GitLab

* 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>

* Convert weights only if `old_key` is in `state_dict`

* Fix linter

* Minor updates to optical flow ref for consistency

* Actually put back name

* linting

* First PR for model doc revamp

* Deactivating fail on warning, temporarily

* Remove commnet

* Minor changes

* Typos

* Added TODO in Makefile

* Keep old models.rst file intact, move new docs into new models_new.rst file

* Added docs LOL

* First PR for model doc revamp

* Deactivating fail on warning, temporarily

* Remove commnet

* Minor changes

* Typos

* Added TODO in Makefile

* Keep old models.rst file intact, move new docs into new models_new.rst file

the assert msg should be same
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>

To resolve issue #5815
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Update focal_loss.py

updated docstring for the `sigmoid_focal_loss`

* edited docstring of focal_loss

* Update focal_loss.py

* fix doc style.

* formatting

* formatting

* minor edits

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

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

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

There is a mistake in FGVCAircraft dataset documentation. If you load dataset and sum up 'trainval' and 'test' splits, there are not 10 200, but 10 000 images. Also mistake is in the number of classes: if we choose `annotation_level` to be `variant`, then unique number of classes is going to be not 102, but 100, and with `manufacturer` level it is not 41, but 30.
Co-authored-by: Nicolas Hug <contact@nicolas-hug.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>

As Ubuntu-1604 runners will no longer be available in early May 2022
Update `ubuntu-1604:201903-01` to `ubuntu-2004:202104-01`
and `ubuntu-1604-cuda-10.2:202012-01` to `ubuntu-2004-cuda-11.4:202110-01`
Per [CircleCI Configuration reference](https://circleci.com/docs/2.0/configuration-reference/)

* Add SWAG model that only the linear classifier head is finetuned with frozen trunk weight

* Add accuracy from experiments

* Change name from SWAG_LC to SWAG_LINEAR

* Add comment on SWAG_LINEAR weight

* Remove the comment docs (moved to PR description), and add the PR url as recipe. Also change name of previous swag model to SWAG_E2E_V1

* Update _register_onnx_ops.py

* Update misc.py

* 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>

* Add MaskRCNN improved weights

* Adding recipe URL

* Add FasterRCNN improved weights

* Add recipe URL

* Update publication_year field

* Add RetinaNet improved weights

* Add weights.

* Change publication date.

* 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>

* port image type conversion transforms to prototype API

* implement proposal for image type conversion

* add deprecation warnings

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

* Add regnet_y_128gh_swag weight

* Add default weight for regnet_y_128gf

* Add the accuracy from experiments

* Added functional affine_bounding_box op with tests

* Updated comments and added another test case

* Update _geometry.py

* Added affine_segmentation_mask with tests

* Fixed device mismatch issue
Added a cude/cpu test
Reduced the number of test samples

* Added test_correctness_affine_segmentation_mask_on_fixed_input

* Updates according to the review

* Replaced [None, ...] by [None, :]

* Adressed review comments

* Fixed formatting and more updates according to the review

* Fixed bad merge

* WIP

* Fixed tests

* Updated warning message

Signed-off-by: Kyle Chen <kylechen@amd.com>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* [FEAT] Start implementing Food101 using the new datasets API. WIP.

* [FEAT] Generate Food101 categories and start the test mock.

* [FEAT] food101 dataset code seems to work now.

* [TEST] food101 mock update.

* [FIX] Some fixes thanks to running food101 tests.

* [FIX] Fix mypy checks for the food101 file.

* [FIX] Remove unused numpy.

* [FIX] Some changes thanks to code review.

* [ENH] More idomatic dataset code thanks to code review.

* [FIX] Remove unused cast.

* [ENH] Set decompress and extract to True for some performance gains.

* [FEAT] Use the preprocess=decompress keyword.

* [ENH] Use the train and test.txt file instead of the .json variants and simplify code + update mock data.

* [ENH] Better food101 mock data generation.

* [FIX] Remove a useless print.
Co-authored-by: Philip Meier <github.pmeier@posteo.de>