GitLab

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

* Fixed return docstrings

* Added some refs and corrected some parts

* more refs, and a note about dtypes
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* bump to 5.3.0

* Also make 3.6 CI runs rely on 5.3.0

* docs for resize

* address comment: describe antialiasing

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

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

* add _all for autoaugment

* adds docs

* add docs, test locally

* refactored as per code review

* use bincount instead of hist

* only use bincount when on CPU

* Added equality test for CPU vs cuda

* Fix flake8 and tests

* tuple instead of int for size

* WIP, still needs tests and docs

* tests

* flake8

* Docs + fixed some tests

* proper error messages

* fixed origin head

* fixed inconsistent casting

* updated functional_tensor.py

Modified the .to() method to convert_image_dtype() method.

* Apply suggestions from code review
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* deprecate _video modules

* flake8
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

Fixes #3393

* aspect ratio must be a sampling from log scale.
reference from: https://github.com/pytorch/vision/blob/8317295c1d272e0ba7b2ce31e3fd2c048235fc73/torchvision/transforms/transforms.py#L833-L836



* add random erasing unittest code

* Increased threshold for difference in sampling rate

* move outside of the loop

* log_ratio move outside of the loop. RandomResizedCrop also
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Renamed original method to test center crop

* Added test method, docs and added padding when imgsize < cropsize.

* BugFix - keep odd_crop_size odd

* Do not crop when image size after padding matches crop size; updated test.
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* initial fix

* fill=0

* docstrings

* fill type check

* fill type check

* set None to zero

* unit tests

* set instead of NotImplemented

* fix W293
Co-authored-by: vfdev <vfdev.5@gmail.com>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

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

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

* Simplify code and remove used vars.

* Simplify expressions and remove used parenthesis.

* Jit fixes.

* Making check more readable.

* fixing styles

* adjust_hue

* adjust_*

* colorjitter

* Initial doc clean-up

* Remove all private docs

* Rename files

* Highlight backend inconsistencies

* Sequence and number

* [Need checking] AutoAugment related doc change

* Revert name changes

* added the helper method for dimension checks

* unit tests for dimensio check function in functional_tensor

* code formatting and typing

* moved torch image check after tensor check

* unit testcases for test_assert_image_tensor added and refactored

* separate unit testcase file deleted

* assert_image_tensor added to newly created 6 methods

* test cases added for new 6 mthohds

* removed wrongly pasted posterize method and added solarize method for testing
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Replacing all torch.jit.annotations with typing

* Replacing remaining typing

* 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>

This has been fixed in PyTorch in https://github.com/pytorch/pytorch/pull/40897

accimage always stores images as uint8, so let's be compatible with the internal representation. Tests were failing without this as it would return a float32 image normalized between 0-1

We could have errors such as aten/src/ATen/native/cpu/PowKernel.cpp:41:5:  runtime error: 5.7896e+76 is outside the range of representable values of type 'float'

* Fixing upperbound value on tests and documentation.

* Limit the number of channels on adjust_* transoforms.