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Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Nicolas Hug <nh.nicolas.hug@gmail.com>

Signed-off-by: Edward Z. Yang <ezyang@meta.com>
Co-authored-by: Nicolas Hug <nh.nicolas.hug@gmail.com>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

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

Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: vfdev <vfdev.5@gmail.com>

* fix typos throughout the code base

* fix grammar

* revert formatting changes to gallery

* revert 'an uXX'

* remove 'number of the best'

* update tests

* revert replacing expect

* test_detection_model freeze_rng_state

* update tests

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

* update test_models.py

* update tests

* fix linting

* fix linting

* add comment

* Trigger CI
Co-authored-by: YosuaMichael <yosuamichael@fb.com>

* Revert "Bump tol for autocasted `fasterrcnn_resnet50_fpn` (#6601)"

This reverts commit a4f53308.

* Temporarily remove FasterRCNN autocast test

* ADD: init_weights config for googlenet

* Fix: Inception and googlenet warnings

* Fix: warning in test_datasets.py

* Fix: Formatting error with ufmt

* Fix: Failing tests in quantized_classification_model

* Update test/test_models.py to make googlenet in 1 line
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Refactor: Change inception quantisation class initialization to use args/kwargs

* Resolve mypy issue

* Move *args before inception_blocks

* Move args keywords before other arguments
Co-authored-by: Ambuj Pawar <your_email@abc.example>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

Not sure what have changed between CUDA-11.3 and CUDA-11.6, but bumping tolerance keeps tests green

* Skip big models per platform/device

* Specifying skips on Windows only.

* Simplify and clean up code.

* Move output to CPU before assert_expected

* Fixing `test_detection_model`

* check_device=False

* linter

* S3D initial commit

* add model builder code and docstrings

* change classifier submodule, populate weights enum

* fix change of block args from List[List[int]] to ints

* add VideoClassification to transforms

* edit weights url for testing, add s3d to models.video init

* norm_layer changes

* norm_layer and args fix

* Overwrite default dropout

* Remove docs from internal submodules.

* Fix tests

* Adding documentation.

* Link doc from main models.rst

* Fix min_temporal_size

* Adding crop/resize parameters in references script

* Release weights.

* Refactor dropout.

* Adding the weights table in the doc
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Vasilis Vryniotis <vvryniotis@fb.com>

* init submit

* fix typo

* support ufmt and mypy

* fix 2 unittest errors

* fix ufmt issue

* Apply suggestions from code review
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* unify codes

* fix meshgrid indexing

* fix a bug

* fix type check

* add type_annotation

* add slow model

* fix device issue

* fix ufmt issue

* add expect pickle file

* fix jit script issue

* fix type check

* keep consistent argument order

* add support for pretrained_window_size

* avoid code duplication

* a better code reuse

* update window_size argument

* make permute and flatten operations modular

* add PatchMergingV2

* modify expect.pkl

* use None as default argument value

* fix type check

* fix indent

* fix window_size (temporarily)

* remove "v2_" related prefix and add v2 builder

* remove v2 builder

* keep default value consistent with official repo

* deprecate dropout

* deprecate pretrained_window_size

* fix dynamic padding edge case

* remove unused imports

* remove doc modification

* Revert "deprecate dropout"

This reverts commit 8a13f932815ae25655c07430d52929f86b1ca479.

* Revert "fix dynamic padding edge case"

This reverts commit 1c7579cb1bd7bf2f0f94907f39bee6ed707a97a8.

* remove unused kwargs

* add downsample docs

* revert block default value

* revert argument order change

* explicitly specify start_dim

* add small and base variants

* add expect files and slow_models

* Add model weights and documentation for swin v2

* fix lint

* fix end of files line
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Joao Gomes <jdsgomes@fb.com>

* Extending to support MViTv2

* Fix docs, mypy and linter

* Refactor the relative positional code.

* Code refactoring.

* Rename vars.

* Update docs.

* Replace assert with exception.

* Updat docs.

* Minor refactoring.

* Remove the square input limitation.

* Moving methods around.

* Modify the shortcut in the attention layer.

* Add ported weights.

* Introduce a `residual_cls` config on the attention layer.

* Make the patch_embed kernel/padding/stride configurable.

* Apply changes from code-review.

* Remove stale todo.

* Make test precision stricter for Classification

* Update classification threshold.

* Update quantized classification threshold.

* Model registration mechanism.

* Add overwrite options to the dataset prototype registration mechanism.

* Adding example models.

* Fix module filtering

* Fix linter

* Fix docs

* Make name optional if same as model builder

* Apply updates from code-review.

* fix minor bug

* Adding getter for model weight enum

* Support both strings and callables on get_model_weight.

