonClient, problem_data: dict, test_input: str, test_output: str, submission...
open-r1/src/open_r1/utils/competitive_programming/cf_scoring.py/0
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# Copyright 2025 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...
open-r1/tests/slow/test_code_reward.py/0
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<!--⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be rendered properly in your Markdown viewer. --> # Fully Sharded Data Parallel [Fully sharded data parallel](https://pytorch.org/docs/stable/fsdp.html) (FSDP) is developed for distributed training ...
peft/docs/source/accelerate/fsdp.md/0
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<!--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 applicable law or agreed...
peft/docs/source/install.md/0
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<!--Copyright 2025 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 applicable law or agreed...
peft/docs/source/package_reference/trainable_tokens.md/0
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# Copyright 2023-present 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 law or...
peft/examples/boft_controlnet/test_controlnet.py/0
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#!/usr/bin/env python # Copyright 2023-present 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 require...
peft/examples/boft_dreambooth/train_dreambooth.py/0
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<jupyter_start><jupyter_code>import torch from datasets import load_dataset from transformers import set_seed, AutoModelForSeq2SeqLM, AutoTokenizer from peft import get_peft_model, MultitaskPromptTuningConfig, TaskType, MultitaskPromptTuningInit set_seed(42) device = torch.accelerator.current_accelerator().type if has...
peft/examples/conditional_generation/multitask_prompt_tuning.ipynb/0
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<jupyter_start><jupyter_text>PEFT with DNA Language Models This notebook demonstrates how to utilize parameter-efficient fine-tuning techniques (PEFT) from the PEFT library to fine-tune a DNA Language Model (DNA-LM). The fine-tuned DNA-LM will be applied to solve a task from the nucleotide benchmark dataset. Parameter-...
peft/examples/dna_language_models/dna_lm.ipynb/0
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<jupyter_start><jupyter_code>import os from PIL import Image import torch from accelerate.logging import get_logger from diffusers import StableDiffusionPipeline from diffusers.utils import check_min_version from peft import PeftModel # Will error if the minimal version of diffusers is not installed. Remove at your...
peft/examples/hra_dreambooth/dreambooth_inference.ipynb/0
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<jupyter_start><jupyter_text>Finetuning Whisper-large-V2 on Colab using PEFT-Lora + BNB INT8 training In this Colab, we present a step-by-step guide on how to fine-tune Whisper for any multilingual ASR dataset using Hugging Face 🤗 Transformers and 🤗 PEFT. Using 🤗 PEFT and `bitsandbytes`, you can train the `whisper-l...
peft/examples/int8_training/peft_bnb_whisper_large_v2_training.ipynb/0
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# RandLora: Full-rank parameter-efficient fine-tuning of large models ## Introduction [RandLora](https://huggingface.co/papers/2502.00987) is a parameter-efficient fine-tuning technique that is similar to LoRA and VeRA but performs full rank updates to improve performance. RandLora can be particulary usefull when ada...
peft/examples/randlora_finetuning/README.md/0
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<jupyter_start><jupyter_text>Using VeRA for sequence classification In this example, we fine-tune Roberta on a sequence classification task using VeRA. Imports<jupyter_code>import torch from torch.optim import AdamW from torch.utils.data import DataLoader from peft import ( get_peft_model, VeraConfig, Peft...
peft/examples/sequence_classification/VeRA.ipynb/0
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# Makefile for running MetaMathQA experiments. # --- Configuration --- PYTHON := python RUN_SCRIPT := run.py EXPERIMENTS_DIR := experiments RESULTS_DIR := results # --- Automatic Experiment and Result Discovery --- # 1. Find all experiment directories by looking for adapter_config.json files. # This gives us a li...
peft/method_comparison/MetaMathQA/Makefile/0
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{ "auto_mapping": null, "base_model_name_or_path": null, "exclude_modules": null, "fan_in_fan_out": false, "feedforward_modules": null, "inference_mode": false, "init_ia3_weights": true, "modules_to_save": null, "peft_type": "IA3", "revision": null, "target_modules": null, "task_type": null }
peft/method_comparison/MetaMathQA/experiments/ia3/llama-3.2-3B-default/adapter_config.json/0
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# Copyright 2025-present 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 law or...
peft/method_comparison/text_generation_benchmark/utils.py/0
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# Copyright 2024-present 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 law or...
peft/src/peft/mapping_func.py/0
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# Copyright 2023-present 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 law or...
peft/src/peft/tuners/adaption_prompt/config.py/0
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# Copyright 2025-present 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 law or...
peft/src/peft/tuners/c3a/config.py/0
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# Copyright 2023-present 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 law or...
peft/src/peft/tuners/ia3/bnb.py/0
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# Copyright 2023-present 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 law or...
peft/src/peft/tuners/lora/variants.py/0
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# Copyright 2024-present 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 law or...
peft/src/peft/tuners/oft/eetq.py/0
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# Copyright 2023-present 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 law or...
peft/src/peft/tuners/prefix_tuning/model.py/0
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# Copyright 2025-present 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 law or...
