repo_id stringlengths 15 89 | file_path stringlengths 27 180 | content stringlengths 1 2.23M | __index_level_0__ int64 0 0 |
|---|---|---|---|
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/deit.py | """ DeiT - Data-efficient Image Transformers
DeiT model defs and weights from https://github.com/facebookresearch/deit, original copyright below
paper: `DeiT: Data-efficient Image Transformers` - https://arxiv.org/abs/2012.12877
paper: `DeiT III: Revenge of the ViT` - https://arxiv.org/abs/2204.07118
Modifications ... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/pnasnet.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
import torch
import torch... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/ghostnet.py | """
An implementation of GhostNet & GhostNetV2 Models as defined in:
GhostNet: More Features from Cheap Operations. https://arxiv.org/abs/1911.11907
GhostNetV2: Enhance Cheap Operation with Long-Range Attention. https://proceedings.neurips.cc/paper_files/paper/2022/file/40b60852a4abdaa696b5a1a78da34635-Paper-Conference... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/fastvit.py | # FastViT for PyTorch
#
# Original implementation and weights from https://github.com/apple/ml-fastvit
#
# For licensing see accompanying LICENSE file at https://github.com/apple/ml-fastvit/tree/main
# Original work is copyright (C) 2023 Apple Inc. All Rights Reserved.
#
import os
from functools import partial
from typ... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/mobilevit.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... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/metaformer.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.... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/vision_transformer_relpos.py | """ Relative Position Vision Transformer (ViT) in PyTorch
NOTE: these models are experimental / WIP, expect changes
Hacked together by / Copyright 2022, Ross Wightman
"""
import logging
import math
from functools import partial
from typing import Optional, Tuple
import torch
import torch.nn as nn
from torch.jit impo... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/efficientformer_v2.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}... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/_pretrained.py | import copy
from collections import deque, defaultdict
from dataclasses import dataclass, field, replace, asdict
from typing import Any, Deque, Dict, Tuple, Optional, Union
__all__ = ['PretrainedCfg', 'filter_pretrained_cfg', 'DefaultCfg']
@dataclass
class PretrainedCfg:
"""
"""
# weight source location... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/sequencer.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 Tuple
... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/nfnet.py | """ Normalization Free Nets. NFNet, NF-RegNet, NF-ResNet (pre-activation) Models
Paper: `Characterizing signal propagation to close the performance gap in unnormalized ResNets`
- https://arxiv.org/abs/2101.08692
Paper: `High-Performance Large-Scale Image Recognition Without Normalization`
- https://arxiv.org/... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/_helpers.py | """ Model creation / weight loading / state_dict helpers
Hacked together by / Copyright 2020 Ross Wightman
"""
import logging
import os
from collections import OrderedDict
from typing import Any, Callable, Dict, Optional, Union
import torch
try:
import safetensors.torch
_has_safetensors = True
except ImportEr... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/efficientvit_msra.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... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/swin_transformer_v2.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, ... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/_factory.py | import os
from typing import Any, Dict, Optional, Union
from urllib.parse import urlsplit
from timm.layers import set_layer_config
from ._helpers import load_checkpoint
from ._hub import load_model_config_from_hf
from ._pretrained import PretrainedCfg
from ._registry import is_model, model_entrypoint, split_model_name... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/__init__.py | from .beit import *
