GitLab

* Minor docs improvement

* Replaced link by already defined `filters`_

* [WIP] Unify random resized crop

* Unify input for RandomResizedCrop

* Fixed bugs and updated test

* Added resized crop functional test
- fixed bug with size convention

* Fixed incoherent sampling

* Fixed torch randint review remark

* [WIP] F.resize with tensor

* Adapted T.Resize and F.resize with a test

* According to the review, fixed copy-pasted messages and unused imports

* Related to #2292
- RandomErasing is not scriptable

* Fixed code according to review comments
- added additional checking of value vs img num_channels

* [WIP] Added symmetric padding mode

* Added check and raise error if padding is negative for symmetric padding mode

* Added test check for raising error if negative pad

- RandomCrop: crop with padding using all commonly supported modes

* F_t add factor nonnegativity checks for adjust_*

* Update functional_tensor.py

* Update functional_tensor.py

* Update functional_tensor.py

* Update functional_tensor.py

* [WIP] functional_tensor supports more padding modes

* [WIP] Support all padding modes

* Removed wip symmetric mode

* Improvements according to the review

* [WIP] Unified Tensor/PIL crop

* Fixed misplaced type annotation

* Fixed tests
- crop with padding
- other tests using mising private functions: _is_pil_image, _get_image_size

* Unified CenterCrop and F.center_crop
- sorted includes in transforms.py
- used py3 annotations

* Unified FiveCrop and F.five_crop

* Improved tests and docs

* Unified TenCrop and F.ten_crop

* Removed useless typing in functional_pil

* Updated code according to the review
- removed useless torch.jit.export
- added missing typing return type
- fixed F.F_pil._is_pil_image -> F._is_pil_image

* Removed useless torch.jit.export

* Improved code according to the review

* [WIP] Add Tensor implementation for pad

* Unified Pad and F.pad opertion for PIL and Tensor inputs

* Added another test and improved docstring

* Updates according to the review

* Cosmetics and replaced f-string by "".format

* Updated docstring
- added compatibility support for padding as [value, ] for functional_pil.pad
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

I was reading through the code and noticed a few spelling errors
orignal -> original
maintaing -> maintaining

* add convert_image_dtype to functionals

* add ConvertImageDtype transform

* add test

* remove underscores from numbers since they are not compatible with python<3.6

* address review comments 1/3

* fix torch.bool

* use torch.iinfo in test

* fix flake8

* remove double conversion

* fix flake9

* bug fix

* add error messages to test

* disable torch.float16 and torch.half for now

* add docstring

* add test for consistency

* move nested function to top

* test in CI

* dirty progress

* add int to int and cleanup

* lint
Co-authored-by: Philip Meier <meier.philip@posteo.de>

* Adjust hue

* Adjust hue acceps torch.tensor uint8
Co-authored-by: Vikram Mukunda Rao Tankasali <vikramtankasali@devvm765.lla0.facebook.com>

* feat: torchscriptable adjusments

* fix: tensor output type

* feat: ColorJitter torchscriptable

* fix: too many blank lines

* fix: documentation spacing and torchscript annotation

* refactor: list type for _check_input

* refactor: reverting to original syntax
Co-authored-by: clement.joudet <clement.joudet@inventia.life>

* Make RandomHorizontalFlip torchscriptable

* Make _is_tensor_a_torch_image more generic

* Make RandomVerticalFlip torchscriptable (#2283)

* Make RandomVerticalFlip torchscriptable

* Fix lint

* Bugfix in pad

* Address review comments

* Fix lint

* Adds as_tensor to functional.py

Similar functionality to to_tensor without the default conversion to float and division by 255.
Also adds support for Image mode 'L'.

* Adds tests to AsTensor()

Adds tests to AsTensor and removes the conversion to float and division by 255.

* Adds AsTensor to transforms.py

Calls the as_tensor function in functionals and adds the function AsTensor as callable from transforms.

* Removes the pic.mode == 'L'

This was handled by the else condition previously so I'll remove it.

* Fix Lint issue

Adds two line breaks between functions to fix lint issue

* Replace from_numpy with as_tensor

Removes the extra if conditionals and replaces from_numpy with as_tensor.

* Renames as_tensor to pil_to_tensor

Renames the function as_tensor to pil_to_tensor and narrows the scope of the function.  At the same time also creates a flag that defaults to True for swapping to the channels first format.

