repo stringclasses 454
values | file_path stringlengths 5 201 | extension stringclasses 1
value | content stringlengths 8 509k | num_lines int64 3 16.9k | size_bytes int64 8 511k |
|---|---|---|---|---|---|
pytorch-image-models | timm/models/rdnet.py | .py | """
RDNet
Copyright (c) 2024-present NAVER Cloud Corp.
Apache-2.0
"""
from functools import partial
from typing import List, Optional, Tuple, Union, Callable, Type
import torch
import torch.nn as nn
from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
from timm.layers import DropPath, calculate_drop_pat... | 562 | 21,049 |
pytorch-image-models | timm/models/nest.py | .py | """ Nested Transformer (NesT) in PyTorch
A PyTorch implement of Aggregating Nested Transformers as described in:
'Aggregating Nested Transformers'
- https://arxiv.org/abs/2105.12723
The official Jax code is released and available at https://github.com/google-research/nested-transformer. The weights
have been con... | 699 | 25,818 |
pytorch-image-models | timm/models/registry.py | .py | from ._registry import *
import warnings
warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.models", FutureWarning)
| 5 | 146 |
pytorch-image-models | timm/models/levit.py | .py | """ LeViT
Paper: `LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference`
- https://arxiv.org/abs/2104.01136
@article{graham2021levit,
title={LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference},
author={Benjamin Graham and Alaaeldin El-Nouby and Hugo Touvron and Pierre Stoc... | 1,153 | 40,984 |
pytorch-image-models | timm/models/pit.py | .py | """ Pooling-based Vision Transformer (PiT) in PyTorch
A PyTorch implement of Pooling-based Vision Transformers as described in
'Rethinking Spatial Dimensions of Vision Transformers' - https://arxiv.org/abs/2103.16302
This code was adapted from the original version at https://github.com/naver-ai/pit, original copyrigh... | 556 | 18,607 |
pytorch-image-models | timm/models/hardcorenas.py | .py | from functools import partial
import torch.nn as nn
from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
from ._builder import build_model_with_cfg
from ._builder import pretrained_cfg_for_features
from ._efficientnet_blocks import SqueezeExcite
from ._efficientnet_builder import decode_arch_def, resolve... | 158 | 7,730 |
pytorch-image-models | timm/models/inception_resnet_v2.py | .py | """ Pytorch Inception-Resnet-V2 implementation
Sourced from https://github.com/Cadene/tensorflow-model-zoo.torch (MIT License) which is
based upon Google's Tensorflow implementation and pretrained weights (Apache 2.0 License)
"""
from functools import partial
from typing import Type, Optional
import torch
import torch.... | 392 | 13,666 |
pytorch-image-models | timm/models/tresnet.py | .py | """
TResNet: High Performance GPU-Dedicated Architecture
https://arxiv.org/pdf/2003.13630.pdf
Original model: https://github.com/mrT23/TResNet
"""
from collections import OrderedDict
from functools import partial
from typing import List, Optional, Tuple, Union, Type
import torch
import torch.nn as nn
from timm.laye... | 448 | 16,224 |
pytorch-image-models | timm/models/inception_v4.py | .py | """ Pytorch Inception-V4 implementation
Sourced from https://github.com/Cadene/tensorflow-model-zoo.torch (MIT License) which is
based upon Google's Tensorflow implementation and pretrained weights (Apache 2.0 License)
"""
from functools import partial
from typing import List, Optional, Tuple, Union, Type
import torch... | 446 | 15,270 |
pytorch-image-models | timm/models/cspnet.py | .py | """PyTorch CspNet
A PyTorch implementation of Cross Stage Partial Networks including:
* CSPResNet50
* CSPResNeXt50
* CSPDarkNet53
* and DarkNet53 for good measure
Based on paper `CSPNet: A New Backbone that can Enhance Learning Capability of CNN` - https://arxiv.org/abs/1911.11929
Reference impl via darknet cfg file... | 1,209 | 43,210 |
pytorch-image-models | timm/models/coat.py | .py | """
CoaT architecture.
