GitLab

* Remove `(N, T, H, W, C) => (N, T, C, H, W)` conversion on presets

* Update docs.

* Fix the tests

* Use `output_format` for `read_video()`

* Use `output_format` for `Kinetics()`

* Adding input descriptions on presets

Throw warning for empty masks or box tensors on draw_segmentation_masks and draw_bounding_boxes (#5857)

* Fixing the IndexError in draw_segmentation_masks

* fixing the bug on draw_bounding_boxes

* Changing fstring to normal string

* Removing unecessary conversion

* Adding test for the change

* Adding a test for draw seqmentation mask

* Fixing small mistake

* Fixing an error in the tests

* removing useless imports

* ufmt
Co-authored-by: LEGRAND Matthieu <legrand.ma@chu-toulouse.fr>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Add swin on hubconfig.

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

* add swin_s and swin_b variants

* fix swin_b params

* fix n parameters and acc numbers

* adding missing acc numbers

* apply ufmt

* Updating `_docs` to reflect training recipe

* Fix exted for swin_b
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Classif models

* Detection

* Segmentation

* quantization

* Video

* optical flow

* tests

* Fix docs

* Fix Video dataset

* Consistency for RAFT dataset names

* use ImageNet-1K

* Use COCO-val2017-VOC-labels for segmentation

* formatting

* Adding docs for quantized models.

* Adding docs for video models.

* Adding docs for segmentation models.

* Adding docs for optical flow models.

* Adding docs for detection models.

* Fix typo.

* Make changes from code-review.

* Improving the auto-gen doc.

* Adding details for AlexNet, ConvNext, DenseNet, EfficientNets, GoogLeNet and InceptionV3.

* Fixing location of `_docs`

* Adding docs in the remaining classification models.

* Fix linter

* simplify OnlineResource.load

* [PoC] merge mock data preparation and loading

* Revert "cache mock data based on config"

This reverts commit 5ed6eedef74865e0baa746a375d5ec1f0ab1bde7.

* Revert "[PoC] merge mock data preparation and loading"

This reverts commit d62747962f9ed6a7b0b80849e7c971efabb5d3da.

* remove preprocess returning a new path in favor of querying twice

* address test comments

* clarify comment

* mypy

* use builtin decompress utility

* merge mock data preparation and loading

* address comments

* fix extra file creation

* remove tmp folder

* inline images meta creation in coco mock data

* Requested here https://github.com/pytorch/vision/pull/5898#discussion_r864765799

.

* Fix tests

* ufmt, not black
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* rely on patched datasets home rather than passing it around

* add comment

* POC

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

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

* Fix tests

* ufmt

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

* [FEAT] Add distance IoU and distance IoU loss + some tests (WIP for tests).

* [FIX] Remove URL from docstring + remove assert since it causes a big performance drop.

* [FIX] eps isn't None.

* [TEST] Update existing box dIoU test + add dIoU loss tests (inspired from cIoU ones).

* [ENH] Some pre-commit fixes + remove print + mypy.

* [ENH] Pass the device in the assertion for the dIoU loss test.

* [FIX] Remove type hints from the dIoU box test.

* [ENH] Refactor box and loss for dIoU functions + fix half tests.

* [FIX] Precommits fix.

* [ENH] Some improvement for the distance IoU tests thanks to code review.

* [ENH] Upcast in distance boxes computation to avoid overflow.

* [ENH] Revert the refactor of distance IoU loss back since it introduced a bug and can be slow.

* Precommit fix.

* [FIX] Few changes introduced by merge conflict.

* Add code reference

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

* [proto] Added `center_crop_bounding_box` functional op

* Fixed mypy issue

* Added one more test case

* More test cases

* Added functional `perspective_bounding_box`/`perspective_segmentation_mask` ops

* Added more comments and added a code to assert denom != 0

* Put larger r/a tolerence when matching bboxes

* Update transforms for PIL deprecation

* Changes agreed at pytorch/vision#5898

* black, sort constants, version check

* Format tests

* Square brackets

* Update torchvision/transforms/_pil_constants.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* 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

* feat: add functional pad on segmentation mask

* test: add basic correctness test with random masks

* test: add all padding options

* fix: pr comments

* fix: tests

* refactor: reshape tensor in 4d, then pad
Co-authored-by: Federico Pozzi <federico.pozzi@argo.vision>

* added ciou loss

* "formatting with flake8 and ufmt"

* formatting with ufmt and flake8

* minor changes

* changes as per the suggestions

* added reference in torchvision/ops/__init__.py

* sample test

* tests formatted

* added description

* formatting

* edited tests

* changes in tests

* added tests for multiple boxes

* minor edits

* minor edit

* doc added

* minor edits

* Update test_ops.py

* formatting test file

* changes as per the suggestions

* formatting and adding some more tests

* bounding box added

* removed unnecessary comment

* added docstring

* added type annotations

* removed potential bug

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

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

* Update test/test_ops.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* fix test_data_loader on Windows and macOS

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

* 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>

* 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>

* Fixed issue with padding on CI

* Disabled failing tests with color_jitter

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

* [proto] Added crop_bounding_box op

* Added `crop_segmentation_mask` op

* Fixed failed mypy

* Added tests for resized_crop_bounding_box

* Fixed code formatting

* Added resized_crop_segmentation_mask op

* Added tests

* [proto] Added crop_bounding_box op

* Added tests for resized_crop_bounding_box

* Fixed code formatting

* test: add functional vertical flip tests on segmentation mask

* refactor: improve test readibility

* Update test_prototype_transforms_functional.py
Co-authored-by: Federico Pozzi <federico.pozzi@argo.vision>
Co-authored-by: vfdev <vfdev.5@gmail.com>

* Restructuring metrics meta-data for detection, segmentation and optical flow.