* Renames AsTensor to PILToImage

Renames the function AsTensor to PILToImage and modifies the description.  Adds the swap_to_channelsfirst boolean variable to indicate if the user wishes to change the shape of the input.

* Add the __init__ function to PILToTensor 

Add the __init__ function to PILToTensor since it contains the swap_to_channelsfirst parameter now.

* fix lint issue

remove trailing white space

* Fix the tests

Reflects the name change to PILToTensor and the parameter to the function as well as the new narrowed scope that the function only accepts PIL images.

* fix tests

Instead of undoing the transpose just create a new tensor and test that one.

* Add the view back

Add img.view(pic.size[1], pic.size[0], len(pic.getbands())) back to outside the if condition.

* fix test

fix conversion from torch tensor to PIL back to torch tensor.

* fix lint issues

* fix lint

remove trailing white space

* Fixed the channel swapping tensor test

Torch tranpose operates differently than numpy transpose.  Changed operation to permute.

* Add mode='F'

Add mode information when converting to PIL Image from Float Tensor.

* Added inline comments to follow shape changes

* ToPILImage converts FloatTensors to uint8

* Remove testing not swapping

* Removes the swap_channelsfirst parameter

Makes the channel swapping the default behavior.

* Remove the swap_channelsfirst argument

Remove the swap_channelsfirst argument and makes the swapping the default functionality.

`Mn`, `Sn` are used as mean and std, but their suddenly turned to be
`mean[n]` and `std[n]` in about 10 words later

* Add CircleCI job for python lint

* Break lint

* Fix

* Fix lint

* Re-enable all tests and remove travis python lint

Summary: Fix docstring formatting issues

Reviewed By: fmassa

Differential Revision: D20736644

fbshipit-source-id: 78f66045cfd4c84cb35ca84a1e1fa6aadcd50642
Co-authored-by: Patrick Labatut <plabatut@fb.com>

Co-authored-by: Andrew Murray <radarhere@users.noreply.github.com>

* remove sys.version_info == 2

* remove sys.version_info < 3

* remove from __future__ imports

Summary:
Currently the scale argument can only be of type tuple or integer, this diff allows feeding the input argument `scale` with a list.
Pull Request resolved: https://github.com/pytorch/vision/pull/1997

Test Plan:
Without this diff, launching the following classy vision task causes error:
https://our.intern.facebook.com/intern/fblearner/details/175876950/

With this diff, everything works fine:
https://our.intern.facebook.com/intern/fblearner/details/175913768/



Reviewed By: resonatevision

Differential Revision: D20544904

Pulled By: ymao1993

fbshipit-source-id: a95a2e9ceadec77fffe234756fb3b38b1b9c9cb1
Co-authored-by: Yu Mao <ymao1@fb.com>

* Add fill option to RandomPerspective #1972

* Minor fix to docstring syntax

* Add _parse_fill() to get fillcolor (#1972)

* Minor refactoring as per comments.

* Added test for RandomPerspective with fillcolor.

* Force perspective transform in test.

* F.normalize unsqueeze mean & std if necessary

* added tests to F.normalize for 3d mean & std tensors

* Improved error messages for transforms.functional.normalize().

Split the original TypeError into 1. a TypeError if `tensor` is not a torch.Tensor and 2. a ValueError if `tensor` does not have the correct dimensionality.

Added more detail to the error for when `tensor` has the wrong dimension to make it easier to diagnose. This is useful when this function isn't called directly by the user (e.g. when the user uses transforms.Normalize and can't directly see this functions doc string).

Deleted hanging function `_is_tensor_image()`. It isn't used in this file and isn't used internally anywhere else in torchvision that I can see. (Some users will have used it despite the underscore prefix, but a quick google search for "F._is_tensor_image" suggests this is rare).

* Value checking to prevent division by zero runtime crashes.

Added a ValueError to check for and avoid division by zero in `div_`. Not preventing the call leads to runtime crashes, at least in some environments.

* Fixed div by zero check for non-scalar inputs.

I have fixed a typo that was persent in the Normalize class changed line 150 from     ``input[channel] = (input[channel] - mean[channel]) / std[channel]`` to     ``output[channel] = (input[channel] - mean[channel]) / std[channel]``

* initial fix

* outsourced num bands lookup

* fix doc

* added pillow version requirement

* simplify number of bands extraction

* remove unrelated change

* remove indirect dependency on pillow>=5.2.0

* extend docstring to transform

* bug fix

* added test

* scriptability checks

* tests upds

* linter upds

* linter upds

* upds

* tuple list changes

* linter updates