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* add tests for prototype datasets API

* add pytest-mock as test dependency

* remove unnecessary fixtures

* Apply suggestions from code review
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* address first batch of review comments

* remove dynamic class generation

* aggregate similar tests

* split immutable tests once again

* removed unused fixture

* remove re.escape usages

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

* Add logging to torchvision ops

* Hack to make torchscript work

* Bugfix

* Bugfix

* Lint

* mypy... let's silence it

* Fighting with mymy

* One more try

Summary:
This diff enables ImageNet to be usable from within torchvision.

It implements a different codepath for some families of datasets that can be sharded into multiple pieces, and uses it if within fbcode.

For now all previously supported datasets are also supported (MNIST, CIFAR and FashionMNIST), in addition to ImageNet.

Pull Request resolved: https://github.com/pytorch/vision/pull/4776

Reviewed By: datumbox

Differential Revision: D31929684

fbshipit-source-id: 58f9fe2ed6ce731a6b43a38be912983247eff562
(cherry picked from commit b43fead8ea5164e37637ade0e80477e94f993365)

* Update readme for new torch

* Fix typo

It's FBcode, not FBCode

* Adding multiweight support for shufflenetv2 prototype models

* Revert "Adding multiweight support for shufflenetv2 prototype models"

This reverts commit 31fadbee7d1a65cd73ae43dfd4ac6e97e7ca7b01.

* Adding multiweight support for shufflenetv2 prototype models

* Revert "Adding multiweight support for shufflenetv2 prototype models"

This reverts commit 4e3d900f796c1e3e667312087e77956ca4a4c017.

* Adding multiweight support for shufflenetv2 prototype models

* addressing PR comment

* Show git diff after lint run

* break both flake8 and ufmt

* Make it run on fail

* Undo breaks and fix job message.

* [WIP] Added script to sync fbcode changes with main branch

* Make unique branches for multiple runs of the script

* Updated the files

* Change echo message

* Addressed review comments

* Removed from_repo command line argument

* Make fork_main_branch optional

* 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

* Add mutli-weight support for VideoResNet.

* Fix linter.

* Minor refactoring.

* Update comments.

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

* setting 100 seeds

* back to 10 seeds

* Trying with 100 seeds

* Change seeds from 100 to 10

* setting 100 seeds, let's see if it fails

* Passed with 100, so setting 10

* adding multiweight support for deeplabv3 prototype models

* adding default values for optional params

* fixing bug

* addressing PR comment

* Change test_random_apply

* Change test_random_choice

* Change test_randomness

* took care of RandomVert/HorizFlip

* take care of RandomGrayScale

* minor cleanup

* avoid 0 degree rotation just in case

* Fix flakiness on the TestStochasticDepth test.

* Fix minor bug when p=1.0

* Remove device and dtype setting.

* cache dataset info

* try loading categories file by default
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Adding multi-weight support to LRASPP

* Adding tests for segmentation models.

* Skip segmentation test by default.

Relocate fails to find nvjpeg unless its present in the library search path.

* Refactoring tests.

* Fixing lint.

* Skip tests for models that don't have weights.

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

* replace np.frombuffer with torch.frombuffer in MNIST prototype

* cleanup

* appease mypy

* more cleanup

* clarify inplace offset

* fix num bytes for floating point data

Summary:
Pull Request resolved: https://github.com/pytorch/vision/pull/4718



As title

Reviewed By: hanton

Differential Revision: D31853335

fbshipit-source-id: 7e8afb7280bbdf81418dfbdfc329ab49837ea42e
Co-authored-by: Yuchen Huang <hyc@fb.com>

Summary:
Pull Request resolved: https://github.com/pytorch/vision/pull/4620

Pull Request resolved: https://github.com/pytorch/nestedtensor/pull/455



Fixes missing kernel guards as identified by D30072495

Reviewed By: jingsh, xush6528

Differential Revision: D31553158

fbshipit-source-id: 80de017ba2ddc52e2a684df9b3eae5de84ed49f4
Co-authored-by: Richard Barnes <rbarnes@fb.com>

Summary:
Pull Request resolved: https://github.com/pytorch/vision/pull/4571



Fixing windows build for `torchvision` when `MOBILE` is defined. In `csrc/vision.cpp`, since `PyMODINIT_FUNC` depends on `Python.h` I added the same condition for `PyMODINIT_FUNC` as the one for `import <PyTorch.h>`.

Reviewed By: malfet

Differential Revision: D31488734

fbshipit-source-id: fd52a9ab161288d9c8bf3b9e0ab9da856a4ebadb
Co-authored-by: Mengwei Liu <larryliu@fb.com>

* fix cuda installation failure in packaging

* rm stop windows upgrade

* Update cuda_install.bat
Co-authored-by: Nikita Shulga <nshulga@fb.com>

* Removed unnecessary if from setup.py

* Removed empty line

* Update model checkpoint for resnet50.

* Add get_weight method to retrieve weights from name.

* Update the references to support prototype weights.

* Fixing mypy typing.

* Switching to a python 3.6 supported equivalent.

* Add unit-test.

* Add optional num_classes.

Summary: As titled.

Reviewed By: sallysyw

Differential Revision: D31813675

fbshipit-source-id: 8ff879be172530bcc41aae5d71c67e1e90f09cbf
Co-authored-by: Kai Zhang <kaizh@fb.com>