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/utils/clip_grad.py | .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... | 24 | 796 |
pytorch-image-models | timm/utils/random.py | .py | import random
import numpy as np
import torch
def random_seed(seed=42, rank=0):
torch.manual_seed(seed + rank)
np.random.seed(seed + rank)
random.seed(seed + rank)
| 10 | 178 |
pytorch-image-models | timm/utils/decay_batch.py | .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... | 44 | 1,762 |
pytorch-image-models | timm/utils/agc.py | .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... | 43 | 1,624 |
pytorch-image-models | timm/utils/metrics.py | .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
... | 33 | 922 |
pytorch-image-models | timm/utils/log.py | .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 =... | 29 | 1,015 |
pytorch-image-models | timm/utils/onnx.py | .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... | 105 | 3,710 |
pytorch-image-models | timm/utils/summary.py | .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... | 52 | 1,325 |
pytorch-image-models | timm/utils/cuda.py | .py | """ CUDA / AMP utils
Hacked together by / Copyright 2020 Ross Wightman
"""
import torch
try:
from apex import amp
has_apex = True
except ImportError:
amp = None
has_apex = False
from .clip_grad import dispatch_clip_grad
class ApexScaler:
state_dict_key = "amp"
def __call__(
sel... | 79 | 2,173 |
pytorch-image-models | timm/utils/checkpoint_saver.py | .py | """ Checkpoint Saver
Track top-n training checkpoints and maintain recovery checkpoints on specified intervals.
Hacked together by / Copyright 2020 Ross Wightman
"""
import glob
import logging
import operator
import os
import shutil
import torch
from .model import unwrap_model, get_state_dict
_logger = logging.g... | 188 | 7,197 |
pytorch-image-models | timm/task/distillation.py | .py | """Knowledge distillation training tasks and components."""
import logging
from typing import Dict, Optional, Tuple, Union
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.models import create_model, group_parameters
from timm.utils import unwrap_model
from .task import TrainingTask
_lo... | 760 | 29,961 |
pytorch-image-models | timm/task/__init__.py | .py | """Training task abstractions for timm.
This module provides task-based abstractions for training loops where each task
encapsulates both the forward pass and loss computation, returning a dictionary
with loss components and outputs for logging.
"""
from .task import TrainingTask
from ._helpers import resume_task_chec... | 24 | 845 |
pytorch-image-models | timm/task/classification.py | .py | """Classification training task."""
import logging
from typing import Callable, Dict, Optional, Union
import torch
import torch.nn as nn
from .task import TrainingTask
_logger = logging.getLogger(__name__)
class ClassificationTask(TrainingTask):
"""Standard supervised classification task.
Simple task that... | 103 | 3,244 |
pytorch-image-models | timm/task/_helpers.py | .py | """Checkpoint helpers for task-based training."""
import argparse
import logging
import os
from typing import Optional
import torch
from timm.models import clean_state_dict
_logger = logging.getLogger(__name__)
def _load_train_checkpoint(checkpoint_path, weights_only=True):
use_safe_globals = weights_only and... | 107 | 4,127 |
pytorch-image-models | timm/task/task.py | .py | """Base training task abstraction.
This module provides the base TrainingTask class that encapsulates a complete
forward pass including loss computation. Tasks return a dictionary with loss
components and outputs for logging.
"""
from contextlib import nullcontext
from typing import Any, Dict, Optional
import torch
i... | 248 | 8,999 |
pytorch-image-models | timm/task/token_distillation.py | .py | """Token-based distillation training task for models with distillation heads."""
import logging
from typing import Dict, Optional, Union
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.models import create_model
from timm.utils import unwrap_model
from .task import TrainingTask
_logger ... | 369 | 15,230 |
pytorch-image-models | timm/data/naflex_loader.py | .py | """NaFlex data loader for dynamic sequence length training.
