GitLab

* [WIP] Added unified input perspective transformation code

* Unified input for F.perspective
- added tests
- updated docs

* Added more random test configs

* Fixed the code according to PR's review

* Added code for F_t.rotate with test
- updated F.affine tests

* Rotate test tolerance to 2%

* Fixes failing test

* [WIP] RandomRotation

* Unified RandomRotation with tests

* Added code for F_t.rotate with test
- updated F.affine tests

* Rotate test tolerance to 2%

* Fixes failing test

* Optimized _expanded_affine_grid with a single matmul op

* Recoded _compute_output_size

* [WIP] recoded F_t.rotate internal methods

* [WIP] Fixed F.affine to support rectangular images

* Recoded _gen_affine_grid to optimized version ~ affine_grid
- Fixes flake8

* [WIP] Use _gen_affine_grid for affine and rotate

* Fixed tests on square / rectangular images for affine and rotate ops

* Removed redefinition of F.rotate
- due to bad merge

* Added code for F_t.rotate with test
- updated F.affine tests

* Rotate test tolerance to 2%

* Fixes failing test

* Optimized _expanded_affine_grid with a single matmul op

* Recoded _compute_output_size

* fix type hints and move degenerate boxes to a function in torchvision.models.detection.generalized_rcnn

* format code

* format code

* changed to static method

* revert imports

* changed to method

* revert procedure for degenerating boxes

* Fixed resize to only match the smaller edge when an int is given instead of always

* Added test cases for resize()

* add typehints for torchvision.datasets.stl10

* move annotation from class to instance scope

* Clarify scaling of ToTensor transform for target masks in the documentation

* Add link to the segmentation reference
Co-authored-by: vfdev <vfdev.5@gmail.com>
Co-authored-by: vfdev <vfdev.5@gmail.com>

* enable mypy for torchvision.datasets and ignore existing errors

* imagenet

* utils

* lint

* fix fill parameter for PIL pad

* add test

* fix

* lint

* [WIP] Unified input for T.RandomAffine

* Unified inputs for T.RandomAffine transformation

* Update transforms.py

* Updated docs of F.affine fillcolor

* Update transforms.py

* Update transform.py

* Update transform.py

* add torchscriptable adjust_gamma transform

https://github.com/pytorch/vision/issues/1375



* changes based on code-review

* Apply suggested change to add type hint

Required by mypy, even thought technically incorrect due to possible Image parameter. torchscript doesn't support a union based type hint.
Co-authored-by: vfdev <vfdev.5@gmail.com>
Co-authored-by: vfdev <vfdev.5@gmail.com>

* [WIP] F.affine

* [WIP] F.affine + tests

* Unified input for F.affine

* Removed commented code

* Removed unused imports

* Add corruption cases

* Read jpeg headers until exhaustion

* Minor error correction

* Add test script

* Raise exception when image is truncated

* Add test

* Skip damaged_jpeg folder

* Compare against basename

* Remove unused test file

Incoherence is when affine transformation is 90 degrees rotation and output contains a zero line

* Fix wrong clamping in RoIAlign with aligned=True

* Fix silly mistake

* Bugfix pointed out during code-review

* Fixes Xiao's repro

* Ports nms to use full dispatcher

* Move HIPGuard to nms_cuda

* clang-format

* run models in test_models.py on GPU if available

* Francisco's comment, also disable cuda model tests to see if CPU alone still passes

* cuda tests now pass locally, although still not comparing to saved numerics

* add note for thing to ask francisco

* Allow cuda and cpu tests to share a data file

* ignore suffix if unneeded

* Skip autocast numerics checks for a few models

* Add roi_align test
Co-authored-by: Michael Carilli <mcarilli@nvidia.com>