from .byoanet import *
from .byobnet import *
from .cait import *
from .coat import *
from .convit import *
from .convmixer import *
from .convnext import *
from .crossvit import *
from .cspnet import *
from .davit import *
from .deit import *
from .densenet import *
from .dla import *
from .dpn imp... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/hrnet.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 List
import torch
import torch.nn as... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/focalnet.py | """ FocalNet
As described in `Focal Modulation Networks` - https://arxiv.org/abs/2203.11926
Significant modifications and refactoring from the original impl at https://github.com/microsoft/FocalNet
This impl is/has:
* fully convolutional, NCHW tensor layout throughout, seemed to have minimal performance impact but m... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/cait.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... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/twins.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
# ... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/_efficientnet_blocks.py | """ EfficientNet, MobileNetV3, etc Blocks
Hacked together by / Copyright 2019, Ross Wightman
"""
import torch
import torch.nn as nn
from torch.nn import functional as F
from timm.layers import create_conv2d, DropPath, make_divisible, create_act_layer, get_norm_act_layer
__all__ = [
'SqueezeExcite', 'ConvBnAct',... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/swin_transformer_v2_cr.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 ... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/vision_transformer_sam.py | """ Vision Transformer (ViT) in PyTorch
A PyTorch implement of Vision Transformers as described in:
'Exploring Plain Vision Transformer Backbones for Object Detection'
- https://arxiv.org/abs/2203.16527
'Segment Anything Model (SAM)'
- https://github.com/facebookresearch/segment-anything/
"""
import logging... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/xcit.py | """ Cross-Covariance Image Transformer (XCiT) in PyTorch
Paper:
- https://arxiv.org/abs/2106.09681
Same as the official implementation, with some minor adaptations, original copyright below
- https://github.com/facebookresearch/xcit/blob/master/xcit.py
Modifications and additions for timm hacked together by ... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/models/_features.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... | 0 |
hf_public_repos/pytorch-image-models/timm/models | hf_public_repos/pytorch-image-models/timm/models/layers/__init__.py | # NOTE timm.models.layers is DEPRECATED, please use timm.layers, this is here to reduce breakages in transition
from timm.layers.activations import *
from timm.layers.adaptive_avgmax_pool import \
adaptive_avgmax_pool2d, select_adaptive_pool2d, AdaptiveAvgMaxPool2d, SelectAdaptivePool2d
from timm.layers.attention_p... | 0 |
hf_public_repos/pytorch-image-models/timm/models | hf_public_repos/pytorch-image-models/timm/models/_pruned/efficientnet_b2_pruned.txt | conv_stem.weight:[32, 3, 3, 3]***bn1.weight:[32]***bn1.bias:[32]***bn1.running_mean:[32]***bn1.running_var:[32]***bn1.num_batches_tracked:[]***blocks.0.0.conv_dw.weight:[32, 1, 3, 3]***blocks.0.0.bn1.weight:[32]***blocks.0.0.bn1.bias:[32]***blocks.0.0.bn1.running_mean:[32]***blocks.0.0.bn1.running_var:[32]***blocks.0.0... | 0 |
hf_public_repos/pytorch-image-models/timm/models | hf_public_repos/pytorch-image-models/timm/models/_pruned/ecaresnet50d_pruned.txt | conv1.0.weight:[32, 3, 3, 3]***conv1.1.weight:[32]***conv1.3.weight:[32, 32, 3, 3]***conv1.4.weight:[32]***conv1.6.weight:[64, 32, 3, 3]***bn1.weight:[64]***layer1.0.conv1.weight:[47, 64, 1, 1]***layer1.0.bn1.weight:[47]***layer1.0.conv2.weight:[18, 47, 3, 3]***layer1.0.bn2.weight:[18]***layer1.0.conv3.weight:[19, 18, ... | 0 |
hf_public_repos/pytorch-image-models/timm/models | hf_public_repos/pytorch-image-models/timm/models/_pruned/efficientnet_b3_pruned.txt | conv_stem.weight:[40, 3, 3, 3]***bn1.weight:[40]***bn1.bias:[40]***bn1.running_mean:[40]***bn1.running_var:[40]***bn1.num_batches_tracked:[]***blocks.0.0.conv_dw.weight:[40, 1, 3, 3]***blocks.0.0.bn1.weight:[40]***blocks.0.0.bn1.bias:[40]***blocks.0.0.bn1.running_mean:[40]***blocks.0.0.bn1.running_var:[40]***blocks.0.0... | 0 |
