GitLab

* 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>

* Fixed issue with padding on CI

* Disabled failing tests with color_jitter

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

Also, remove reference to conda-forge, all CUDA toolchain should be
available from NVIDIA channel

Install h5py from pip on Windows and skip failing gaussian_blur tests if Win+CUDA11.3 is used

* Adding basic augmix implementation.

* Finish the implementation.

* Add tests and documentation.

* Fix tests.

* Simplify code.

* Speed optimizations.

* Per image weights instead of per batch.

* Fix tests.

* Update torchvision/transforms/autoaugment.py
Co-authored-by: vfdev <vfdev.5@gmail.com>

* Changing the default severity value to get by default the same strength as RandAugment.
Co-authored-by: vfdev <vfdev.5@gmail.com>

* Added ref tests for shear X/Y

* Added PIL tests and fixed tan(level) difference

* Updated tests

* Fixed reparam for shear X/Y in autoaugment

* Fixed arc_level -> level as atan is applied internally

* Fixed links

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

* setting 100 seeds

* back to 10 seeds

* add ufmt as code formatter

* cleanup

* quote ufmt requirement

* split imports into more groups

* regenerate circleci config

* fix CI

* clarify local testing utils section

* use ufmt pre-commit hook

* split relative imports into local category

* Revert "split relative imports into local category"

This reverts commit f2e224cde2008c56c9347c1f69746d39065cdd51.

* pin black and usort dependencies

* fix local test utils detection

* fix ufmt rev

* add reference utils to local category

* fix usort config

* remove custom categories sorting

* Run pre-commit without fixing flake8

* got a double import in merge
Co-authored-by: Nicolas Hug <nicolashug@fb.com>

* Add autouse fixture to save and reset RNG in tests

* Add other RNG generators

* delete freeze_rng_state

* Hopefully fix GaussianBlur test

* Alternative fix, probably better

* revert changes to test_models
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* update channels parameter to every calling to check_functional_vs_PIL_vs_scripted

* update adjust_saturation

* update docstrings for functional transformations

* parametrize channels

* update docstring of ColorJitter class

* move channels to class's parameter

* remove testing channels for geometric transforms

* revert redundant changes

* revert redundant changes

* update grayscale test cases for randaugment, autoaugment, trivialaugment

* update docstrings of randaugment, autoaugment, trivialaugment

* update docstring of ColorJitter

* fix adjust_hue's docstring

* change test equal tolerance

* refactor grayscale tests

* make get_grayscale_test_image private

* Initial Proposal

* Tensor Save Test + Test Name Fix

* Formatting + removing unused argument

* fix old argument

* fix isnan check error + indexing error with jit

* Fix Flake8 error.

* Fix MyPy error.

* Fix Flake8 error.

* Fix PyTorch JIT error in UnitTests due to type annotation.

* Fixing tests.

* Removing type ignore.

* Adding support of ta_wide in references.

* Move methods in classes.

* Moving new classes to the bottom.

* Specialize to TA to TAwide

* Add missing type

* Fixing lint

* Fix doc

* Fix search space of TrivialAugment.
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Vasilis Vryniotis <vvryniotis@fb.com>

* Adding randaugment implementation

* Refactoring.

* Adding num_magnitude_bins.

* Adding FIXME.

* Replace in test_datasets*

* Replace in test_image.py

* Replace in test_transforms_tensor.py

* Replace in test_internet.py and test_io.py

* get_list_of_videos is util function still use get_tmp_dir

* Fix get_list_of_videos siginiture

* Add get_tmp_dir import

* Modify test_datasets_video_utils.py for test to pass

* Fix indentation

* Replace get_tmp_dir in util functions in test_dataset_sampler.py

* Replace get_tmp_dir in util functions in test_dataset_video_utils.py

* Move get_tmp_dir() to datasets_utils.py and refactor

* Fix pylint, indentation and imports

* import shutil to common_util.py

* Fix function signiture

* Remove get_list_of_videos under context manager

* Move get_list_of_videos to common_utils.py

* Move get_tmp_dir() back to common_utils.py

* Fix pylint and imports
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

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

Co-authored-by: Meghan Lele <meghanl@fb.com>

Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Make crop work the same for pil and tensor

* Only call pad if needed in functional_tensor.crop

* Fix top-left functional_tensor.crop

* Update document for functional.crop

* Add other test cases of functional.crop

* Fix bug

* Fixing formattter

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

* fix test

* more robust test

* flake8
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* WIP, still needs tests and docs

