GitLab

* remove explicit install of Pillow throughout CI

* explicitly install zlib in windows conda env

* check pillow on Windows

* move check into conda env

* fix

* more debug output

* more debug

* add debug also to linux

* retry w/ and w/o packaging third party library

* tag debug

* more debug

* pin setuptools < 61

* install setuptools from pip

* cleanup

* try remove one more
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Add Docs for QuantizedGoogleNet

* ufmt

* Use explicit _QuantizedWeights or _Weights suffix

* [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>

* Fixing AlexNet references

* Fix doc rendering

* [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

* [ROCm] Upgrade to rocm5.1.1

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

* Add mask rcnn to instance segmentation

* Add docs a use nicolas suggestion

* remov param

* remov docsstring, edit docs

* Add one section level
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Document Keypoint RCNN separately

* Move Keypoint detection into its own section

* ufmt

* Remove references to non-existing weights

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

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

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

* docs: Added SSD300 to the new doc

To resolve #5897

* Minor fixes

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

* Change code to reduce variance in eval

* Remove unnecessary new line

* Fix missing import warnings

* Fix the warning on video_classification

* Fix bug to get len of UniformClipSampler

* updating mnasnet docs

* fix bug

* fix lint

* fix end of file

* fix linting

* Add missing weights
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Update ShuffleNetV2 docstring

* Add entry for ShuffleNet V2 in new doc

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

* init

* init

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

* Update torchvision/models/detection/faster_rcnn.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Add inception

* Fix googlenet bug

* Fix bug add file

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

* add docs

* Small fix

* Update docs/source/models/lraspp.rst
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* docs: Added FCN to new doc

* docs: Updated docstring

* docs: Fixed docstring

* Update docs/source/models/fcn.rst
Co-authored-by: Aditya Oke <47158509+oke-aditya@users.noreply.github.com>

* Apply suggestions from code review
Co-authored-by: FG Fernandez <–26927750+frgfm@users.noreply.github.com>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Aditya Oke <47158509+oke-aditya@users.noreply.github.com>

* docs: Added SSDLite to new doc

* docs: Updated docstring

* docs: Fixed docstring

* Apply suggestions from code review
Co-authored-by: FG Fernandez <–26927750+frgfm@users.noreply.github.com>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Add *_FOUND macros to CMakeLists.txt

* Remove NVJPEG as it fails CI
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* 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>

* Add shufflenetv2 1.5 and 2.0 weights

* Update recipe

* Add to docs

* Use resize_size=232 for eval and update the result

* Add quantized shufflenetv2 large

* Update docs and readme

* Format with ufmt

* Add to hubconf.py

* Update readme for classification reference

* Fix reference classification readme

* Fix typo on readme

* Update reference/classification/readme

* add Windows and macOS CI jobs for prototype tests

* fix CircleCI config

* cleanup

* use 3.8 as base to surface errors

* try using bash explicitly

* cleanup

* try test reports

* debug

* disable CircleCI

* add write permissions for write

* expand permissions

* try move permissions on job rather than global

* debug

* always debug

* maximum permissions

* cleanup

* cleanup

* 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>

* Start adding

* Finish adding docs

* Fix other bugs

* Update torchvision/models/mobilenetv3.py

* Update torchvision/models/mobilenetv3.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* init

* minor change

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

* Custom class for weights table

* Proper CSS

* 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>