hf_public_repos/pytorch-image-models/timm/models | hf_public_repos/pytorch-image-models/timm/models/_pruned/ecaresnet101d_pruned.txt | conv1.0.weight:[32, 3, 3, 3]***conv1.1.weight:[32]***conv1.3.weight:[32, 32, 3, 3]***conv1.4.weight:[32]***conv1.6.weight:[64, 32, 3, 3]***bn1.weight:[64]***layer1.0.conv1.weight:[45, 64, 1, 1]***layer1.0.bn1.weight:[45]***layer1.0.conv2.weight:[25, 45, 3, 3]***layer1.0.bn2.weight:[25]***layer1.0.conv3.weight:[26, 25, ... | 0 |
hf_public_repos/pytorch-image-models/timm/models | hf_public_repos/pytorch-image-models/timm/models/_pruned/efficientnet_b1_pruned.txt | conv_stem.weight:[32, 3, 3, 3]***bn1.weight:[32]***bn1.bias:[32]***bn1.running_mean:[32]***bn1.running_var:[32]***bn1.num_batches_tracked:[]***blocks.0.0.conv_dw.weight:[32, 1, 3, 3]***blocks.0.0.bn1.weight:[32]***blocks.0.0.bn1.bias:[32]***blocks.0.0.bn1.running_mean:[32]***blocks.0.0.bn1.running_var:[32]***blocks.0.0... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/data/auto_augment.py | """ 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... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/data/dataset.py | """ Quick n Simple Image Folder, Tarfile based DataSet
Hacked together by / Copyright 2019, Ross Wightman
"""
import io
import logging
from typing import Optional
import torch
import torch.utils.data as data
from PIL import Image
from .readers import create_reader
_logger = logging.getLogger(__name__)
_ERROR_RETR... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/data/imagenet_info.py | import csv
import os
import pkgutil
import re
from typing import Dict, List, Optional, Union
from .dataset_info import DatasetInfo
# NOTE no ambiguity wrt to mapping from # classes to ImageNet subset so far, but likely to change
_NUM_CLASSES_TO_SUBSET = {
1000: 'imagenet-1k',
11221: 'imagenet-21k-miil', # m... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/data/transforms_factory.py | """ Transforms Factory
Factory methods for building image transforms for use with TIMM (PyTorch Image Models)
Hacked together by / Copyright 2019, Ross Wightman
"""
import math
import torch
from torchvision import transforms
from timm.data.constants import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, DEFAULT_CROP_PC... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/data/tf_preprocessing.py | """ Tensorflow Preprocessing Adapter
Allows use of Tensorflow preprocessing pipeline in PyTorch Transform
Copyright of original Tensorflow code below.
Hacked together by / Copyright 2020 Ross Wightman
"""
# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/data/transforms.py | import math
import numbers
import random
import warnings
from typing import List, Sequence
import torch
import torchvision.transforms.functional as F
try:
from torchvision.transforms.functional import InterpolationMode
has_interpolation_mode = True
except ImportError:
has_interpolation_mode = False
from PI... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/data/dataset_info.py | from abc import ABC, abstractmethod
from typing import Dict, List, Optional, Union
class DatasetInfo(ABC):
def __init__(self):
pass
@abstractmethod
def num_classes(self):
pass
@abstractmethod
def label_names(self):
pass
@abstractmethod
def label_descriptions(sel... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/data/constants.py | DEFAULT_CROP_PCT = 0.875
DEFAULT_CROP_MODE = 'center'
IMAGENET_DEFAULT_MEAN = (0.485, 0.456, 0.406)
IMAGENET_DEFAULT_STD = (0.229, 0.224, 0.225)
IMAGENET_INCEPTION_MEAN = (0.5, 0.5, 0.5)
IMAGENET_INCEPTION_STD = (0.5, 0.5, 0.5)
IMAGENET_DPN_MEAN = (124 / 255, 117 / 255, 104 / 255)
IMAGENET_DPN_STD = tuple([1 / (.0167 *... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/data/distributed_sampler.py | import math
import torch
from torch.utils.data import Sampler
import torch.distributed as dist
class OrderedDistributedSampler(Sampler):
"""Sampler that restricts data loading to a subset of the dataset.
