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* revamp log api usage method

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

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

* Adding test that verifies meta schema.

* Adding missing interpolation to keypoint model.

* Change assertion.

* Adding map metric in meta schema for detection and renaming metrics for kp and mask rcnn.

* add download functionality to prototype datasets

* fix annotation

* fix test

* remove iopath

* add comments

* Revert "[FBcode->GH] remove unused requests functionality (#5014)"

This reverts commit 33123bee.

* Revert "replace requests with urllib (#4973)"

This reverts commit 8d25de7b.

* add requests as hard dependency

* install library stubs in CI

* fix syntax

* add requests to conda dependencies

* fix mypy CI

* Adding logging calls for raft and vit

* Linter fix

* simplify model builders

* cleanup

* refactor kwonly to pos or kw handling

* put weight verification back

* revert num categories checks

* fix default weights

* cleanup

* remove manual parameter map

* refactor decorator interface

* address review comments

* cleanup

* refactor callable default

* fix type annotation

* process ungrouped models

* cleanup

* mroe cleanup

* use decorator for detection models

* add decorator for quantization models

* add decorator for segmentation  models

* add decorator for video  models

* remove old helpers

* fix resnet50

* Adding verification back on InceptionV3

* Add kwargs in DeeplabeV3

* Add kwargs on FCN

* Fix typing on Deeplab

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

* exclude windows from mmap

* add comment for windows

* appease mypy

According to the benchmark link https://github.com/pytorch/vision/issues/1311#issuecomment-781329339

, for GPU the threshold should be higher (which is why detectron2 used 40k).
This PR changes the threshold to be device dependent.
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Add bias parameter to ConvNormActivation

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

Co-authored-by: Prabhat Roy <prabhatroy@fb.com>

making torchvision ops leaf nodes by default

* improve COCO prototype

* test 2017 annotations

* add option to include captions

* fix categories and add tests

* cleanup

* add correct image size to bounding boxes

* fix annotation collation

* appease mypy

* add benchmark

* always use image as reference

* another refactor

* add support for segmentations

* add support for segmentations

* fix CI dependencies

* Change the `default` weights mechanism to sue Enum aliases.

* Change `get_weights` to work with full Enum names and make it public.

* Applying improvements from code review.

* Fix bug on autocontrast when `min==max`

* Adding PIL vs TorchVision test for min==max

* Rename classes Weights => WeightsEnum and WeightEntry => Weights.

* Make enum values follow the naming convention `_V1`, `_V2` etc

* Cleanup the Enum class naming conventions.

* Add a test to check naming conventions.

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

* Update functional_tensor.py

To resolve issue #4818
Add assert function and logic after checking bound of image

* Update functional_tensor.py

* Update test

* Update test_functional_tensor.py

* Update test_functional_tensor.py

* Update test_functional_tensor.py

* Update test_functional_tensor.py

* Update test_functional_tensor.py

* Update test_functional_tensor.py

* Update test_functional_tensor.py

* Update test_functional_tensor.py

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

* [vit] Adding ViT to torchvision/models

* adding pre-logits layer + resolving comments

* Fix the model attribute bug

* Change version to arch

* fix failing unittests

* remove useless prints

* reduce input size to fix unittests

* Increase windows-cpu executor to 2xlarge

* Use `batch_first=True` and remove classifier

* Change resource_class back to xlarge

* Remove vit_h_14

* Remove vit_h_14 from __all__

* Move vision_transformer.py into prototype

* Fix formatting issue

* remove arch in builder

* Fix type err in model builder

* address comments and trigger unittests

* remove the prototype import in torchvision.models

* Adding vit back to models to trigger CircleCI test

* fix test_jit_forward_backward

* Move all to prototype.

* Adopt new helper methods and fix prototype tests.

* Remove unused import.
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Vasilis Vryniotis <vvryniotis@fb.com>

* Updated the link for densenet recipe.

* Set default value of `num_classes` and `num_keypoints` to `None`

* Provide helper methods for parameter checks to reduce duplicate code.

* Throw errors on silent config overwrites from weight meta-data and legacy builders.

* Changing order of arguments + fixing mypy.

* Make the builders fully BC.

* Add "default" weights support that returns always the best weights.

* style: Fixed last missing typing annotation

* style: Fixed typing

* style: Fixed remaining typing annotations

* style: Fixed typing

* style: Fixed typing

* refactor: Removed unused import

* Update torchvision/datasets/video_utils.py
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Prabhat Roy <prabhatroy@fb.com>

* don't close file handles in protoype dataset tests

* remove file closing from decoder
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

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

* change to stable sort in nms implementations