Paper: Co-Scale Conv-Attentional Image Transformers - https://arxiv.org/abs/2104.06399
Official CoaT code at: https://github.com/mlpc-ucsd/CoaT
Modified from timm/models/vision_transformer.py
"""
from typing import List, Optional, Tuple, Union, Type, Any
import torch
import torch.nn as nn
imp... | 845 | 31,742 |
pytorch-image-models | timm/models/efficientformer_v2.py | .py | """ EfficientFormer-V2
@article{
li2022rethinking,
title={Rethinking Vision Transformers for MobileNet Size and Speed},
author={Li, Yanyu and Hu, Ju and Wen, Yang and Evangelidis, Georgios and Salahi, Kamyar and Wang, Yanzhi and Tulyakov, Sergey and Ren, Jian},
journal={arXiv preprint arXiv:2212.08059}... | 947 | 32,467 |
pytorch-image-models | timm/models/vision_transformer_hybrid.py | .py | """ Hybrid Vision Transformer (ViT) in PyTorch
A PyTorch implement of the Hybrid Vision Transformers as described in:
'An Image Is Worth 16 x 16 Words: Transformers for Image Recognition at Scale'
- https://arxiv.org/abs/2010.11929
`How to train your ViT? Data, Augmentation, and Regularization in Vision Transfor... | 462 | 19,053 |
pytorch-image-models | timm/models/pvt_v2.py | .py | """ Pyramid Vision Transformer v2
@misc{wang2021pvtv2,
title={PVTv2: Improved Baselines with Pyramid Vision Transformer},
author={Wenhai Wang and Enze Xie and Xiang Li and Deng-Ping Fan and Kaitao Song and Ding Liang and
Tong Lu and Ping Luo and Ling Shao},
year={2021},
eprint={2106.137... | 595 | 21,079 |
pytorch-image-models | timm/models/efficientvit_mit.py | .py | """ EfficientViT (by MIT Song Han's Lab)
Paper: `Efficientvit: Enhanced linear attention for high-resolution low-computation visual recognition`
- https://arxiv.org/abs/2205.14756
Adapted from official impl at https://github.com/mit-han-lab/efficientvit
"""
__all__ = ['EfficientVit', 'EfficientVitLarge']
from ty... | 1,282 | 41,978 |
pytorch-image-models | timm/models/cait.py | .py | """ Class-Attention in Image Transformers (CaiT)
Paper: 'Going deeper with Image Transformers' - https://arxiv.org/abs/2103.17239
Original code and weights from https://github.com/facebookresearch/deit, copyright below
Modifications and additions for timm hacked together by / Copyright 2021, Ross Wightman
"""
# Copy... | 633 | 23,170 |
pytorch-image-models | timm/models/_helpers.py | .py | """ Model creation / weight loading / state_dict helpers
Hacked together by / Copyright 2020 Ross Wightman
"""
import argparse
import logging
import os
import pickle
from typing import Any, Callable, Dict, Optional, Union
import torch
try:
import safetensors.torch
_has_safetensors = True
except ImportError:... | 262 | 10,089 |
pytorch-image-models | timm/models/_features.py | .py | """ PyTorch Feature Extraction Helpers
A collection of classes, functions, modules to help extract features from models
and provide a common interface for describing them.
The return_layers, module re-writing idea inspired by torchvision IntermediateLayerGetter
https://github.com/pytorch/vision/blob/d88d8961ae51507d0... | 484 | 19,758 |
pytorch-image-models | timm/models/beit.py | .py | """ BEiT: BERT Pre-Training of Image Transformers (https://arxiv.org/abs/2106.08254)
Model from official source: https://github.com/microsoft/unilm/tree/master/beit
@inproceedings{beit,
title={{BEiT}: {BERT} Pre-Training of Image Transformers},
author={Hangbo Bao and Li Dong and Songhao Piao and Furu Wei},
booktitle=... | 1,063 | 43,081 |
pytorch-image-models | timm/models/repvit.py | .py | """ RepViT
Paper: `RepViT: Revisiting Mobile CNN From ViT Perspective`
- https://arxiv.org/abs/2307.09283
@misc{wang2023repvit,
title={RepViT: Revisiting Mobile CNN From ViT Perspective},
author={Ao Wang and Hui Chen and Zijia Lin and Hengjun Pu and Guiguang Ding},
year={2023},
eprint={230... | 694 | 21,526 |
pytorch-image-models | timm/models/factory.py | .py | from ._factory import *
import warnings
warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.models", FutureWarning)
| 5 | 145 |
pytorch-image-models | timm/models/res2net.py | .py | """ Res2Net and Res2NeXt
Adapted from Official Pytorch impl at: https://github.com/gasvn/Res2Net/
Paper: `Res2Net: A New Multi-scale Backbone Architecture` - https://arxiv.org/abs/1904.01169
"""
import math
from typing import Optional, Type
import torch
import torch.nn as nn
from timm.data import IMAGENET_DEFAULT_MEA... | 241 | 8,165 |
pytorch-image-models | timm/models/maxxvit.py | .py | """ MaxVit and CoAtNet Vision Transformer - CNN Hybrids in PyTorch
This is a from-scratch implementation of both CoAtNet and MaxVit in PyTorch.
99% of the implementation was done from papers, however last minute some adjustments were made
based on the (as yet unfinished?) public code release https://github.com/google... | 2,712 | 101,089 |
pytorch-image-models | timm/models/byobnet.py | .py | """ Bring-Your-Own-Blocks Network
A flexible network w/ dataclass based config for stacking those NN blocks.
This model is currently used to implement the following networks:
GPU Efficient (ResNets) - gernet_l/m/s (original versions called genet, but this was already used (by SENet author)).
Paper: `Neural Architect... | 3,181 | 116,445 |
pytorch-image-models | timm/models/efficientvit_msra.py | .py | """ EfficientViT (by MSRA)
Paper: `EfficientViT: Memory Efficient Vision Transformer with Cascaded Group Attention`
- https://arxiv.org/abs/2305.07027
Adapted from official impl at https://github.com/microsoft/Cream/tree/main/EfficientViT
"""
__all__ = ['EfficientVitMsra']
import itertools
from collections impor... | 827 | 29,281 |
pytorch-image-models | timm/models/csatv2.py | .py | """CSATv2
A frequency-domain vision model using DCT transforms with spatial attention.