This module provides a specialized data loader for Vision Transformer models that supports:
- Dynamic sequence length sampling during training for improved efficiency
- Variable patch size training with probabilistic selection
- Patch-level random erasing aug... | 459 | 18,490 |
pytorch-image-models | timm/data/distributed_sampler.py | .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... | 136 | 5,540 |
pytorch-image-models | timm/data/naflex_transforms.py | .py | """ NaFlex (NaViT + FlexiViT) Transforms and Collation
Implements PyTorch versions of the transforms described in the NaViT and FlexiViT papers:
- NaViT: https://arxiv.org/abs/2307.14995
- FlexiViT: https://arxiv.org/abs/2212.08013
Enables variable resolution/aspect ratio image handling with efficient patching.
Hack... | 850 | 33,926 |
pytorch-image-models | timm/data/naflex_dataset.py | .py | """ Dynamic Sequence Length Datasets for Variable Resolution Image Processing
Implements two dataset wrappers:
1. NaFlexMapDatasetWrapper - Map-style dataset that returns batches with variable sequence lengths
TODO: 2. NaFlexIterableDatasetWrapper - Iterable dataset that yields batches with variable sequence lengths
... | 566 | 25,014 |
pytorch-image-models | timm/data/dataset_info.py | .py | from abc import ABC, abstractmethod
from numbers import Integral
from typing import Dict, List, NamedTuple, Optional, Tuple, Union
LabelNames = Union[List[str], Tuple[str, ...], Dict[Union[int, str], str]]
class DatasetInfo(ABC):
def __init__(self):
pass
@abstractmethod
def num_classes(self):
... | 176 | 6,996 |
pytorch-image-models | timm/data/random_erasing.py | .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... | 118 | 4,964 |
pytorch-image-models | timm/data/auto_augment.py | .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... | 1,001 | 35,599 |
pytorch-image-models | timm/data/naflex_random_erasing.py | .py | """Patch-level random erasing augmentation for NaFlex Vision Transformers.
This module implements random erasing specifically designed for patchified images,
operating at the patch granularity rather than pixel level. It supports two modes:
- 'patch': Randomly erases individual patches (speckle-like noise)
- 'region':... | 354 | 14,283 |
pytorch-image-models | timm/data/__init__.py | .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_... | 29 | 1,367 |
pytorch-image-models | timm/data/constants.py | .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 *... | 11 | 442 |
pytorch-image-models | timm/data/transforms.py | .py | import math
import numbers
import random
import warnings
from typing import List, Sequence, Tuple, Union
import torch
import torchvision.transforms as transforms
import torchvision.transforms.functional as F
try:
from torchvision.transforms.functional import InterpolationMode
has_interpolation_mode = True
exce... | 584 | 20,120 |
pytorch-image-models | timm/data/real_labels.py | .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... | 48 | 1,800 |
pytorch-image-models | timm/data/imagenet_info.py | .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... | 96 | 4,167 |
pytorch-image-models | timm/data/mixup.py | .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... | 350 | 16,078 |
pytorch-image-models | timm/data/transforms_factory.py | .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
from typing import Optional, Tuple, Union
import torch
from torchvision import transforms
from timm.data.constants import IMAGENET_DEFAULT_M... | 535 | 22,478 |
pytorch-image-models | timm/data/dataset.py | .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... | 208 | 6,527 |
pytorch-image-models | timm/data/tf_preprocessing.py | .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.... | 234 | 9,169 |
pytorch-image-models | timm/data/config.py | .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... | 130 | 4,616 |
pytorch-image-models | timm/data/loader.py | .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... | 505 | 21,065 |
pytorch-image-models | timm/data/scheduled_sampler.py | .py | """Scheduled batch sampling and transform dispatch for map-style datasets."""
import math
from itertools import islice
from typing import Any, Callable, Iterator, List, Optional, Sequence, Tuple, Union
import torch
from torch.utils.data import Dataset, Sampler
class ScheduledBatchSampler(Sampler[List[Tuple[Any, int... | 332 | 15,383 |
pytorch-image-models | timm/data/dataset_factory.py | .py | """ Dataset Factory
Hacked together by / Copyright 2021, Ross Wightman
"""
import os
from typing import Optional
from torchvision.datasets import CIFAR100, CIFAR10, MNIST, KMNIST, FashionMNIST, ImageFolder
try:
from torchvision.datasets import Places365
has_places365 = True
except ImportError:
has_places3... | 231 | 8,627 |
pytorch-image-models | timm/data/naflex_mixup.py | .py | """Variable‑size Mixup / CutMix utilities for NaFlex data loaders.