It is especially useful in conjunction with
:class:`torch.nn.parallel.DistributedDataParallel`. In suc... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/data/random_erasing.py | """ Random Erasing (Cutout)
Originally inspired by impl at https://github.com/zhunzhong07/Random-Erasing, Apache 2.0
Copyright Zhun Zhong & Liang Zheng
Hacked together by / Copyright 2019, Ross Wightman
"""
import random
import math
import torch
def _get_pixels(per_pixel, rand_color, patch_size, dtype=torch.float3... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/data/loader.py | """ Loader Factory, Fast Collate, CUDA Prefetcher
Prefetcher and Fast Collate inspired by NVIDIA APEX example at
https://github.com/NVIDIA/apex/commit/d5e2bb4bdeedd27b1dfaf5bb2b24d6c000dee9be#diff-cf86c282ff7fba81fad27a559379d5bf
Hacked together by / Copyright 2019, Ross Wightman
"""
import logging
import random
from... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/data/dataset_factory.py | """ Dataset Factory
Hacked together by / Copyright 2021, Ross Wightman
"""
import os
from torchvision.datasets import CIFAR100, CIFAR10, MNIST, KMNIST, FashionMNIST, ImageFolder
try:
from torchvision.datasets import Places365
has_places365 = True
except ImportError:
has_places365 = False
try:
from tor... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/data/real_labels.py | """ Real labels evaluator for ImageNet
Paper: `Are we done with ImageNet?` - https://arxiv.org/abs/2006.07159
Based on Numpy example at https://github.com/google-research/reassessed-imagenet
Hacked together by / Copyright 2020 Ross Wightman
"""
import os
import json
import numpy as np
import pkgutil
class RealLabels... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/data/__init__.py | from .auto_augment import RandAugment, AutoAugment, rand_augment_ops, auto_augment_policy,\
rand_augment_transform, auto_augment_transform
from .config import resolve_data_config, resolve_model_data_config
from .constants import *
from .dataset import ImageDataset, IterableImageDataset, AugMixDataset
from .dataset_... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/data/mixup.py | """ Mixup and Cutmix
Papers:
mixup: Beyond Empirical Risk Minimization (https://arxiv.org/abs/1710.09412)
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features (https://arxiv.org/abs/1905.04899)
Code Reference:
CutMix: https://github.com/clovaai/CutMix-PyTorch
Hacked together by / Co... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/data/config.py | import logging
from .constants import *
_logger = logging.getLogger(__name__)
def resolve_data_config(
args=None,
pretrained_cfg=None,
model=None,
use_test_size=False,
verbose=False
):
assert model or args or pretrained_cfg, "At least one of model, args, or pretrained_cfg... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/readers/reader.py | from abc import abstractmethod
class Reader:
def __init__(self):
pass
@abstractmethod
def _filename(self, index, basename=False, absolute=False):
pass
def filename(self, index, basename=False, absolute=False):
return self._filename(index, basename=basename, absolute=absolute)... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/readers/reader_wds.py | """ Dataset reader for webdataset
Hacked together by / Copyright 2022 Ross Wightman
"""
import io
import json
import logging
import math
import os
import random
import sys
from dataclasses import dataclass
from functools import partial
from itertools import islice
from typing import Any, Callable, Dict, List, Optional... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/readers/reader_factory.py | import os
from .reader_image_folder import ReaderImageFolder
from .reader_image_in_tar import ReaderImageInTar
def create_reader(name, root, split='train', **kwargs):
name = name.lower()
name = name.split('/', 1)
prefix = ''
if len(name) > 1:
prefix = name[0]
name = name[-1]
# FIXME ... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/readers/reader_image_in_tar.py | """ A dataset reader that reads tarfile based datasets
This reader can extract image samples from:
* a single tar of image files
* a folder of multiple tarfiles containing imagefiles
* a tar of tars containing image files
Labels are based on the combined folder and/or tar name structure.
Hacked together by / Copyrig... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/readers/reader_tfds.py | """ Dataset reader that wraps TFDS datasets
Wraps many (most?) TFDS image-classification datasets
from https://github.com/tensorflow/datasets
https://www.tensorflow.org/datasets/catalog/overview#image_classification
Hacked together by / Copyright 2020 Ross Wightman
"""
import math
import os
from typing import Optiona... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/readers/class_map.py | import os
import pickle
def load_class_map(map_or_filename, root=''):
if isinstance(map_or_filename, dict):
assert dict, 'class_map dict must be non-empty'
return map_or_filename
class_map_path = map_or_filename
if not os.path.exists(class_map_path):
class_map_path = os.path.join(r... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/readers/reader_image_folder.py | """ A dataset reader that extracts images from folders
Folders are scanned recursively to find image files. Labels are based
on the folder hierarchy, just leaf folders by default.