Paper: TBD
This model created by members of MLPA Lab. Welcome feedback and suggestion, questions.
gusdlf93@naver.com
juno.demie.oh@gmail.com
Refined for timm by Ross Wightman
"""
import math
import warnings
from functools import ... | 871 | 33,967 |
pytorch-image-models | timm/models/mobilevit.py | .py | """ MobileViT
Paper:
V1: `MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer` - https://arxiv.org/abs/2110.02178
V2: `Separable Self-attention for Mobile Vision Transformers` - https://arxiv.org/abs/2206.02680
MobileVitBlock and checkpoints adapted from https://github.com/apple/ml-cvnets... | 711 | 26,626 |
pytorch-image-models | timm/models/fasternet.py | .py | """FasterNet
Run, Don't Walk: Chasing Higher FLOPS for Faster Neural Networks
- paper: https://arxiv.org/abs/2303.03667
- code: https://github.com/JierunChen/FasterNet
@article{chen2023run,
title={Run, Don't Walk: Chasing Higher FLOPS for Faster Neural Networks},
author={Chen, Jierun and Kao, Shiu-hong and He, Hao... | 507 | 18,998 |
pytorch-image-models | timm/models/features.py | .py | from ._features import *
import warnings
warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.models", FutureWarning)
| 5 | 146 |
pytorch-image-models | timm/models/vision_transformer.py | .py | """ Vision Transformer (ViT) in PyTorch
A PyTorch implement of Vision Transformers as described in:
'An Image Is Worth 16 x 16 Words: Transformers for Image Recognition at Scale'
- https://arxiv.org/abs/2010.11929
`How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers`
- https:... | 4,923 | 211,911 |
pytorch-image-models | timm/models/starnet.py | .py | """
Implementation of Prof-of-Concept Network: StarNet.
We make StarNet as simple as possible [to show the key contribution of element-wise multiplication]:
- like NO layer-scale in network design,
- and NO EMA during training,
- which would improve the performance further.
Created by: Xu Ma (Email: ma.xu... | 363 | 13,637 |
pytorch-image-models | timm/models/metaformer.py | .py | """
Poolformer from MetaFormer is Actually What You Need for Vision https://arxiv.org/abs/2111.11418
IdentityFormer, RandFormer, PoolFormerV2, ConvFormer, and CAFormer
from MetaFormer Baselines for Vision https://arxiv.org/abs/2210.13452
All implemented models support feature extraction and variable input resolution.... | 1,184 | 40,565 |
pytorch-image-models | timm/models/hrnet.py | .py | """ HRNet
Copied from https://github.com/HRNet/HRNet-Image-Classification
Original header:
Copyright (c) Microsoft
Licensed under the MIT License.
Written by Bin Xiao (Bin.Xiao@microsoft.com)
Modified by Ke Sun (sunk@mail.ustc.edu.cn)
"""
import logging
from typing import Dict, List, Type, Optional, Tuple
im... | 1,005 | 34,373 |
pytorch-image-models | timm/models/swin_transformer_v2_cr.py | .py | """ Swin Transformer V2
A PyTorch impl of : `Swin Transformer V2: Scaling Up Capacity and Resolution`
- https://arxiv.org/pdf/2111.09883
Code adapted from https://github.com/ChristophReich1996/Swin-Transformer-V2, original copyright/license info below
This implementation is experimental and subject to change in ... | 1,290 | 51,389 |
pytorch-image-models | timm/models/pnasnet.py | .py | """
pnasnet5large implementation grabbed from Cadene's pretrained models
Additional credit to https://github.com/creafz
https://github.com/Cadene/pretrained-models.pytorch/blob/master/pretrainedmodels/models/pnasnet.py
"""
from collections import OrderedDict
from functools import partial
from typing import Type
i... | 465 | 17,353 |
pytorch-image-models | timm/models/swin_transformer_v2.py | .py | """ Swin Transformer V2
A PyTorch impl of : `Swin Transformer V2: Scaling Up Capacity and Resolution`
- https://arxiv.org/abs/2111.09883
Code/weights from https://github.com/microsoft/Swin-Transformer, original copyright/license info below
Modifications and additions for timm hacked together by / Copyright 2022, ... | 1,320 | 53,039 |
pytorch-image-models | timm/models/convit.py | .py | """ ConViT Model
@article{d2021convit,
title={ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases},
author={d'Ascoli, St{\'e}phane and Touvron, Hugo and Leavitt, Matthew and Morcos, Ari and Biroli, Giulio and Sagun, Levent},
journal={arXiv preprint arXiv:2103.10697},
year={2021}
}
P... | 459 | 16,683 |
pytorch-image-models | timm/models/mlp_mixer.py | .py | """ MLP-Mixer, ResMLP, and gMLP in PyTorch
This impl originally based on MLP-Mixer paper.