This module provides:
* `mix_batch_variable_size` – pixel‑level Mixup/CutMix that operates on a
list of images whose spatial sizes differ, mixing only their central overlap
so no resizing is required.
* `pairwise_mixup_target` – builds soft‑label ... | 251 | 9,001 |
pytorch-image-models | timm/data/readers/reader_image_tar.py | .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... | 75 | 2,644 |
pytorch-image-models | timm/data/readers/reader_factory.py | .py | import os
from typing import Optional
from .reader_image_folder import ReaderImageFolder
from .reader_image_in_tar import ReaderImageInTar
def create_reader(
name: str,
root: Optional[str] = None,
split: str = 'train',
**kwargs,
):
kwargs = {k: v for k, v in kwargs.items() if v is... | 49 | 1,918 |
pytorch-image-models | timm/data/readers/class_map.py | .py | import os
import pickle
class _ClassMapUnpickler(pickle.Unpickler):
"""Restricted unpickler for `.pkl` class map files.
A class map is a plain ``{class_name: index}`` dict of built-in types, which never
triggers ``find_class``. Disallowing all globals therefore blocks arbitrary code
execution from a ... | 38 | 1,570 |
pytorch-image-models | timm/data/readers/reader_tfds.py | .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
import sys
from typing imp... | 356 | 17,909 |
pytorch-image-models | timm/data/readers/img_extensions.py | .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... | 51 | 1,482 |
pytorch-image-models | timm/data/readers/reader_hfids.py | .py | """ Dataset reader for HF IterableDataset
"""
import math
import os
from itertools import repeat, chain
from typing import Optional
import torch
import torch.distributed as dist
from PIL import Image
try:
import datasets
from datasets.distributed import split_dataset_by_node
from datasets.splits import Sp... | 220 | 8,409 |
pytorch-image-models | timm/data/readers/reader_hfds.py | .py | """ Dataset reader that wraps Hugging Face datasets
Hacked together by / Copyright 2022 Ross Wightman
"""
import io
import math
from typing import Optional
import torch
import torch.distributed as dist
from PIL import Image
try:
import datasets
except ImportError as e:
print("Please install Hugging Face data... | 103 | 3,262 |
pytorch-image-models | timm/data/readers/reader_wds.py | .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... | 467 | 16,976 |
pytorch-image-models | timm/data/readers/reader_image_in_tar.py | .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... | 249 | 10,165 |
pytorch-image-models | timm/data/readers/reader_image_folder.py | .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... | 100 | 3,508 |
pytorch-image-models | timm/data/readers/shared_count.py | .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
| 15 | 303 |
pytorch-image-models | timm/data/readers/reader.py | .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)... | 18 | 487 |
pytorch-image-models | timm/models/nfnet.py | .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/... | 1,190 | 45,753 |
pytorch-image-models | timm/models/visformer.py | .py | """ Visformer
Paper: Visformer: The Vision-friendly Transformer - https://arxiv.org/abs/2104.12533
From original at https://github.com/danczs/Visformer
Modifications and additions for timm hacked together by / Copyright 2021, Ross Wightman
"""
from typing import Optional, Union, Type, Any
import torch
import torch.... | 592 | 20,709 |
pytorch-image-models | timm/models/davit.py | .py | """ DaViT: Dual Attention Vision Transformers
As described in https://arxiv.org/abs/2204.03645
Input size invariant transformer architecture that combines channel and spacial
attention in each block. The attention mechanisms used are linear in complexity.