Hacked together by / Copyright 2020 Ross Wightman
"""
import os
from typing import Dict, List, Optional, Set, Tuple, Union
from timm.util... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/readers/reader_hfds.py | """ Dataset reader that wraps Hugging Face datasets
Hacked together by / Copyright 2022 Ross Wightman
"""
import io
import math
import torch
import torch.distributed as dist
from PIL import Image
try:
import datasets
except ImportError as e:
print("Please install Hugging Face datasets package `pip install dat... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/readers/img_extensions.py | from copy import deepcopy
__all__ = ['get_img_extensions', 'is_img_extension', 'set_img_extensions', 'add_img_extensions', 'del_img_extensions']
IMG_EXTENSIONS = ('.png', '.jpg', '.jpeg') # singleton, kept public for bwd compat use
_IMG_EXTENSIONS_SET = set(IMG_EXTENSIONS) # set version, private, kept in sync
de... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/readers/__init__.py | from .reader_factory import create_reader
from .img_extensions import *
| 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/readers/shared_count.py | from multiprocessing import Value
class SharedCount:
def __init__(self, epoch: int = 0):
self.shared_epoch = Value('i', epoch)
@property
def value(self):
return self.shared_epoch.value
@value.setter
def value(self, epoch):
self.shared_epoch.value = epoch
| 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/readers/reader_image_tar.py | """ A dataset reader that reads single tarfile based datasets
This reader can read datasets consisting if a single tarfile containing images.
I am planning to deprecated it in favour of ParerImageInTar.
Hacked together by / Copyright 2020 Ross Wightman
"""
import os
import tarfile
from timm.utils.misc import natural... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/_info/imagenet12k_synsets.txt | n00005787
n00006484
n00007846
n00015388
n00017222
n00021265
n00021939
n00120010
n00141669
n00288000
n00288384
n00324978
n00326094
n00433458
n00433661
n00433802
n00434075
n00439826
n00440039
n00440382
n00440509
n00440747
n00440941
n00441073
n00441824
n00442115
n00442437
n00442847
n00442981
n00443231
n00443692
n00443803
... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/_info/imagenet_real_labels.json | [[], [970, 795], [230, 231], [809], [516, 850], [57], [334], [700], [674], [332], [109], [286], [370], [757], [595], [147], [327, 108], [21, 22], [478], [517], [334], [], [948], [727], [23], [619, 526, 846], [270], [167], [64, 55], [858], [324], [573], [150], [981], [586], [887], [], [398], [], [74], [516], [756], [129... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/_info/imagenet_synset_to_lemma.txt | n00004475 organism, being
n00005787 benthos
n00006024 heterotroph
n00006484 cell
n00007846 person, individual, someone, somebody, mortal, soul
n00015388 animal, animate being, beast, brute, creature, fauna
n00017222 plant, flora, plant life
n00021265 food, nutrient
n00021939 artifact, artefact
n00120010 hop
n00141669 c... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/_info/imagenet_a_indices.txt | 6
11
13
15
17
22
23
27
30
37
39
42
47
50
57
70
71
76
79
89
90
94
96
97
99
105
107
108
110
113
124
125
130
132
143
144
150
151
207
234
235
254
277
283
287
291
295
298
301
306
307
308
309
310
311
313
314
315
317
319
323
324
326
327
330
334
335
336
347
361
363
372
378
386
397
400
401
402
404
407
411
416
417
420
425
428
43... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/_info/imagenet22k_to_12k_indices.txt | 1
3
4
5
6
7
8
9
10
11
13
14
15
16
17
18
19
20
21
23
24
26
27
28
29
30
31
32
33
34
37
38
41
43
44
45
46
47
48
49
50
51
53
55
56
57
58
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
89
90
91
93
94
95
96
97
99
100
101
102
103
105
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/_info/imagenet_r_synsets.txt | n01443537
n01484850
n01494475
n01498041
n01514859
n01518878
n01531178
n01534433
n01614925
n01616318
n01630670
n01632777
n01644373
n01677366
n01694178
n01748264
n01770393
n01774750
n01784675
n01806143
n01820546
n01833805
n01843383
n01847000
n01855672
n01860187
n01882714
n01910747
n01944390
n01983481
n01986214
n02007558
... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/_info/imagenet_a_synsets.txt | n01498041
n01531178
n01534433
n01558993
n01580077
n01614925
n01616318
n01631663
n01641577
n01669191
n01677366
n01687978
n01694178
n01698640
n01735189
n01770081
n01770393
n01774750
n01784675
n01819313
n01820546
n01833805
n01843383
n01847000
n01855672
n01882714
n01910747
n01914609
n01924916
n01944390
n01985128
n01986214
... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/_info/imagenet22k_ms_synsets.txt | n01440764
n01443537
n01484850
n01491361
n01494475
n01496331
n01498041
n01514668
n01514859
n01518878
n01530575
n01531178
n01532829
n01534433
n01537544
n01558993
n01560419
n01580077
n01582220
n01592084
n01601694
n01608432
n01614925
n01616318
n01622779
n01629819
n01630670
n01631663
n01632458
n01632777
n01641577
n01644373
... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/_info/imagenet22k_ms_to_22k_indices.txt | 1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/_info/imagenet21k_goog_synsets.txt | n00004475
n00005787
n00006024
n00006484
n00007846
n00015388
n00017222
n00021265
n00021939
n00120010
n00141669
n00288000
n00288190
n00288384
n00324978
n00326094
n00433458
n00433661
n00433802
n00434075
n00439826
n00440039
n00440218
n00440382
n00440509
n00440643
n00440747
n00440941
n00441073
n00441824
n00442115
n00442437
... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/_info/imagenet22k_ms_to_12k_indices.txt | 1001
1003
1004
1005
1006
1007
1008
1009
1010
1011
1013
1014
1015
1016
1017
1018
1019
1020
1021
1023
1024
1026
1027
1028
1029
1030
1031
1032
1033
1034
1037
1038
1041
1043
1044
1045
1046
1047
1048
1049
1050
1051
1053
1055
1056
1057
1058
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/_info/imagenet_synset_to_definition.txt | n00004475 a living thing that has (or can develop) the ability to act or function independently
n00005787 organisms (plants and animals) that live at or near the bottom of a sea
n00006024 an organism that depends on complex organic substances for nutrition
n00006484 (biology) the basic structural and functional unit of... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/_info/imagenet_synsets.txt | n01440764
n01443537
n01484850
n01491361
n01494475
n01496331
n01498041
n01514668
n01514859
n01518878
n01530575
n01531178
n01532829
n01534433
n01537544
n01558993
n01560419
n01580077
n01582220
n01592084
n01601694
n01608432
n01614925
n01616318
n01622779
n01629819
n01630670
n01631663
n01632458
n01632777
n01641577
n01644373
... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/_info/imagenet_r_indices.txt | 1
2
4
6
8
9
11
13
22
23
26
29
31
39
47
63
71
76
79
84
90
94
96
97
99
100
105
107
113
122
125
130
132
144
145
147
148
150
151
155
160
161
162
163
171
172
178
187
195
199
203
207
208
219
231
232
234
235
242
245
247
250
251
254
259
260
263
265
267
269
276
277
281
288
289
291
292
293
296
299
301
308
309
310
311
314
315
319... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/_info/imagenet21k_miil_w21_synsets.txt | n00005787
n00006484
n00007846
n00015388
n00017222
n00021265
n00021939
n00120010
n00141669
n00288000
n00288384
n00324978
n00326094
n00433458
n00433661
n00433802
n00434075
n00439826
n00440039
n00440382
n00440509
n00440747
n00440941
n00441073
n00441824
n00442115
n00442437
n00442847
n00442981
n00443231
n00443692
n00443803
... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/_info/imagenet21k_miil_synsets.txt | n00005787
n00006484
n00007846
n00015388
n00017222
n00021265
n00021939
n00120010
n00141669
n00288000
n00288384
n00324978
n00326094
n00433458
n00433661
n00433802
n00434075
n00439826
n00440039
n00440382
n00440509
n00440747
n00440941
n00441073
n00441824
n00442115
n00442437
n00442847
n00442981
n00443231
n00443692
n00443803
... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/_info/imagenet22k_synsets.txt | n00004475
n00005787
n00006024
n00006484
n00007846
n00015388
n00017222
n00021265
n00021939
n00120010
n00141669
n00288000
n00288190
n00288384
n00324978
n00326094
n00433458
n00433661
n00433802
n00434075
n00439826
n00440039
n00440218
n00440382
n00440509
n00440643
n00440747
n00440941
n00441073
n00441824
n00442115
n00442437
... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/_info/imagenet21k_goog_to_12k_indices.txt | 1
3
4
5
6
7
8
9
10
11
13
14
15
16
17
18
19
20
21
23
24
26
27
28
29
30
31
32
33
34
37
38
41
43
44
45
46
47
48
49
50
51
53
55
56
57
58
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
89
90
91
93
94
95
96
97
99
100
101
102
103
105
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121... | 0 |
hf_public_repos/pytorch-image-models/timm/data | hf_public_repos/pytorch-image-models/timm/data/_info/imagenet21k_goog_to_22k_indices.txt | 0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
10... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/scheduler/scheduler.py | import abc
from abc import ABC
from typing import Any, Dict, Optional
import torch
class Scheduler(ABC):
""" Parameter Scheduler Base Class
A scheduler base class that can be used to schedule any optimizer parameter groups.