Official JAX impl: https://github.com/google-research/vision_transformer/blob/linen/vit_jax/models_mixer.py
Paper: 'MLP-Mixer: An all-MLP Architecture for Vision' - https://arxiv.org/abs/2105.01601
@article{tolstikhin2021,
t... | 881 | 33,749 |
pytorch-image-models | timm/models/vovnet.py | .py | """ VoVNet (V1 & V2)
Papers:
* `An Energy and GPU-Computation Efficient Backbone Network` - https://arxiv.org/abs/1904.09730
* `CenterMask : Real-Time Anchor-Free Instance Segmentation` - https://arxiv.org/abs/1911.06667
Looked at https://github.com/youngwanLEE/vovnet-detectron2 &
https://github.com/stigma0617/VoVNe... | 560 | 18,826 |
pytorch-image-models | timm/models/resnest.py | .py | """ ResNeSt Models
Paper: `ResNeSt: Split-Attention Networks` - https://arxiv.org/abs/2004.08955
Adapted from original PyTorch impl w/ weights at https://github.com/zhanghang1989/ResNeSt by Hang Zhang
Modified for torchscript compat, and consistency with timm by Ross Wightman
"""
from typing import Optional, Type
f... | 279 | 10,479 |
pytorch-image-models | timm/models/fx_features.py | .py | from ._features_fx import *
import warnings
warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.models", FutureWarning)
| 5 | 149 |
pytorch-image-models | timm/models/twins.py | .py | """ Twins
A PyTorch impl of : `Twins: Revisiting the Design of Spatial Attention in Vision Transformers`
- https://arxiv.org/pdf/2104.13840.pdf
Code/weights from https://github.com/Meituan-AutoML/Twins, original copyright/license info below
"""
# --------------------------------------------------------
# Twins
# ... | 631 | 23,769 |
pytorch-image-models | timm/models/sequencer.py | .py | """ Sequencer
Paper: `Sequencer: Deep LSTM for Image Classification` - https://arxiv.org/pdf/2205.01972.pdf
"""
# Copyright (c) 2022. Yuki Tatsunami
# Licensed under the Apache License, Version 2.0 (the "License");
import math
from functools import partial
from itertools import accumulate
from typing import List, ... | 573 | 18,907 |
pytorch-image-models | timm/models/xception_aligned.py | .py | """Pytorch impl of Aligned Xception 41, 65, 71
This is a correct, from scratch impl of Aligned Xception (Deeplab) models compatible with TF weights at
https://github.com/tensorflow/models/blob/master/research/deeplab/g3doc/model_zoo.md
Hacked together by / Copyright 2020 Ross Wightman
"""
from functools import partia... | 484 | 16,407 |
pytorch-image-models | timm/models/vitamin.py | .py | """ ViTamin
Paper: Designing Scalable Vison Models in the Vision-Language Era
A family of model weights on Huggingface: https://huggingface.co/collections/jienengchen/vitamin-family-661048126b72debdaca060bf
@inproceedings{chen2024vitamin,
title={ViTamin: Designing Scalable Vision Models in the Vision-language Era},... | 627 | 21,490 |
pytorch-image-models | timm/models/inception_v3.py | .py | """ Inception-V3
Originally from torchvision Inception3 model
Licensed BSD-Clause 3 https://github.com/pytorch/vision/blob/master/LICENSE
"""
from functools import partial
from typing import Optional, Type
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.data import IMAGENET_DEFAULT_STD, ... | 509 | 18,808 |
pytorch-image-models | timm/models/efficientformer.py | .py | """ EfficientFormer
@article{li2022efficientformer,
title={EfficientFormer: Vision Transformers at MobileNet Speed},
author={Li, Yanyu and Yuan, Geng and Wen, Yang and Hu, Eric and Evangelidis, Georgios and Tulyakov,
Sergey and Wang, Yanzhi and Ren, Jian},
journal={arXiv preprint arXiv:2206.01191},
year={20... | 687 | 23,607 |
pytorch-image-models | timm/models/inception_next.py | .py | """
InceptionNeXt paper: https://arxiv.org/abs/2303.16900
Original implementation & weights from: https://github.com/sail-sg/inceptionnext
"""
from functools import partial
from typing import List, Optional, Tuple, Union, Type
import torch
import torch.nn as nn
from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_D... | 523 | 18,868 |
pytorch-image-models | timm/models/edgenext.py | .py | """ EdgeNeXt
Paper: `EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision Applications`
- https://arxiv.org/abs/2206.10589
Original code and weights from https://github.com/mmaaz60/EdgeNeXt
Modifications and additions for timm by / Copyright 2022, Ross Wightman
"""
import math
from funct... | 707 | 25,512 |
pytorch-image-models | timm/models/cpubone.py | .py | """CPUBone
CPUBone: Efficient Vision Backbone Design for Devices with Low Parallelization Capabilities
Moritz Nottebaum, Matteo Dunnhofer, Christian Micheloni
Conference on Computer Vision and Pattern Recognition (CVPR) Findings, 2026
Adapted from the original implementation at https://github.com/altair199797/CPUBone... | 1,081 | 41,698 |
pytorch-image-models | timm/models/sknet.py | .py | """ Selective Kernel Networks (ResNet base)
Paper: Selective Kernel Networks (https://arxiv.org/abs/1903.06586)