DaViT model defs and weights adapted from https://github.com/... | 954 | 32,770 |
pytorch-image-models | timm/models/vision_transformer_relpos.py | .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 List, Optional, Tuple, Type, Union
try:
from typing import Literal... | 743 | 30,435 |
pytorch-image-models | timm/models/nasnet.py | .py | """ NasNet-A (Large)
nasnetalarge implementation grabbed from Cadene's pretrained models
https://github.com/Cadene/pretrained-models.pytorch
"""
from functools import partial
from typing import Optional, Type
import torch
import torch.nn as nn
from timm.layers import ConvNormAct, create_conv2d, create_pool2d, creat... | 720 | 29,335 |
pytorch-image-models | timm/models/hgnet.py | .py | """ PP-HGNet (V1 & V2)
Reference:
https://github.com/PaddlePaddle/PaddleClas/blob/develop/docs/zh_CN/models/ImageNet1k/PP-HGNetV2.md
The Paddle Implement of PP-HGNet (https://github.com/PaddlePaddle/PaddleClas/blob/release/2.5.1/docs/en/models/PP-HGNet_en.md)
PP-HGNet: https://github.com/PaddlePaddle/PaddleClas/blob/r... | 853 | 27,737 |
pytorch-image-models | timm/models/_manipulate.py | .py | import collections.abc
import math
import re
from collections import defaultdict
from itertools import chain
from typing import Any, Callable, Dict, Iterator, List, Optional, Tuple, Type, Union
import torch
import torch.utils.checkpoint
from torch import nn as nn
from torch import Tensor
from timm.layers import use_r... | 347 | 12,698 |
pytorch-image-models | timm/models/shvit.py | .py | """SHViT
SHViT: Single-Head Vision Transformer with Memory Efficient Macro Design
Code: https://github.com/ysj9909/SHViT
Paper: https://arxiv.org/abs/2401.16456
@inproceedings{yun2024shvit,
author={Yun, Seokju and Ro, Youngmin},
title={SHViT: Single-Head Vision Transformer with Memory Efficient Macro Design},
bo... | 567 | 20,059 |
pytorch-image-models | timm/models/nextvit.py | .py | """ Next-ViT
As described in https://arxiv.org/abs/2207.05501
Next-ViT model defs and weights adapted from https://github.com/bytedance/Next-ViT, original copyright below
"""
# Copyright (c) ByteDance Inc. All rights reserved.
from functools import partial
from typing import List, Optional, Tuple, Union, Type
import... | 822 | 27,671 |
pytorch-image-models | timm/models/hub.py | .py | from ._hub import *
import warnings
warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.models", FutureWarning)
| 5 | 141 |
pytorch-image-models | timm/models/senet.py | .py | """
SEResNet implementation from Cadene's pretrained models
https://github.com/Cadene/pretrained-models.pytorch/blob/master/pretrainedmodels/models/senet.py
Additional credit to https://github.com/creafz
Original model: https://github.com/hujie-frank/SENet
ResNet code gently borrowed from
https://github.com/pytorch/v... | 543 | 20,138 |
pytorch-image-models | timm/models/xcit.py | .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 ... | 1,090 | 44,565 |
pytorch-image-models | timm/models/hieradet_sam2.py | .py | import math
from copy import deepcopy
from functools import partial
from typing import Dict, List, Optional, Tuple, Type, Union
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
from timm.layers import (
PatchEmbed,
Mlp,
Dr... | 701 | 25,214 |
pytorch-image-models | timm/models/gcvit.py | .py | """ Global Context ViT
From scratch implementation of GCViT in the style of timm swin_transformer_v2_cr.py
Global Context Vision Transformers -https://arxiv.org/abs/2206.09959
@article{hatamizadeh2022global,
title={Global Context Vision Transformers},
author={Hatamizadeh, Ali and Yin, Hongxu and Kautz, Jan and M... | 687 | 24,868 |
pytorch-image-models | timm/models/byoanet.py | .py | """ Bring-Your-Own-Attention Network
A flexible network w/ dataclass based config for stacking NN blocks including
self-attention (or similar) layers.
