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Co-authored-by: Nicolas Hug <nicolashug@meta.com>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* fix typos throughout the code base

* fix grammar

* revert formatting changes to gallery

* revert 'an uXX'

* remove 'number of the best'

* Fixing inverted center_crop check on Classification preset

* Remove the `--train-center-crop` flag.

* Added maxvit architecture and tests

* rebased + addresed comments

* Revert "rebased + addresed comments"

This reverts commit c5b28398cd48d2f3403c7c8eeefbaba9df05fcfe.

* Re-added model changes after revert

* aligned with partial original implementation

* removed submitit script fixed lint

* mypy fix for too many arguments

* updated old tests

* removed per batch lr scheduler and seed setting

* removed ontap

* added docs, validated weights

* fixed test expect, moved shape assertions in the begging for torch.fx compatibility

* mypy fix

* lint fix

* added legacy interface

* added weight link

* updated docs

* Update references/classification/train.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Update torchvision/models/maxvit.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* adressed comments

* update ra_maginuted and augmix_severity default values

* adressed some comments

* remove input_channels parameter
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Expose on Hub the public methods of the registration API

* Limit methods and update docs.

* Update references to use the new Model Registration API

* add swin transformer

* Update swin_transformer.py

* Update swin_transformer.py

* fix lint

* fix lint

* refactor code

* add swin_transformer

* Update swin_transformer.py

* fix bug

* refactor code

* fix lint

* update init_weights

* move shift_window into attention

* refactor code

* fix bug

* Update swin_transformer.py

* Update swin_transformer.py

* fix lint

* add patch_merge

* fix bug

* Update swin_transformer.py

* Update swin_transformer.py

* Update swin_transformer.py

* refactor code

* Update swin_transformer.py

* refactor code

* fix lint

* refactor code

* add swin_tiny

* add swin_tiny.pkl

* fix lint

* Delete ModelTester.test_swin_tiny_expect.pkl

* add swin_tiny

* add

* add Optional to bias

* update init weights

* update init_weights and add no weight decay

* add no weight decay

* add set_weight_decay

* add set_weight_decay

* fix lint

* fix lint

* add lr_cos_min

* add other swin models

* Update torchvision/models/swin_transformer.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* refactor doc

* Update utils.py

* Update train.py

* Update train.py

* Update swin_transformer.py

* update model builder

* fix lint

* add

* Update torchvision/models/swin_transformer.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Update torchvision/models/swin_transformer.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* update other model

* simplify the model name just like ViT

* add lr_cos_min

* fix lint

* fix lint

* Update swin_transformer.py

* Update swin_transformer.py

* Update swin_transformer.py

* Delete ModelTester.test_swin_tiny_expect.pkl

* add swin_t

* refactor code

* Update train.py

* add swin_s

* ignore a error of mypy

* Update swin_transformer.py

* fix lint

* add swin_b

* add swin_l

* refactor code

* Update train.py

* move relative_position_bias to __init__

* fix formatting

* Revert "fix formatting"

This reverts commit 41faba232668f7ac4273a0cf632c0d0130c7ce9c.

* Revert "move relative_position_bias to __init__"

This reverts commit f0615440bf18617dc0e5dc4839bd5ed27e5ed010.

* refactor code

* Remove deprecated meta-data from `_COMMON_META`

* fix linter

* add pretrained weights for swin_t

* fix format

* apply ufmt

* add documentation

* update references README

* adding new style docs

* update pre-trained weights values

* remove other variants

* fix typo

* Remove expect for the variants not yet supported
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Joao Gomes <jdsgomes@fb.com>

* add set_weight_decay

* Update _utils.py

* refactor code

* fix import

* add set_weight_decay

* fix lint

* fix lint

* replace split_normalization_params with set_weight_decay

* simplfy the code

* refactor code

* refactor code

* fix lint

* remove unused

* Update test_ops.py

* Update train.py

* Update _utils.py

* Update train.py

* add set_weight_decay

* add set_weight_decay

* Update _utils.py

* Update test_ops.py

* Change `--transformer-weight-decay` to `--transformer-embedding-decay`
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Detection recipe enhancements

* Add back nesterov momentum

* Moving basefiles outside of prototype and porting Alexnet, ConvNext, Densenet and EfficientNet.

