GitLab

* Adding ciou and diou support in `_box_loss()`

* Fix linter

* Addressing comments for nits

* 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

* 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>

* 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>

* 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

* 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>

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

* refactor doc

* refactor code

* add fcos.rst

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

* docs: Added MaskRCNN to new doc

* docs: Updated docstring

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

* Add revamped docs for video classification models

* EOL

* docs: Added entry for MobileNet V2 in new doc

* docs: Updated MobileNetV2 docstring

* docs: Fixed docstring
Co-authored-by: FG Fernandez <–26927750+frgfm@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>

* Document MobileNetV3 quantization approach

* Change the URL.

* [DOC] Add alexnet new documentation.

* [FIX] Fix wrong alexnet header.

* [FIX] Fix the AlexNet paper link.
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Start doc revamp for detection models

* Minor cleanup

* Use list of tuples for metrics