Currently used to implement experimental variants of:
* Bottleneck Transformers
* Lambda ResNets
* HaloNets
Consider all of the models definitions here as exper... | 478 | 19,779 |
pytorch-image-models | timm/models/selecsls.py | .py | """PyTorch SelecSLS Net example for ImageNet Classification
License: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/legalcode)
Author: Dushyant Mehta (@mehtadushy)
SelecSLS (core) Network Architecture as proposed in "XNect: Real-time Multi-person 3D
Human Pose Estimation with a Single RGB Camera, Mehta et al."... | 390 | 13,509 |
pytorch-image-models | timm/models/_builder.py | .py | import dataclasses
import logging
import os
from copy import deepcopy
from pathlib import Path
from typing import Any, Callable, Dict, List, Optional, Tuple, Type, TypeVar, Union
from torch import nn as nn
from torch.hub import load_state_dict_from_url
from timm.models._features import FeatureListNet, FeatureDictNet,... | 504 | 21,917 |
pytorch-image-models | timm/models/dpn.py | .py | """ PyTorch implementation of DualPathNetworks
Based on original MXNet implementation https://github.com/cypw/DPNs with
many ideas from another PyTorch implementation https://github.com/oyam/pytorch-DPNs.
This implementation is compatible with the pretrained weights from cypw's MXNet implementation.
Hacked together b... | 388 | 14,067 |
pytorch-image-models | timm/models/_hub.py | .py | 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 ... | 602 | 21,714 |
pytorch-image-models | timm/models/crossvit.py | .py | """ CrossViT Model
@inproceedings{
chen2021crossvit,
title={{CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification}},
author={Chun-Fu (Richard) Chen and Quanfu Fan and Rameswar Panda},
booktitle={International Conference on Computer Vision (ICCV)},
year={2021}
}
Paper l... | 655 | 26,079 |
pytorch-image-models | timm/models/deit.py | .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 ... | 424 | 19,055 |
pytorch-image-models | timm/models/ghostnet.py | .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... | 1,016 | 36,846 |
pytorch-image-models | timm/models/focalnet.py | .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... | 741 | 27,245 |
pytorch-image-models | timm/models/resnetv2.py | .py | """Pre-Activation ResNet v2 with GroupNorm and Weight Standardization.
A PyTorch implementation of ResNetV2 adapted from the Google Big-Transfer (BiT) source code
at https://github.com/google-research/big_transfer to match timm interfaces. The BiT weights have
been included here as pretrained models from their origina... | 1,193 | 45,851 |
pytorch-image-models | timm/models/repghost.py | .py | """
An implementation of RepGhostNet Model as defined in:
RepGhost: A Hardware-Efficient Ghost Module via Re-parameterization. https://arxiv.org/abs/2211.06088
Original implementation: https://github.com/ChengpengChen/RepGhost
"""
import copy
from functools import partial
from typing import List, Optional, Tuple, Unio... | 585 | 20,512 |
pytorch-image-models | timm/models/mambaout.py | .py | """
MambaOut models for image classification.
Some implementations are modified from:
timm (https://github.com/rwightman/pytorch-image-models),
MetaFormer (https://github.com/sail-sg/metaformer),
InceptionNeXt (https://github.com/sail-sg/inceptionnext)
"""
from collections import OrderedDict
from typing import List, Op... | 738 | 24,549 |
pytorch-image-models | timm/models/resnet.py | .py | """PyTorch ResNet
This started as a copy of https://github.com/pytorch/vision 'resnet.py' (BSD-3-Clause) with
additional dropout and dynamic global avg/max pool.
ResNeXt, SE-ResNeXt, SENet, and MXNet Gluon stem/downsample variants, tiered stems added by Ross Wightman
Copyright 2019, Ross Wightman
"""
import math
fro... | 2,267 | 104,102 |
pytorch-image-models | timm/models/eva.py | .py | """ EVA
EVA ViT from https://github.com/baaivision/EVA , paper: https://arxiv.org/abs/2211.07636
This file contains a number of ViT variants the utilise ROPE position embeddings, SwiGLU and other additions:
* EVA & EVA02 model implementations that evolved from BEiT, additional models in vision_transformer.py.