This was inspired by reading 'Compounding the Performance Improvements...' (https://arxiv.org/abs/2001.06268)
and a streamlined impl at https://github.com/clovaai/assembled-cnn but I ended up building somet... | 270 | 9,771 |
pytorch-image-models | timm/models/tnt.py | .py | """ Transformer in Transformer (TNT) in PyTorch
A PyTorch implement of TNT as described in
'Transformer in Transformer' - https://arxiv.org/abs/2103.00112
The official mindspore code is released and available at
https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/TNT
The official pytorch code is ... | 596 | 22,766 |
pytorch-image-models | timm/models/swiftformer.py | .py | """SwiftFormer
SwiftFormer: Efficient Additive Attention for Transformer-based Real-time Mobile Vision Applications
Code: https://github.com/Amshaker/SwiftFormer
Paper: https://arxiv.org/pdf/2303.15446
@InProceedings{Shaker_2023_ICCV,
author = {Shaker, Abdelrahman and Maaz, Muhammad and Rasheed, Hanoona and Kha... | 650 | 24,050 |
pytorch-image-models | timm/models/_features_fx.py | .py | """ PyTorch FX Based Feature Extraction Helpers
Using https://pytorch.org/vision/stable/feature_extraction.html
"""
from typing import Callable, Dict, List, Optional, Union, Tuple, Type
import torch
from torch import nn
from timm.layers import (
create_feature_extractor,
get_graph_node_names,
register_not... | 101 | 3,279 |
pytorch-image-models | timm/models/_registry.py | .py | """ Model Registry
Hacked together by / Copyright 2020 Ross Wightman
"""
import fnmatch
import re
import sys
import warnings
from collections import defaultdict, deque
from copy import deepcopy
from dataclasses import replace
from typing import Any, Callable, Dict, Iterable, List, Optional, Set, Sequence, Union, Tuple... | 353 | 14,465 |
pytorch-image-models | timm/models/xception.py | .py | """
Ported to pytorch thanks to [tstandley](https://github.com/tstandley/Xception-PyTorch)
@author: tstandley
Adapted by cadene
Creates an Xception Model as defined in:
Francois Chollet
Xception: Deep Learning with Depthwise Separable Convolutions
https://arxiv.org/pdf/1610.02357.pdf
This weights ported from the Ke... | 299 | 9,110 |
pytorch-image-models | timm/models/mobilenetv5.py | .py | from functools import partial
from typing import Callable, Dict, List, Optional, Sequence, Tuple, Union
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.data import IMAGENET_INCEPTION_MEAN, IMAGENET_INCEPTION_STD
from timm.layers import (
SelectAdaptivePool2d,
Linear,
LayerType... | 881 | 33,419 |
pytorch-image-models | timm/models/vgg.py | .py | """VGG
Adapted from https://github.com/pytorch/vision 'vgg.py' (BSD-3-Clause) with a few changes for
timm functionality.
Copyright 2021 Ross Wightman
"""
from typing import Any, Dict, List, Optional, Type, Union, cast
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.data import IMAGENET_... | 427 | 14,626 |
pytorch-image-models | timm/models/efficientnet.py | .py | """ The EfficientNet Family in PyTorch
An implementation of EfficienNet that covers variety of related models with efficient architectures:
* EfficientNet-V2
- `EfficientNetV2: Smaller Models and Faster Training` - https://arxiv.org/abs/2104.00298
* EfficientNet (B0-B8, L2 + Tensorflow pretrained AutoAug/RandAug/A... | 2,974 | 126,149 |
pytorch-image-models | timm/models/_prune.py | .py | import os
import pkgutil
from copy import deepcopy
from torch import nn as nn
from timm.layers import Conv2dSame, BatchNormAct2d, Linear
__all__ = ['extract_layer', 'set_layer', 'adapt_model_from_string', 'adapt_model_from_file']
def extract_layer(model, layer):
"""Extract a layer from a model using dot-separa... | 177 | 5,810 |
pytorch-image-models | timm/optim/nadam.py | .py | import math
import torch
from torch.optim.optimizer import Optimizer
class NAdamLegacy(Optimizer):
"""Implements Nadam algorithm (a variant of Adam based on Nesterov momentum).
NOTE: This impl has been deprecated in favour of torch.optim.NAdam and remains as a reference
It has been proposed in `Incorpo... | 107 | 4,114 |
pytorch-image-models | timm/optim/_param_groups.py | .py | import fnmatch
import logging
from itertools import islice
from typing import Collection, Optional
from torch import nn as nn
from timm.models import group_parameters
_logger = logging.getLogger(__name__)
def _matches_pattern(name: str, patterns: Collection[str]) -> bool:
"""Check if parameter name matches an... | 195 | 6,824 |
pytorch-image-models | timm/optim/adafactor.py | .py | """ Adafactor Optimizer
Lifted from https://github.com/pytorch/fairseq/blob/master/fairseq/optim/adafactor.py
Modified by Ross Wightman to fix some issues with factorization dims for non nn.Linear layers
Original header/copyright below.
"""
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is l... | 230 | 9,969 |
pytorch-image-models | timm/optim/radam.py | .py | """RAdam Optimizer.