peft/src/peft/tuners/shira/layer.py/0
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# Copyright 2023-present 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 law or...
peft/tests/test_feature_extraction_models.py/0
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# Copyright 2023-present 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 law or...
peft/tests/test_other.py/0
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#!/usr/bin/env python3 """ Bulk Model Script Runner Run validation or benchmark script in separate process for each model Benchmark all 'vit*' models: python bulk_runner.py --model-list 'vit*' --results-file vit_bench.csv benchmark.py --amp -b 512 Validate all models: python bulk_runner.py --model-list all --resul...
pytorch-image-models/bulk_runner.py/0
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# CSP-DarkNet **CSPDarknet53** is a convolutional neural network and backbone for object detection that uses [DarkNet-53](https://paperswithcode.com/method/darknet-53). It employs a CSPNet strategy to partition the feature map of the base layer into two parts and then merges them through a cross-stage hierarchy. The u...
pytorch-image-models/hfdocs/source/models/csp-darknet.mdx/0
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# PNASNet **Progressive Neural Architecture Search**, or **PNAS**, is a method for learning the structure of convolutional neural networks (CNNs). It uses a sequential model-based optimization (SMBO) strategy, where we search the space of cell structures, starting with simple (shallow) models and progressing to comple...
pytorch-image-models/hfdocs/source/models/pnasnet.mdx/0
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# SSL ResNet **Residual Networks**, or **ResNets**, learn residual functions with reference to the layer inputs, instead of learning unreferenced functions. Instead of hoping each few stacked layers directly fit a desired underlying mapping, residual nets let these layers fit a residual mapping. They stack [residual b...
pytorch-image-models/hfdocs/source/models/ssl-resnet.mdx/0
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# Learning Rate Schedulers This page contains the API reference documentation for learning rate schedulers included in `timm`. ## Schedulers ### Factory functions [[autodoc]] timm.scheduler.scheduler_factory.create_scheduler [[autodoc]] timm.scheduler.scheduler_factory.create_scheduler_v2 ### Scheduler Classes [[...
pytorch-image-models/hfdocs/source/reference/schedulers.mdx/0
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""" AutoAugment, RandAugment, AugMix, and 3-Augment for PyTorch This code implements the searched ImageNet policies with various tweaks and improvements and does not include any of the search code. AA and RA Implementation adapted from: https://github.com/tensorflow/tpu/blob/master/models/official/efficientnet/au...
pytorch-image-models/timm/data/auto_augment.py/0
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from .reader_factory import create_reader from .img_extensions import *
pytorch-image-models/timm/data/readers/__init__.py/0
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""" Transforms Factory Factory methods for building image transforms for use with TIMM (PyTorch Image Models) Hacked together by / Copyright 2019, Ross Wightman """ import math from typing import Optional, Tuple, Union import torch from torchvision import transforms from timm.data.constants import IMAGENET_DEFAULT_M...
pytorch-image-models/timm/data/transforms_factory.py/0
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""" Conv2d w/ Same Padding Hacked together by / Copyright 2020 Ross Wightman """ import torch import torch.nn as nn import torch.nn.functional as F from typing import Tuple, Optional from ._fx import register_notrace_module from .config import is_exportable, is_scriptable from .padding import pad_same, pad_same_arg, ...
pytorch-image-models/timm/layers/conv2d_same.py/0
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""" Global Response Normalization Module Based on the GRN layer presented in `ConvNeXt-V2 - Co-designing and Scaling ConvNets with Masked Autoencoders` - https://arxiv.org/abs/2301.00808 This implementation * works for both NCHW and NHWC tensor layouts * uses affine param names matching existing torch norm layers * s...
pytorch-image-models/timm/layers/grn.py/0
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""" Padding Helpers Hacked together by / Copyright 2020 Ross Wightman """ import math from typing import List, Tuple, Union import torch import torch.nn.functional as F from .helpers import to_2tuple # Calculate symmetric padding for a convolution def get_padding(kernel_size: int, stride: int = 1, dilation: int = ...
pytorch-image-models/timm/layers/padding.py/0
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try: from torch import _assert except ImportError: def _assert(condition: bool, message: str): assert condition, message def _float_to_int(x: float) -> int: """ Symbolic tracing helper to substitute for inbuilt `int`. Hint: Inbuilt `int` can't accept an argument of type `Proxy` """ ...
pytorch-image-models/timm/layers/trace_utils.py/0
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import hashlib import json import logging import os from functools import partial from pathlib import Path from tempfile import TemporaryDirectory from typing import Any, Dict, Iterable, List, Optional, Tuple, Union import torch from torch.hub import HASH_REGEX, download_url_to_file, urlparse try: from torch.hub ...
pytorch-image-models/timm/models/_hub.py/0
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""" ConvMixer """ from typing import Optional import torch import torch.nn as nn from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD from timm.layers import SelectAdaptivePool2d from ._registry import register_model, generate_default_cfgs from ._builder import build_model_with_cfg from ._manipulate imp...
pytorch-image-models/timm/models/convmixer.py/0
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