* Porting googlenet

* Porting inception

* Porting mnasnet

* Porting mobilenetv2

* Porting mobilenetv3

* Porting regnet

* Porting resnet

* Porting shufflenetv2

* Porting squeezenet

* Porting vgg

* Porting vit

* Fix docstrings

* Fixing imports

* Adding missing import

* Fix mobilenet imports

* Fix tests

* Fix prototype tests

* Exclude get_weight from models on test

* Fix init files

* Porting googlenet

* Porting inception

* porting mobilenetv2

* porting mobilenetv3

* porting resnet

* porting shufflenetv2

* Fix test and linter

* Fixing docs.

* Porting Detection models (#5617)

* fix inits

* fix docs

* Port faster_rcnn

* Port fcos

* Port keypoint_rcnn

* Port mask_rcnn

* Port retinanet

* Port ssd

* Port ssdlite

* Fix linter

* Fixing tests

* Fixing tests

* Fixing vgg test

* Porting Optical Flow, Segmentation, Video models (#5619)

* Porting raft

* Porting video resnet

* Porting deeplabv3

* Porting fcn and lraspp

* Fixing the tests and linter

* Porting docs, examples, tutorials and galleries (#5620)

* Fix examples, tutorials and gallery

* Update gallery/plot_optical_flow.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Fix import

* Revert hardcoded normalization

* fix uncommitted changes

* Fix bug

* Fix more bugs

* Making resize optional for segmentation

* Fixing preset

* Fix mypy

* Fixing documentation strings

* Fix flake8

* minor refactoring
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Resolve conflict

* Porting model tests (#5622)

* Porting tests

* Remove unnecessary variable

* Fix linter

* Move prototype to extended tests

* Fix download models job

* Update CI on Multiweight branch to use the new weight download approach (#5628)

* port Pad to prototype transforms (#5621)

* port Pad to prototype transforms

* use literal

* Bump up LibTorchvision version number for Podspec to release Cocoapods (#5624)
Co-authored-by: Anton Thomma <anton@pri.co.nz>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* pre-download model weights in CI docs build (#5625)

* pre-download model weights in CI docs build

* move changes into template

* change docs image

* Regenerated config.yml
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Anton Thomma <11010310+thommaa@users.noreply.github.com>
Co-authored-by: Anton Thomma <anton@pri.co.nz>

* Porting reference scripts and updating presets (#5629)

* Making _preset.py classes

* Remove support of targets on presets.

* Rewriting the video preset

* Adding tests to check that the bundled transforms are JIT scriptable

* Rename all presets from *Eval to *Inference

* Minor refactoring

* Remove --prototype and --pretrained from reference scripts

* remove  pretained_backbone refs

* Corrections and simplifications

* Fixing bug

* Fixing linter

* Fix flake8

* restore documentation example

* minor fixes

* fix optical flow missing param

* Fixing commands

* Adding weights_backbone support in detection and segmentation

* Updating the commands for InceptionV3

* Setting `weights_backbone` to its fully BC value (#5653)

* Replace default `weights_backbone=None` with its BC values.

* Fixing tests

* Fix linter

* Update docs.

* Update preprocessing on reference scripts.

* Change qat/ptq to their full values.

* Refactoring preprocessing

* Fix video preset

* No initialization on VGG if pretrained

* Fix warning messages for backbone utils.

* Adding star to all preset constructors.

* Fix mypy.
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Anton Thomma <11010310+thommaa@users.noreply.github.com>
Co-authored-by: Anton Thomma <anton@pri.co.nz>

* Refactor preset transforms

* Making presets public.

* Add is_qat support using a method getter

* Switch to an internal _fuse_modules

* Fix linter.

* Pass is_qat=False on PTQ

* Fix bug on ra_sampler flag.

* Set is_qat=True for QAT

* Adding prototype flag on reference scripts.

* Import prototype instead of models/transforms.