* Renaming acc to pixel_acc for segmentation

* Restructure video meta-data.

* Restructure classification and quantization meta-data.

* Fix tests.

* Fix documentation

* Added `crop_segmentation_mask` op

* Fixed failed mypy

* Removing `task`, `architecture` and `quantization`

* Fix mypy

* Remove size field

* Remove unused import.

* Fix mypy

* Remove size from schema list.

* update todo

* Simplify with assert

* Adding min_size to all models.

* Update RAFT min size to 128

* Remove publication_year and interpolation meta

* Add type to _COMMON_META and _COMMON_SWAG_META to prevent error from mypy check

* Remove test to check interpolation and publication_year meta
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* add warning if font is not set

* added quotes

* added changes after review

* Apply suggestions from code review
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* escaped warning string

* Apply suggestions from code review
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* updated warning message in test

* refactored code

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

* Add test for giou_loss

* Use standard assert for integer comparison
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Fix ufmt format and add log after assert
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Add test for sigmoid_focal_loss

* Update test/test_ops.py

Improve code by using torch.testing.make_tensor
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Update test/test_ops.py

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

* Update test/test_ops.py

Refactor code for generating inputs and targets
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Improve focal_loss test code suggested on comment by Philip

* Use fuser2 to prevent fuser bug

* Combine function to generate input, dont set the fuser when device is cpu

* Add github issue for the fuser problem
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* [proto] Added crop_bounding_box op

* Removed "pass"

* Updated comment

* Removed unused args from signature

* refactor prototype datasets to inherit from IterDataPipe (#5448)

* refactor prototype datasets to inherit from IterDataPipe

* depend on new architecture

* fix missing file detection

* remove unrelated file

* reinstante decorator for mock registering

* options -> config

* remove passing of info to mock data functions

* refactor categories file generation

* fix imagenet

* fix prototype datasets data loading tests (#5711)

* reenable serialization test

* cleanup

* fix dill test

* trigger CI

* patch DILL_AVAILABLE for pickle serialization

* revert CI changes

* remove dill test and traversable test

* add data loader test

* parametrize over only_datapipe

* draw one sample rather than exhaust data loader

* cleanup

* trigger CI

* migrate VOC prototype dataset (#5743)

* migrate VOC prototype dataset

* cleanup

* revert unrelated mock data changes

* remove categories annotations

* move properties to constructor

* readd homepage

* migrate CIFAR prototype datasets (#5751)

* migrate country211 prototype dataset (#5753)

* migrate CLEVR prototype datsaet (#5752)

* migrate coco prototype (#5473)

* migrate coco prototype

* revert unrelated change

* add kwargs to super constructor call

* remove unneeded changes

* fix docstring position

* make kwargs explicit

* add dependencies to docstring

* fix missing dependency message

* Migrate PCAM prototype dataset (#5745)

* Port PCAM

* skip_integrity_check

* Update torchvision/prototype/datasets/_builtin/pcam.py
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

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

* Migrate DTD prototype dataset (#5757)

* Migrate DTD prototype dataset

* Docstring

* Apply suggestions from code review
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Migrate GTSRB prototype dataset (#5746)

* Migrate GTSRB prototype dataset

* ufmt

* Address comments

* Apparently mypy doesn't know that __len__ returns ints. How cute.

* why is the CI not triggered??

* Update torchvision/prototype/datasets/_builtin/gtsrb.py
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* migrate CelebA prototype dataset (#5750)

* migrate CelebA prototype dataset

* inline split_id

* Migrate Food101 prototype dataset (#5758)

* Migrate Food101 dataset

* Added length

* Update torchvision/prototype/datasets/_builtin/food101.py
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Migrate Fer2013 prototype dataset (#5759)

* Migrate Fer2013 prototype dataset

* Update torchvision/prototype/datasets/_builtin/fer2013.py
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Migrate EuroSAT prototype dataset (#5760)

* Migrate Semeion prototype dataset (#5761)

* migrate caltech prototype datasets (#5749)

* migrate caltech prototype datasets

* resolve third party dependencies

* Migrate Oxford Pets prototype dataset (#5764)

* Migrate Oxford Pets prototype dataset

* Update torchvision/prototype/datasets/_builtin/oxford_iiit_pet.py
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* migrate mnist prototype datasets (#5480)

* migrate MNIST prototype datasets

* Update torchvision/prototype/datasets/_builtin/mnist.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Migrate Stanford Cars prototype dataset (#5767)

* Migrate Stanford Cars prototype dataset

* Address comments

* fix category file generation (#5770)

* fix category file generation

* revert unrelated change

* revert unrelated change

* migrate cub200 prototype dataset (#5765)

* migrate cub200 prototype dataset

* address comments

* fix category-file-generation

* Migrate USPS prototype dataset (#5771)

* migrate SBD prototype dataset (#5772)

* migrate SBD prototype dataset

* reuse categories

* Migrate SVHN prototype dataset (#5769)

* add test to enforce __len__ is working on prototype datasets (#5742)

* reactivate special dataset tests

* add missing annotation

* Cleanup prototype dataset implementation (#5774)

* Remove Dataset2 class

* Move read_categories_file out of DatasetInfo

* Remove FrozenBunch and FrozenMapping

* Remove test_prototype_datasets_api.py and move missing dep test somewhere else

* ufmt

* Let read_categories_file accept names instead of paths

* Mypy

* flake8

* fix category file reading
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* update prototype dataset README (#5777)

* update prototype dataset README

* fix header level

* Apply suggestions from code review
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.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