Unlike the builtin PyTorch schedulers, this is intended to be consistently calle... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/scheduler/scheduler_factory.py | """ Scheduler Factory
Hacked together by / Copyright 2021 Ross Wightman
"""
from typing import List, Union
from torch.optim import Optimizer
from .cosine_lr import CosineLRScheduler
from .multistep_lr import MultiStepLRScheduler
from .plateau_lr import PlateauLRScheduler
from .poly_lr import PolyLRScheduler
from .ste... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/scheduler/cosine_lr.py | """ Cosine Scheduler
Cosine LR schedule with warmup, cycle/restarts, noise, k-decay.
Hacked together by / Copyright 2021 Ross Wightman
"""
import logging
import math
import numpy as np
import torch
from .scheduler import Scheduler
_logger = logging.getLogger(__name__)
class CosineLRScheduler(Scheduler):
"""
... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/scheduler/step_lr.py | """ Step Scheduler
Basic step LR schedule with warmup, noise.
Hacked together by / Copyright 2020 Ross Wightman
"""
import math
import torch
from .scheduler import Scheduler
class StepLRScheduler(Scheduler):
"""
"""
def __init__(
self,
optimizer: torch.optim.Optimizer,
... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/scheduler/multistep_lr.py | """ MultiStep LR Scheduler
Basic multi step LR schedule with warmup, noise.
"""
import torch
import bisect
from timm.scheduler.scheduler import Scheduler
from typing import List
class MultiStepLRScheduler(Scheduler):
"""
"""
def __init__(
self,
optimizer: torch.optim.Optimizer,
... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/scheduler/plateau_lr.py | """ Plateau Scheduler
Adapts PyTorch plateau scheduler and allows application of noise, warmup.
Hacked together by / Copyright 2020 Ross Wightman
"""
import torch
from .scheduler import Scheduler
class PlateauLRScheduler(Scheduler):
"""Decay the LR by a factor every time the validation loss plateaus."""
d... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/scheduler/tanh_lr.py | """ TanH Scheduler
TanH schedule with warmup, cycle/restarts, noise.
Hacked together by / Copyright 2021 Ross Wightman
"""
import logging
import math
import numpy as np
import torch
from .scheduler import Scheduler
_logger = logging.getLogger(__name__)
class TanhLRScheduler(Scheduler):
"""
Hyberbolic-Tan... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/scheduler/poly_lr.py | """ Polynomial Scheduler
Polynomial LR schedule with warmup, noise.
Hacked together by / Copyright 2021 Ross Wightman
"""
import math
import logging
import torch
from .scheduler import Scheduler
_logger = logging.getLogger(__name__)
class PolyLRScheduler(Scheduler):
""" Polynomial LR Scheduler w/ warmup, no... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/scheduler/__init__.py | from .cosine_lr import CosineLRScheduler
from .multistep_lr import MultiStepLRScheduler
from .plateau_lr import PlateauLRScheduler
from .poly_lr import PolyLRScheduler
from .step_lr import StepLRScheduler
from .tanh_lr import TanhLRScheduler
from .scheduler_factory import create_scheduler, create_scheduler_v2, schedul... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/utils/model_ema.py | """ Exponential Moving Average (EMA) of model updates
Hacked together by / Copyright 2020 Ross Wightman
"""
import logging
from collections import OrderedDict
from copy import deepcopy
import torch
import torch.nn as nn
_logger = logging.getLogger(__name__)
class ModelEma:
""" Model Exponential Moving Average ... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/utils/onnx.py | from typing import Optional, Tuple, List
import torch
def onnx_forward(onnx_file, example_input):
import onnxruntime
sess_options = onnxruntime.SessionOptions()
session = onnxruntime.InferenceSession(onnx_file, sess_options)
input_name = session.get_inputs()[0].name
output = session.run([], {inp... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/utils/misc.py | """ Misc utils
Hacked together by / Copyright 2020 Ross Wightman
"""
import argparse
import ast
import re
def natural_key(string_):
"""See http://www.codinghorror.com/blog/archives/001018.html"""
return [int(s) if s.isdigit() else s for s in re.split(r'(\d+)', string_.lower())]
def add_bool_arg(parser, nam... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/utils/agc.py | """ Adaptive Gradient Clipping
An impl of AGC, as per (https://arxiv.org/abs/2102.06171):
@article{brock2021high,
author={Andrew Brock and Soham De and Samuel L. Smith and Karen Simonyan},
title={High-Performance Large-Scale Image Recognition Without Normalization},
journal={arXiv preprint arXiv:},
year={2021... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/utils/decay_batch.py | """ Batch size decay and retry helpers.