* `ti... | 3,261 | 122,388 |
pytorch-image-models | timm/models/densenet.py | .py | """Pytorch Densenet implementation w/ tweaks
This file is a copy of https://github.com/pytorch/vision 'densenet.py' (BSD-3-Clause) with
fixed kwargs passthrough and addition of dynamic global avg/max pool.
"""
import re
from collections import OrderedDict
from typing import Any, Dict, Optional, Tuple, Type, Union
impo... | 564 | 21,179 |
pytorch-image-models | timm/models/swin_transformer.py | .py | """ Swin Transformer
A PyTorch impl of : `Swin Transformer: Hierarchical Vision Transformer using Shifted Windows`
- https://arxiv.org/pdf/2103.14030
Code/weights from https://github.com/microsoft/Swin-Transformer, original copyright/license info below
S3 (AutoFormerV2, https://arxiv.org/abs/2111.14725) Swin weig... | 1,256 | 49,446 |
pytorch-image-models | timm/models/gemma4_vit.py | .py | """Gemma4 Vision Transformer
Vision encoder from Google's Gemma 4 multimodal model.
Custom ViT with 2D RoPE, Gated MLP, QKV normalization, and 4-norm sandwich blocks.
Paper: https://ai.google.dev/gemma/docs/core/model_card_4
Reference impl: https://github.com/huggingface/transformers (Gemma4VisionModel)
Copyright 20... | 1,486 | 60,250 |
pytorch-image-models | timm/models/_efficientnet_builder.py | .py | """ EfficientNet, MobileNetV3, etc Builder
Assembles EfficieNet and related network feature blocks from string definitions.
Handles stride, dilation calculations, and selects feature extraction points.
Hacked together by / Copyright 2019, Ross Wightman
"""
from typing import Callable, Optional
import logging
import ... | 582 | 24,025 |
pytorch-image-models | timm/models/naflexvit.py | .py | """ NaFlex Vision Transformer
An improved version of the Vision Transformer with:
1. Encapsulated embedding and position encoding in a single module
2. Support for linear patch embedding on pre-patchified inputs
3. Support for NaFlex variable aspect, variable resolution
4. Support for FlexiViT variable patch size
5. S... | 2,393 | 101,389 |
pytorch-image-models | timm/models/lcnetv2.py | .py | """ PP-LCNetV2
Reference:
https://github.com/PaddlePaddle/PaddleClas/blob/release/2.6/docs/en/models/PP-LCNetV2_en.md
The Paddle Implement of PP-LCNetV2 (https://github.com/PaddlePaddle/PaddleClas/blob/release/2.6/ppcls/arch/backbone/legendary_models/pp_lcnet_v2.py)
PP-LCNetV2 is a CPU oriented network built on PP-LC... | 483 | 18,308 |
pytorch-image-models | timm/models/convmixer.py | .py | """ ConvMixer
"""
from typing import Optional, Type
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 ._manipula... | 151 | 4,957 |
pytorch-image-models | timm/models/tiny_vit.py | .py | """ TinyViT
Paper: `TinyViT: Fast Pretraining Distillation for Small Vision Transformers`
- https://arxiv.org/abs/2207.10666
Adapted from official impl at https://github.com/microsoft/Cream/tree/main/TinyViT
"""
__all__ = ['TinyVit']
import itertools
from functools import partial
from typing import Dict, List, ... | 880 | 29,839 |
pytorch-image-models | timm/models/_pretrained.py | .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... | 95 | 3,525 |
pytorch-image-models | timm/models/convnext.py | .py | """ ConvNeXt
Papers:
* `A ConvNet for the 2020s` - https://arxiv.org/pdf/2201.03545.pdf
@Article{liu2022convnet,
author = {Zhuang Liu and Hanzi Mao and Chao-Yuan Wu and Christoph Feichtenhofer and Trevor Darrell and Saining Xie},
title = {A ConvNet for the 2020s},
journal = {Proceedings of the IEEE/CVF Confer... | 1,438 | 61,592 |
pytorch-image-models | timm/models/hiera.py | .py | """ An PyTorch implementation of Hiera
Adapted for timm from originals at https://github.com/facebookresearch/hiera
"""
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#... | 1,050 | 38,528 |