* tests

* flake8

* Docs + fixed some tests

* proper error messages

Summary:
Pull Request resolved: https://github.com/pytorch/vision/pull/3422

In CUDA-10.1 or below it is a no-op, but few of the tests will start to fail if update to 10.2 or newer, for example:
```
torchvision/transforms/transforms.py", line 1043, in forward
    transformed_tensor = torch.mm(flat_tensor, self.transformation_matrix)
RuntimeError: Deterministic behavior was enabled with either `torch.use_deterministic_algorithms(True)` or `at::Context::setDeterministicAlgorithms(true)`, but this operation is not deterministic because it uses CuBLAS and you have CUDA >= 10.2. To enable deterministic behavior in this case, you must set an environment variable before running your PyTorch application: CUBLAS_WORKSPACE_CONFIG=:4096:8 or CUBLAS_WORKSPACE_CONFIG=:16:8. For more information, go to https://docs.nvidia.com/cuda/cublas/index.html#cublasApi_reproducibility


```

Reviewed By: meyering

Differential Revision: D26563045

fbshipit-source-id: 65e5fabc8cdb471a72f931df55389ed7c0063e54
Co-authored-by: Nikita Shulga <nshulga@fb.com>

* Speedup test_ucf101 (#2623 

* Speedup Cmake builds (#3186)

* Speedup test_autoaugment (#3190)

* Speedup DeformConvTester (#3191)

* Speedup InceptionV3 and GoogleNet on Windows (#3196)

* Invert Transform (#3104)

* Adding invert operator.

* Make use of the _assert_channels().

* Update upper bound value.

* Remove private doc from invert, create or reuse generic testing methods to avoid duplication of code in the tests. (#3106)

* Create posterize transformation and refactor common methods to assist reuse. (#3108)

* Implement the solarize transform. (#3112)

* Implement the adjust_sharpness transform (#3114)

* Adding functional operator for sharpness.

* Adding transforms for sharpness.

* Handling tiny images and adding a test.

* Implement the autocontrast transform. (#3117)

* Implement the equalize transform (#3119)

* Implement the equalize transform.

* Turn off deterministic for histogram.

* Fixing test. (#3126)

* Force ratio to be float to avoid numeric overflows on blend. (#3127)

* Separate the tests of Adjust Sharpness from ColorJitter. (#3128)

* Add AutoAugment Policies and main Transform (#3142)

* Separate the tests of Adjust Sharpness from ColorJitter.

* Initial implementation, not-jitable.

* AutoAugment passing JIT.

* Adding tests/docs, changing formatting.

* Update test.

* Fix formats

* Fix documentation and imports.

* Apply changes from code review:
- Move the transformations outside of AutoAugment on a separate method.
- Renamed degenerate method for sharpness for better clarity.

* Update torchvision/transforms/functional.py
Co-authored-by: vfdev <vfdev.5@gmail.com>

* Apply more changes from code review:
- Add InterpolationMode parameter.
- Move all declarations away from AutoAugment constructor and into the private method.

* Update documentation.

* Apply suggestions from code review
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Apply changes from code review:
- Refactor code to eliminate as any to() and clamp() as possible.
- Reuse methods where possible.
- Apply speed ups.

* Replacing pad.
Co-authored-by: vfdev <vfdev.5@gmail.com>
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Fill color support for tensor affine transforms

* PEP fix

* Docstring changes and float support

* Docstring update for transforms and float type cast

* Cast only for Tensor

* Temporary patch for lack of Union type support, plus an extra unit test

* More plausible bilinear filling for tensors

* Keep things simple & New docstrings

* Fix lint and other issues after merge

* make it in one line

* Docstring and some code modifications

* More tests and corresponding changes for transoforms and docstring changes

* Simplify test configs

* Update test_functional_tensor.py

* Update test_functional_tensor.py

* Move assertions
Co-authored-by: vfdev <vfdev.5@gmail.com>

[BC-breaking] Introduced InterpolationModes and deprecated arguments: resample and fillcolor (#2952)

* Deprecated arguments: resample and fillcolor
Replaced by interpolation and fill

* Updates according to the review

* Added tests to check warnings and asserted BC

* [WIP] Interpolation modes

* Added InterpolationModes enum

* Added supported for int values for interpolation for BC

* Removed useless test code

* Fix flake8

- fixed problem with error computation between results
- refactored tensor cast for resize
- fixed round usage