Implementation lifted from: https://github.com/LiyuanLucasLiu/RAdam
Paper: `On the Variance of the Adaptive Learning Rate and Beyond` - https://arxiv.org/abs/1908.03265
NOTE: This impl has been deprecated in favour of torch.optim.RAdam and remains as a reference
"""
import math
import torch
from to... | 106 | 3,843 |
pytorch-image-models | timm/optim/rmsprop_tf.py | .py | """ RMSProp modified to behave like Tensorflow impl
Originally cut & paste from PyTorch RMSProp
https://github.com/pytorch/pytorch/blob/063946d2b3f3f1e953a2a3b54e0b34f1393de295/torch/optim/rmsprop.py
Licensed under BSD-Clause 3 (ish), https://github.com/pytorch/pytorch/blob/master/LICENSE
References for added functio... | 183 | 7,639 |
pytorch-image-models | timm/optim/sgdw.py | .py | """ SGD with decoupled weight-decay.
References for added functionality:
Cautious Optimizers: https://arxiv.org/abs/2411.16085
Why Gradients Rapidly Increase Near the End of Training: https://arxiv.org/abs/2506.02285
Hacked together by Ross Wightman
"""
from typing import List, Optional
import torch
from tor... | 319 | 11,285 |
pytorch-image-models | timm/optim/sgdp.py | .py | """
SGDP Optimizer Implementation copied from https://github.com/clovaai/AdamP/blob/master/adamp/sgdp.py
Paper: `Slowing Down the Weight Norm Increase in Momentum-based Optimizers` - https://arxiv.org/abs/2006.08217
Code: https://github.com/clovaai/AdamP
References for added functionality:
Cautious Optimizers: ht... | 98 | 2,971 |
pytorch-image-models | timm/optim/muon.py | .py | """ Muon Optimizer
Improved Muon optimizer implementation with flexible handling of high-dimensional tensors.
Combines PyTorch-style structure with options for:
- Batched spatial processing for convolutions in addition to flatten
- Optional spatial normalization
- Selectable coefficient presets
- Automatic fallback t... | 1,057 | 41,665 |
pytorch-image-models | timm/optim/lamb.py | .py | """ PyTorch Lamb optimizer w/ behaviour similar to NVIDIA FusedLamb
This optimizer code was adapted from the following (starting with latest)
* https://github.com/HabanaAI/Model-References/blob/2b435114fe8e31f159b1d3063b8280ae37af7423/PyTorch/nlp/bert/pretraining/lamb.py
* https://github.com/NVIDIA/DeepLearningExample... | 253 | 11,038 |
pytorch-image-models | timm/optim/nadamw.py | .py | """ NAdamW Optimizer
Based on simplified algorithm in https://github.com/mlcommons/algorithmic-efficiency/tree/main/baselines/nadamw
Added multi-tensor (foreach) path.
References for added functionality:
Cautious Optimizers: https://arxiv.org/abs/2411.16085
Why Gradients Rapidly Increase Near the End of Trai... | 427 | 16,131 |
pytorch-image-models | timm/optim/lookahead.py | .py | """ Lookahead Optimizer Wrapper.
Implementation modified from: https://github.com/alphadl/lookahead.pytorch
Paper: `Lookahead Optimizer: k steps forward, 1 step back` - https://arxiv.org/abs/1907.08610
Hacked together by / Copyright 2020 Ross Wightman
"""
from collections import OrderedDict
from typing import Callable... | 67 | 2,687 |
pytorch-image-models | timm/optim/adafactor_bv.py | .py | """ Adafactor (Big Vision variant) for PyTorch
Adapted from the implementation in big vision: https://github.com/google-research/big_vision
Described in 'Scaling Vision Transformers': https://arxiv.org/abs/2106.04560
References for added functionality:
Cautious Optimizers: https://arxiv.org/abs/2411.16085
Wh... | 341 | 13,102 |
pytorch-image-models | timm/optim/kron.py | .py | """ PyTorch Implementation of the Kron (PSGD) optimizer
This is a PSGD optimizer using a Kronecker-factored preconditioner.
This impl was adapted from https://github.com/evanatyourservice/kron_torch
by Evan Walters, licensed CC-BY-4.0.
Contributions to above also made by
* Lucas Nestler, added to his https://github.... | 564 | 22,341 |
pytorch-image-models | timm/optim/nvnovograd.py | .py | """ Nvidia NovoGrad Optimizer.
