GitLab

* Add ValueError

* Add tests for ValueError

* Add tests for ValueError

* Add ValueError

* Change to if/else

* Ammend iou_fn tests

* Move code excerpt

* Format tests
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* update roipool to make in torch fx traceable

* update ps_roi_align, ps_roi_pool and roi_align to make them torch fx traceable

* add unittest

* Remove `.to(output_fx)` from test
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Fix typing jit issue on RoIPool and RoIAlign

* Fix nit.

* Address code review comments.

* Fix bug in calculating cIoU for unequal sizes

* Remove comment

* what the epsilon?

* Fixing DIoU

* Optimization by Francisco.

* Fix the expected values on CompleteBoxIoU

* Apply suggestions from code review
Co-authored-by: Abhijit Deo <72816663+abhi-glitchhg@users.noreply.github.com>

* Adding cartesian product test.

* remove static
Co-authored-by: Vasilis Vryniotis <vvryniotis@fb.com>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Abhijit Deo <72816663+abhi-glitchhg@users.noreply.github.com>

* Refactor tests

* Remove tol, fix comments

* Add tolerance only where necessary

* Add tolerance only where necessary

* Add tolerance only where necessary

* Refactor to adapt suggestions

* Refactor and add nits

* Refactor box area

* Refactor to one file

* Adapt almost all except area

* final update

* Tighten for jit

* Refactor slightly

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

* upgrade usort to

* Also update black

* Actually use 1.0.2

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

* 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>

* 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>

* reverting some recently introduced exceptions

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

* address PR comments

* replace one more assert with torch._assert:

* address PR comments

* make type checker happy

* Fix bug

* fix bug

* fix for wrong asserts

* attempt to make tests pass

* Fix test_ops tests

* Fix expected exception in tests

* fix typo

* fix tests and format

* fix flake8

* remove one last exception

* fix error

* remove unused immport

* replace fake returns by else
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* replace most asserts with exceptions

* fix formating issues

* fix linting and remove more asserts

* fix regresion

* fix regresion

* fix bug

* apply ufmt

* apply ufmt

* fix tests

* fix format

* fix None check

* fix detection models tests

* non scriptable any

* add more checks for None values

* fix retinanet test

* fix retinanet test

* Update references/classification/transforms.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update references/classification/transforms.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update references/optical_flow/transforms.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update references/optical_flow/transforms.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update references/optical_flow/transforms.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* make value checks more pythonic:

* Update references/optical_flow/transforms.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* make value checks more pythonic

* make more checks pythonic

* fix bug

* appy ufmt

* fix tracing issues

* fib typos

* fix lint

* remove unecessary f-strings

* fix bug

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

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

* Update torchvision/ops/boxes.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update torchvision/ops/poolers.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

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

* address PR comments

* Update torchvision/io/_video_opt.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update torchvision/models/detection/generalized_rcnn.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update torchvision/models/feature_extraction.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update torchvision/models/optical_flow/raft.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* address PR comments

* addressing further pr comments

* fix bug

* remove unecessary else

* apply ufmt

* last pr comment

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

* Create dropblock.py

* add dropblock2d

* fix pylint

* refactor dropblock

* add dropblock

* Rename dropblock.py to drop_block.py

* fix pylint

* add dropblock

* add dropblock3d

* add drop_block3d

* add dropblock

* Update drop_block.py

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

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

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

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

* Update drop_block.py

* Update drop_block.py

* import torch.fx

* fix lint

* fix lint

* Update drop_block.py

* improve dropblock

* add dropblock

* refactor dropblock

* fix doc

* remove the limitation of block_size

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

* fix lint

* fix lint

* add dropblock

* Fix linter

* add dropblock random check

* reduce test time

* Update test_ops.py

* speed the dropblock test

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

* Refactor BoxOps tests to use parameterize

* Refactor BoxOps tests to use parameterize

* Refactor BoxOps to use parameterize, addressed comments from PR#5380

* Refactor BoxOps to use parameterize, addressed minor styling comments from PR#5380

* Refactor BoxOps to use parameterize, addressed typing errorsfrom PR#5380

* Refactor BoxOps to use parameterize, addressed minor naming comments for PR#5380

* Remove APIs that were deprecated before 0.8

* More stuff

* Some more

* oops

making torchvision ops leaf nodes by default

* adding multiweight support for deeplabv3 prototype models

* adding default values for optional params

* fixing bug

* addressing PR comment

* fixing seed in test_batched_nms_implementations

* change seeds in test_batched_nms_implementations

* change seeds in test_batched_nms_implementations

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

* Fix flakiness on the TestStochasticDepth test.

* Fix minor bug when p=1.0

* Remove device and dtype setting.

* 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.

* 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>

Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

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

* Adding operator.

* Adding tests

* switching order of `p` and `mode`.

* Remove seed setting.

* Replace stats import with pytest.importorskip.

* Fix doc

* Apply suggestions from code review
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Fixing indentation.

* Adding operator in the documentation.

* Fixing lint
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

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

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

* hello

* Try with DYLD_FALLBACK_LIBRARY_PATH
Co-authored-by: Edgar Andrés Margffoy Tuay <andfoy@gmail.com>

* WIP

* clang

* docs

* extracted out common utils

* Use better quantization function and pass tensors as parameters

* proper dequantization

* Some tests

* Dequantization optimization, seems to gain a few ms

* clang-format

* again

* more correct test. Had to remove optimization although it almost works

* Also test aligned=True

* remove useless part

* more docs and comments

* Put back optimization with more robust test

* Added check for index upper bound

* avoid possible overflow

* Move common function into common.h

* oops

* scale=1,zero_point=0 makes more sense

* Force batch size of 1 to prevent any indexingbug

* format

* format again

* updated docstring

* put back description comment for pre_calc_bilinear_interpolate

* revert most changes to docstring as it's taken care of in another PR

* Add quantized version of nms

* Added tests

* Compute areas only once

* remove calls to dequantize_val

* fix return type for empty tensor

* flake8

* remove use of scale as it gets cancelled out

* simpler int convertion in tests

* explicitly set ovr to double

* add tests for more values of scale and zero_point

* comment about underflow

* remove unnecessary accessor

* properly convert to float for division

* Add comments about underflow

* explicitely cast coordinates to float to allow vectorization

* clang

* clang  again

* hopefully OK now