Copyright 2022 Ross Wightman
"""
import math
def decay_batch_step(batch_size, num_intra_steps=2, no_odd=False):
""" power of two batch-size decay with intra steps
Decay by stepping between powers of 2:
* determine power-of-2 floor of current batch size (base batch... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/utils/model.py | """ Model / state_dict utils
Hacked together by / Copyright 2020 Ross Wightman
"""
import fnmatch
from copy import deepcopy
import torch
from torchvision.ops.misc import FrozenBatchNorm2d
from timm.layers import BatchNormAct2d, SyncBatchNormAct, FrozenBatchNormAct2d,\
freeze_batch_norm_2d, unfreeze_batch_norm_2d... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/utils/summary.py | """ Summary utilities
Hacked together by / Copyright 2020 Ross Wightman
"""
import csv
import os
from collections import OrderedDict
try:
import wandb
except ImportError:
pass
def get_outdir(path, *paths, inc=False):
outdir = os.path.join(path, *paths)
if not os.path.exists(outdir):
os.maked... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/utils/clip_grad.py | import torch
from timm.utils.agc import adaptive_clip_grad
def dispatch_clip_grad(parameters, value: float, mode: str = 'norm', norm_type: float = 2.0):
""" Dispatch to gradient clipping method
Args:
parameters (Iterable): model parameters to clip
value (float): clipping value/factor/norm, m... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/utils/log.py | """ Logging helpers
Hacked together by / Copyright 2020 Ross Wightman
"""
import logging
import logging.handlers
class FormatterNoInfo(logging.Formatter):
def __init__(self, fmt='%(levelname)s: %(message)s'):
logging.Formatter.__init__(self, fmt)
def format(self, record):
if record.levelno =... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/utils/jit.py | """ JIT scripting/tracing utils
Hacked together by / Copyright 2020 Ross Wightman
"""
import os
import torch
def set_jit_legacy():
""" Set JIT executor to legacy w/ support for op fusion
This is hopefully a temporary need in 1.5/1.5.1/1.6 to restore performance due to changes
in the JIT exectutor. These... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/utils/metrics.py | """ Eval metrics and related
Hacked together by / Copyright 2020 Ross Wightman
"""
class AverageMeter:
"""Computes and stores the average and current value"""
def __init__(self):
self.reset()
def reset(self):
self.val = 0
self.avg = 0
self.sum = 0
self.count = 0
... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/utils/distributed.py | """ Distributed training/validation utils
Hacked together by / Copyright 2020 Ross Wightman
"""
import os
import torch
from torch import distributed as dist
try:
import horovod.torch as hvd
except ImportError:
hvd = None
from .model import unwrap_model
def reduce_tensor(tensor, n):
rt = tensor.clone()... | 0 |
hf_public_repos/pytorch-image-models/timm | hf_public_repos/pytorch-image-models/timm/utils/__init__.py | from .agc import adaptive_clip_grad
from .checkpoint_saver import CheckpointSaver
from .clip_grad import dispatch_clip_grad
from .cuda import ApexScaler, NativeScaler
from .decay_batch import decay_batch_step, check_batch_size_retry
from .distributed import distribute_bn, reduce_tensor, init_distributed_device,\
wo... | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.