* linter fixes

* Fixing mypy.

* Renaming `get_model_weight` to `get_model_weights`

* Registering all classification models.

* Registering all video models.

* Registering all detection models.

* Registering all optical flow models.

* Fixing mypy.

* Registering all segmentation models.

* Registering all quantization models.

* Fixing linter

* Registering all prototype depth perception models.

* Adding tests and updating existing tests.

* Fix linters

* Fix tests.

* Add beta annotation on docs.

* Fix tests.

* Apply changes from code-review.

* Adding documentation.

* Fix docs.

* upgrade usort to

* Also update black

* Actually use 1.0.2

* Apply pre-commit
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Adding MViT v2 architecture (#6105)

* Adding mvitv2 architecture

* Fixing memory issues on tests and minor refactorings.

* Adding input validation

* Adding docs and minor refactoring

* Add `min_temporal_size` in the supported meta-data.

* Switch Tuple[int, int, int] with List[int] to support easier the 2D case

* Adding more docs and references

* Change naming conventions of classes to follow the same pattern as MobileNetV3

* Fix test breakage.

* Update todos

* Performance optimizations.

* Add support to MViT v1 (#6179)

* Switch implementation to v1 variant.

* Fix docs

* Adding back a v2 pseudovariant

* Changing the way the network are configured.

* Temporarily removing v2

* Adding weights.

* Expand _squeeze/_unsqueeze to support arbitrary dims.

* Update references script.

* Fix tests.

* Fixing frames and preprocessing.

* Fix std/mean values in transforms.

* Add permanent Dropout and update the weights.

* Update accuracies.

* Fix documentation

* Remove unnecessary expected file.

* Skip big model test

* Rewrite the configuration logic to reduce LOC.

* Fix mypy

* Validate against expected files on videos

* Plus tests for autocast

* Add swin on hubconfig.

* Add swin b/s in the `slow_models` list.

* Add resnext101_64x4d model definition

* Add test for resnext101_64x4d

* Add resnext101_64x4d weight

* Update checkpoint to use EMA weigth

* Add quantization model signature for resnext101_64x4d

* Fix class name and update accuracy using 1 gpu and batch_size=1

* Apply ufmt

* Update the quantized weight and accuracy that we still keep the training log

* Add quantized expect file

* Update docs and fix acc1

* Add recipe for quantized to PR

* Update models.rst

* Skip big model in test

* Let get_models_from_module func to read skipped_models from global directly instead of function param to reduce changes

* Also skip regnet_y_128gf

* Only skip test for test_classification_model and create toggle using env var

* Remove unnecessary comment

* Fix comparison of device to use str

* Add logic to test_classification_model directly

* Add kprcnn in autocast flaky list
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Add swin_t to slow list

* apply ufmt

* update expect for swin_t
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Use frozen BN only if pre-trained.

* Add LSJ and ability to from scratch training.

* Fixing formatter

* Adding `--opt` and `--norm-weight-decay` support in Detection.

* Fix error message

* Make ScaleJitter proportional.

* Adding more norm layers in split_normalization_params.

* Add FixedSizeCrop

* Temporary fix for fill values on PIL

* Fix the bug on fill.

* Add RandomShortestSize.

* Skip resize when an augmentation method is used.

* multiscale in [480, 800]

* Add missing star

* Add new RetinaNet variant.

* Add tests.

* Update expected file for old retina

* Fixing tests

* Add FrozenBN to retinav2

* Fix network initialization issues

* Adding BN support in MaskRCNNHeads and FPN

* Adding support of FasterRCNNHeads

* Introduce norm_layers in backbone utils.

* Bigger RPN head + 2x rcnn v2 models.

* Adding gIoU support to retinanet

* Fix assert

* Add back nesterov momentum

* Rename and extend `FastRCNNConvFCHead` to support arbitrary FCs

* Fix linter

* Add vit_b_16_swag

* Better handling idiom for image_size, edit test_extended_model to handle case where number of param differ from default due to different image size input

* Update the accuracy to the experiment result on torchvision model

* Fix typo missing underscore

* raise exception instead of torch._assert, add back publication year (accidentally deleted)

* Add license information on meta and readme

* Improve wording and fix typo for pretrained model license in readme

* Add vit_l_16 weight

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

* Update the accuracy meta on vit_l_16_swag model to result from our experiment

* Add vit_h_14_swag model

* Add accuracy from experiments

* Add to vit_h_16 model to hubconf.py

* Add docs and expected pkl file for test

* Remove legacy compatibility for ViT_H_14 model
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Test vit_h_14 with smaller image_size to speedup the test
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>