Original impl by Nvidia from Jasper example:
- https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/SpeechRecognition/Jasper
Paper: `Stochastic Gradient Methods with Layer-wise Adaptive Moments for Training of Deep Networks`
- https://arxiv.org/abs/1905.11286
"""
im... | 133 | 4,953 |
pytorch-image-models | timm/optim/adamw.py | .py | """ AdamW Optimizer
Impl copied from PyTorch master
References for added functionality:
Cautious Optimizers: https://arxiv.org/abs/2411.16085
Why Gradients Rapidly Increase Near the End of Training: https://arxiv.org/abs/2506.02285
NOTE: This impl has been deprecated in favour of torch.optim.AdamW and remains... | 458 | 17,444 |
pytorch-image-models | timm/optim/adopt.py | .py | """ ADOPT PyTorch Optimizer
ADOPT: Modified Adam Can Converge with Any β2 with the Optimal Rate: https://arxiv.org/abs/2411.02853
Modified for reduced dependencies on PyTorch internals from original at: https://github.com/iShohei220/adopt
@inproceedings{taniguchi2024adopt,
author={Taniguchi, Shohei and Harada, Keno... | 527 | 19,706 |
pytorch-image-models | timm/optim/laprop.py | .py | """ PyTorch impl of LaProp optimizer
Code simplified from https://github.com/Z-T-WANG/LaProp-Optimizer, MIT License
Paper: LaProp: Separating Momentum and Adaptivity in Adam, https://arxiv.org/abs/2002.04839
@article{ziyin2020laprop,
title={LaProp: a Better Way to Combine Momentum with Adaptive Gradient},
author... | 160 | 6,418 |
pytorch-image-models | timm/optim/_helpers.py | .py | """Small optimizer helpers shared by timm optimizer implementations."""
from typing import List, Optional, Sequence, Union
import torch
from torch import Tensor
def _get_scalar_dtype() -> torch.dtype:
return torch.float64 if torch.get_default_dtype() == torch.float64 else torch.float32
def _init_scalar(
... | 91 | 3,241 |
pytorch-image-models | timm/optim/mars.py | .py | """ PyTorch MARS Optimizer
Code simplified from https://github.com/AGI-Arena/MARS
Paper: MARS: Unleashing the Power of Variance Reduction for Training Large Models - https://arxiv.org/abs/2411.10438
@article{yuan2024mars,
title={MARS: Unleashing the Power of Variance Reduction for Training Large Models},
author=... | 208 | 7,404 |
pytorch-image-models | timm/optim/lion.py | .py | """ Lion Optimizer
Paper: `Symbolic Discovery of Optimization Algorithms` - https://arxiv.org/abs/2302.06675
Original Impl: https://github.com/google/automl/tree/master/lion
References for added functionality:
Cautious Optimizers: https://arxiv.org/abs/2411.16085
Why Gradients Rapidly Increase Near the End of ... | 271 | 8,999 |
pytorch-image-models | timm/optim/lars.py | .py | """ PyTorch LARS / LARC Optimizer
An implementation of LARS (SGD) + LARC in PyTorch
Based on:
* PyTorch SGD: https://github.com/pytorch/pytorch/blob/1.7/torch/optim/sgd.py#L100
* NVIDIA APEX LARC: https://github.com/NVIDIA/apex/blob/master/apex/parallel/LARC.py
Additional cleanup and modifications to properly su... | 133 | 5,166 |
pytorch-image-models | timm/optim/adamp.py | .py | """
AdamP Optimizer Implementation copied from https://github.com/clovaai/AdamP/blob/master/adamp/adamp.py
Paper: `Slowing Down the Weight Norm Increase in Momentum-based Optimizers` - https://arxiv.org/abs/2006.08217
Code: https://github.com/clovaai/AdamP
References for added functionality:
Cautious Optimizers:... | 152 | 5,156 |
pytorch-image-models | timm/optim/_types.py | .py | from typing import Any, Dict, Iterable, Union, Protocol, Type
try:
from typing import TypeAlias
except ImportError:
from typing_extensions import TypeAlias
try:
from typing import TypeVar
except ImportError:
from typing_extensions import TypeVar
import torch
import torch.optim
try:
from torch.opti... | 29 | 735 |
pytorch-image-models | timm/optim/adan.py | .py | """ Adan Optimizer
Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models[J]. arXiv preprint arXiv:2208.06677, 2022.
https://arxiv.org/abs/2208.06677
Implementation adapted from https://github.com/sail-sg/Adan
"""
# Copyright 2022 Garena Online Private Limited
#
# Licensed under the Apache L... | 328 | 11,757 |
pytorch-image-models | timm/optim/adabelief.py | .py | import math
import torch
from torch.optim.optimizer import Optimizer
class AdaBelief(Optimizer):
r"""Implements AdaBelief algorithm. Modified from Adam in PyTorch
Arguments:
params (iterable): iterable of parameters to optimize or dicts defining
parameter groups
lr (float, optiona... | 219 | 10,034 |
pytorch-image-models | timm/optim/madgrad.py | .py | """ PyTorch MADGRAD optimizer
MADGRAD: https://arxiv.org/abs/2101.11075
Code from: https://github.com/facebookresearch/madgrad
"""
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import ma... | 190 | 6,951 |
pytorch-image-models | timm/optim/adahessian.py | .py | """ AdaHessian Optimizer
Lifted from https://github.com/davda54/ada-hessian/blob/master/ada_hessian.py
Originally licensed MIT, Copyright 2020, David Samuel
"""
import torch
class Adahessian(torch.optim.Optimizer):
"""