* Correcting exception type.

* fixing none referencing

Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* support random seed used to shuffle the sampler

* fix bug for RA samper
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Adding repaeted data-augument sampler

* rebase on top of latest main

* fix formatting

* rename file

* adding coode source

* Change the `default` weights mechanism to sue Enum aliases.

* Change `get_weights` to work with full Enum names and make it public.

* Applying improvements from code review.

* Add multi-type support on get_weight.

* Fix bug on method call.

* Adding logging suffix for QAT.

Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* fix bug in amp

* fix bug in training by amp

* support use gradient clipping when amp is enabled
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Prabhat Roy <prabhatroy@fb.com>

* [references] Adding gradient clipping

* ufmt formatting

* remove apex code

* resolve naming issue

* Adding multi-weight support to Quantized ResNet.

* Update references script to support testing quantized models with the new API.

* Handle quantized models correctly in ref script.

* Fixing references for quantization.

Co-authored-by: Nicolas Hug <nicolashug@fb.com>

* Update model checkpoint for resnet50.

* Add get_weight method to retrieve weights from name.

* Update the references to support prototype weights.

* Fixing mypy typing.

* Switching to a python 3.6 supported equivalent.

* Add unit-test.

* Add optional num_classes.

* Add type to default argument

To resolve issue #4694

* Resolve issue #4694

Add missing types on argument parser

* Update with ufmt

formatted with ufmt

* Updated with review

Updated with review

* Update type of arguments

Add train.py from video_classification, similarity and train_quantization.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Update EMA every X iters.

* Adding AdamW optimizer.

* Adjusting EMA decay scheme.

* Support custom weight decay for Normalization layers.

* Fix identation bug.

* Change EMA adjustment.

* Quality of life changes to faciliate testing

* ufmt format

* Fixing imports.

* Adding FixRes improvement.

* Support EMA in store_model_weights.

* Adding interpolation values.

* Change train_crop_size.

* Add interpolation option.

* Removing hardcoded interpolation and sizes from the scripts.

* Fixing linter.

* Incorporating feedback from code review.

* Updated classification reference script to use torch.cuda.amp

* Assigned scaler to None if amp is False

* Fixed linter errors

* add ufmt as code formatter

* cleanup

* quote ufmt requirement

* split imports into more groups

* regenerate circleci config

* fix CI

* clarify local testing utils section

* use ufmt pre-commit hook

* split relative imports into local category

* Revert "split relative imports into local category"

This reverts commit f2e224cde2008c56c9347c1f69746d39065cdd51.

* pin black and usort dependencies

* fix local test utils detection

* fix ufmt rev

* add reference utils to local category

* fix usort config

* remove custom categories sorting

* Run pre-commit without fixing flake8

* got a double import in merge
Co-authored-by: Nicolas Hug <nicolashug@fb.com>

* Adding ExponentialLR and LinearLR

* Fix arg type of --lr-warmup-decay

* Adding support of Zero gamma BN and SGD with nesterov.

* Fix --lr-warmup-decay for video_classification.

* Update bn_reinit

* Fix pre-existing bug on num_classes of model

* Remove zero gamma.

* Use fstrings.

* Warmup on Classficiation references.

* Adjust epochs for cosine.

* Warmup on Segmentation references.

* Warmup on Video classification references.

* Adding support of both types of warmup in segmentation.

* Use LinearLR in detection.

* Fix deprecation warning.

* Add RandomMixupCutmix.

* Add test with real data.

* Use dataloader and collate in the test.

* Making RandomMixupCutmix JIT scriptable.

* Move out label_smoothing and try roll instead of flip

* Adding mixup/cutmix in references script.

* Handle one-hot encoded target in accuracy.

* Add support of devices on tests.

* Separate Mixup from Cutmix.

* Add check for floats.

* Adding device on expect value.

* Remove hardcoded weights.

* One-hot only when necessary.

* Fix linter.

* Moving mixup and cutmix to references.

* Final code clean up.

* Update log message.

* Update fstring.

* Added Exponential Moving Average support to classification reference script

* Addressed review comments

* Updated model argument