pytorch-image-models | timm/models/__init__.py | .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 .cpubone import *
from .crossvit import *
from .csatv2 import *
from .cspnet import *
from .davit import *
from .deit import *
from .dense... | 174 | 5,301 |
pytorch-image-models | timm/models/vision_transformer_sam.py | .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... | 784 | 29,095 |
pytorch-image-models | timm/models/fastvit.py | .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... | 1,808 | 62,739 |
pytorch-image-models | timm/models/dla.py | .py | """ Deep Layer Aggregation and DLA w/ Res2Net
DLA original adapted from Official Pytorch impl at: https://github.com/ucbdrive/dla
DLA Paper: `Deep Layer Aggregation` - https://arxiv.org/abs/1707.06484
Res2Net additions from: https://github.com/gasvn/Res2Net/
Res2Net Paper: `Res2Net: A New Multi-scale Backbone Architec... | 609 | 20,733 |
pytorch-image-models | timm/models/volo.py | .py | """ Vision OutLOoker (VOLO) implementation
Paper: `VOLO: Vision Outlooker for Visual Recognition` - https://arxiv.org/abs/2106.13112
Code adapted from official impl at https://github.com/sail-sg/volo, original copyright in comment below
Modifications and additions for timm by / Copyright 2022, Ross Wightman
"""
# Co... | 1,405 | 49,338 |
pytorch-image-models | timm/models/regnet.py | .py | """RegNet X, Y, Z, and more
Paper: `Designing Network Design Spaces` - https://arxiv.org/abs/2003.13678
Original Impl: https://github.com/facebookresearch/pycls/blob/master/pycls/models/regnet.py
Paper: `Fast and Accurate Model Scaling` - https://arxiv.org/abs/2103.06877
Original Impl: None
Based on original PyTorch... | 1,491 | 56,256 |
pytorch-image-models | timm/models/rexnet.py | .py | """ ReXNet
A PyTorch impl of `ReXNet: Diminishing Representational Bottleneck on Convolutional Neural Network` -
https://arxiv.org/abs/2007.00992
Adapted from original impl at https://github.com/clovaai/rexnet
Copyright (c) 2020-present NAVER Corp. MIT license
Changes for timm, feature extraction, and rounded channe... | 605 | 20,565 |
pytorch-image-models | timm/models/mvitv2.py | .py | """ Multi-Scale Vision Transformer v2
@inproceedings{li2021improved,
title={MViTv2: Improved multiscale vision transformers for classification and detection},
author={Li, Yanghao and Wu, Chao-Yuan and Fan, Haoqi and Mangalam, Karttikeya and Xiong, Bo and Malik, Jitendra and Feichtenhofer, Christoph},
booktitle={... | 1,157 | 41,367 |
pytorch-image-models | timm/models/_efficientnet_blocks.py | .py | """ EfficientNet, MobileNetV3, etc Blocks
Hacked together by / Copyright 2019, Ross Wightman
"""
from typing import Callable, Dict, Optional, Type, Union
import torch
import torch.nn as nn
from torch.nn import functional as F
from timm.layers import (
create_conv2d,
DropPath,
make_divisible,
create_a... | 762 | 27,300 |
pytorch-image-models | timm/models/mobilenetv3.py | .py | """ MobileNet V3
A PyTorch impl of MobileNet-V3, compatible with TF weights from official impl.
Paper: Searching for MobileNetV3 - https://arxiv.org/abs/1905.02244
Hacked together by / Copyright 2019, Ross Wightman
"""
from functools import partial
from typing import Any, Dict, Callable, List, Optional, Tuple, Union... | 1,527 | 61,760 |
pytorch-image-models | timm/models/_factory.py | .py | import re
from pathlib import Path
from typing import Any, Dict, Optional, Tuple, Union
from torch import nn
from timm.layers import set_layer_config
from ._helpers import load_checkpoint
from ._hub import load_model_config_from_hf, load_model_config_from_path
from ._pretrained import PretrainedCfg
from ._registry im... | 187 | 8,438 |
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