Implements the AdaHessian algorithm from "ADAHESSIAN: An Adaptive Second OrderOptimizer fo... | 173 | 6,716 |
pytorch-image-models | timm/optim/_optim_factory.py | .py | """ Optimizer Factory w/ custom Weight Decay & Layer Decay support
Hacked together by / Copyright 2021 Ross Wightman
"""
import logging
from dataclasses import dataclass
from functools import partial
from typing import Any, Callable, Collection, Dict, List, Optional, Set, Tuple, Type, Union
from fnmatch import fnmatch... | 1,340 | 48,836 |
pytorch-image-models | results/generate_csv_results.py | .py | import numpy as np
import pandas as pd
results = {
'results-imagenet.csv': [
'results-imagenet-real.csv',
'results-imagenetv2-matched-frequency.csv',
'results-sketch.csv'
],
'results-imagenet-a-clean.csv': [
'results-imagenet-a.csv',
],
'results-imagenet-r-clean.csv... | 80 | 2,769 |
pytorch-image-models | tests/test_factory.py | .py | import pytest
from timm.models import parse_model_name, safe_model_name
@pytest.mark.parametrize('model_name,expected', [
# plain timm model names
('resnet18', (None, 'resnet18')),
('resnet18.a1_in1k', (None, 'resnet18.a1_in1k')),
# hf-hub, incl. deprecated hf_hub prefix and revision in path
('hf... | 81 | 3,676 |
pytorch-image-models | tests/test_naflex_dataset.py | .py | import warnings
from types import SimpleNamespace
import torch
from torch.utils.data import DataLoader, Dataset
from timm.data import NaFlexMapDatasetWrapper
class _TensorImageDataset(Dataset):
def __init__(self, length=32):
self.length = length
def __getitem__(self, index):
return torch.fu... | 99 | 2,862 |
pytorch-image-models | tests/test_dataset_info.py | .py | import pytest
from timm.data import CustomDatasetInfo, DatasetInfoLabelMapper, LabelMappingCoverage
@pytest.mark.parametrize('label_names', [
['cat', 'dog'],
('cat', 'dog'),
])
def test_custom_dataset_info_sequence_labels(label_names):
info = CustomDatasetInfo(
label_names,
label_descript... | 74 | 2,566 |
pytorch-image-models | tests/test_scheduler.py | .py | """ Scheduler Tests
Tests for learning rate schedulers in timm.scheduler.
"""
import math
import pytest
import torch
from torch.nn import Parameter
from timm.scheduler import (
CosineLRScheduler,
StepLRScheduler,
MultiStepLRScheduler,
PlateauLRScheduler,
PolyLRScheduler,
TanhLRScheduler,
)
fro... | 535 | 18,291 |
pytorch-image-models | tests/test_layers_drop.py | .py | """Tests for timm.layers.drop module (DropBlock, DropPath)."""
import torch
import pytest
from timm.layers.drop import drop_block_2d, DropBlock2d, drop_path, DropPath
class TestDropBlock2d:
"""Test drop_block_2d function and DropBlock2d module."""
def test_drop_block_2d_output_shape(self):
"""Test t... | 252 | 10,708 |
pytorch-image-models | tests/test_layers.py | .py | import pytest
import torch
import torch.nn as nn
from timm.layers import (
Attention2d,
MultiQueryAttentionV2,
PatchEmbedInterpolator,
create_act_layer,
get_act_fn,
get_act_layer,
resample_abs_pos_embed,
resample_patch_embed,
set_layer_config,
)
import importlib
import os
torch_ba... | 342 | 10,817 |
pytorch-image-models | tests/test_hub.py | .py | import pytest
import torch
from timm.models._hub import load_state_dict_from_path
try:
import safetensors.torch
_has_safetensors = True
except ImportError:
_has_safetensors = False
def _write_ckpt(path, value):
state_dict = {'weight': torch.full((2,), float(value))}
if path.suffix == '.safetenso... | 64 | 2,357 |
pytorch-image-models | tests/test_scheduled_sampler.py | .py | from collections import Counter
import pytest
import torch
from PIL import Image
from torch.utils.data import Dataset, DistributedSampler, SequentialSampler
from timm.data import FastCollateMixup, ScheduledBatchSampler, ScheduledTransformDataset, create_loader
class _ImageDataset(Dataset):
def __init__(self, le... | 481 | 16,555 |
pytorch-image-models | tests/test_models.py | .py | """Run tests for all models
Tests that run on CI should have a specific marker, e.g. @pytest.mark.base. This
marker is used to parallelize the CI runs, with one runner for each marker.
If new tests are added, ensure that they use one of the existing markers
(documented in pyproject.toml > pytest > markers) or that a ... | 1,039 | 46,130 |
pytorch-image-models | tests/test_task.py | .py | import pytest
import torch
import torch.nn as nn
from timm.task import ClassificationTask, FeatureDistillationTask, load_task_ema_checkpoint, resume_task_checkpoint
from timm.optim import create_optimizer_v2
from timm.utils import CheckpointSaver
class TinyClassifier(nn.Module):
def __init__(self, in_chans=3, nu... | 211 | 7,881 |
pytorch-image-models | tests/test_optim.py | .py | """ Optimzier Tests
These tests were adapted from PyTorch' optimizer tests.
"""
import functools
import importlib
import os
from copy import deepcopy
import pytest
import torch
from torch.nn import Parameter
from torch.testing._internal.common_utils import TestCase
from timm.optim import create_optimizer_v2, list_o... | 764 | 25,686 |
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