GitLab

* Remove test related to prototype

* Remove torchvision/prototype dir

* Remove references/depth/stereo because it depend on prototype

* Remove prototype related entries on mypy.ini

* Remove things related to prototype in pytest.ini

* clean setup.py from prototype

* Clean CI from prototype

* Remove unused expect file

* refactor RandomCrop

* mypy

* fix test

* use padding directly rather than private attribute

* only compute type specific fill if padding is needed

* [DRAFT] don't use the diff trick

* fix error message
Co-authored-by: vfdev <vfdev.5@gmail.com>

* remove height and width diff

* reinstate separate diff checking

* introduce needs_crop flag
Co-authored-by: vfdev <vfdev.5@gmail.com>

* prevent feature wrapping for inplace ops

* cleanup

* mypy

* refactor __torch_function__ to be more concise

* avoid double lookup

* fix normalize

* refactor normalize

* mypy

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

* prevent feature wrapping if the feature is not the primary operand

* explicitly add feature tests to CI

* move metadata computation from prototype features into kernels

* fix tests

* fix no_inplace test

* mypy

* add perf TODO

* Update the expected removal date for several deprecated API

* Revert the change in models/_utils.py

* Remove removal date on pretrained=True

* Update another message related to pretrained=True

* Also update the warning in kwonly_to_pos_or_kw decorator

* Update remaining message in _utils.py

* Hack to improve performance of resize op with nearest mode on 2D

* Moved hack to prototype

* Moved hack into proto and reused code from stable resize

* updates

* More updates

* pass metadata directly after input in prototype kernels

* rename img to image

* Removing cuda 102

Display cuda info

Address comments try to resolve CUDA version issue

More work

Base debugging

Fix cuda version passing

Testing

Adding config.yml

Adding command we use for pytorch vision install

Adding unit tests

Modify install command

Refactor config.in

Move cpu tests to different PR

Remove debug code

Testing similar exception for linux as windows

update test_models.py

Revert "Testing similar exception for linux as windows"

This reverts commit 4aaee0b56376440bb56ecd3efe25b60595a241a5.

Revert "update test_models.py"

This reverts commit 413651a308f68b6801681ddfc2c21201c4df3207.

* Removing debug statement

* Reverting to old command

* Fix `size` in resize.

* Update torchvision/prototype/features/_bounding_box.py
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Address some of the comments.

* Fix `output_size` in center_crop.

* Fix `CenterCrop` transform

* Fix `size` in five_crop.

* Fix `size` in ten_crop.

* Fix `kernel_size` and `sigma` in gaussian_blur.

* Fix `angle` and `shear` in affine.

* Fixing JIT-scriptability issues.

* Update TODOs.

* Restore fake types for `Union[int, List[int]]` and `Union[int, float, List[float]]`

* Fixing tests

* Fix linter

* revert unnecessary JIT mitigations.

* Cherrypick Philip's 6dfc9657ce89fe9e018a11ee25a8e26c7d3d43c6

* Linter fix

* Adding center float casting
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Revert "Bump tol for autocasted `fasterrcnn_resnet50_fpn` (#6601)"

This reverts commit a4f53308.

* Temporarily remove FasterRCNN autocast test

* Remove Kinetics400 class

* Remove '2007-test' in VOC

* Remove some MobileNet layer classes

* Remove torchvision/models/segmentation/segmentation.py

* Remove some MultiScaleRoIAlign methods

* Remove torchvision/transforms/_functional_video.py

* Remove torchvision/transforms/_transforms_video.py

* Remove resample parameter in transforms

* Remove 'range' parameter

* Remove 'fill_value' parameter in transforms

* Revert to original warning for C++ models - looks like we should still keep them around?

* pre-commit

* Fix docs

* Remove test/test_transforms_video.py

* Some fixes

* Remove more tests

* Revert changes to C++ models

* Add back _transforms_video and change warning message

* Change back the warning message, and will change the warning message on separate PR
Co-authored-by: YosuaMichael <yosuamichaelm@gmail.com>
Co-authored-by: Yosua Michael Maranatha <yosuamichael@fb.com>

* Replace torch.utils.data.graph.traverse with traverse_dps

[ghstack-poisoned]

* Update on "Replace `torch.utils.data.graph.traverse` with `traverse_dps`"


CI is expected to fail for now. This should be merged only after https://github.com/pytorch/pytorch/pull/85667

 has been merged into nightly and internal.



[ghstack-poisoned]
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* add more size types for prototype resize sample inputs

* add skip for dispatcher

* add more sizes to resize kernel info

* add more skips

* add more diversity to gaussian_blur parameters

* diversify affine parameters and fix bounding box kernel

* fix center_crop dispatcher info

* revert kernel fixes

* add skips for scalar shears in affine_bounding_box

Co-authored-by: Ambuj Pawar <your_email@abc.example>

* Ignore deprecation warning from traverse function

* remove only_datapipe

* reinstate warning ignore for DL test

* ignore warning class wide due to priority
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Fixing inverted center_crop check on Classification preset

* Remove the `--train-center-crop` flag.

* Remove cpp models

* Also remove the whole models folder in csrc

* Cleanup test for cpp model

* add segmentation reference consistency tests

* fall back to smoke tests for resize

* add test for RandomCrop
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* add limitation of decode_jpeg in the function docstring

* undo unwanted changes in decode_png
Co-authored-by: Ambuj Pawar <your_email@abc.example>

* added crestereo author weights

* update weights name

* synced fl-all metric

* changed resize size config param name

* extended weight sets

* changed weight link

* crestereo draft implementation

* minor model fixes. positional embedding changes.

* aligned base configuration with paper

* Adressing comments

* Broke down Adaptive Correlation Layer. Adressed some other commets.

* adressed some nits

* changed search size, added output channels to model attrs

* changed weights naming

* changed from iterations to num_iters

* removed _make_coords, adressed comments

* fixed jit test

* added script files

* added cascaded inference evaluation

* added optimizer option

* minor changes

* Update references/depth/stereo/train.py
Co-authored-by: vfdev <vfdev.5@gmail.com>

* adressed some comments

* change if-else to dict

* added manual resizing for masks and disparities during evaluation

* minor fixes after previous changes

* changed dataloader to be initialised once

* added distributed changes

* changed loader logic

* updated eval script to generate weight API like logs

* improved support for fine-tuning / training resume

* minor changes for finetuning

* updated with transforms from main

* logging distributed deadlock fix

* lint fix

* updated metrics

* weights API log support

* lint fix

* added readme

* updated readme

* updated readme

* read-me update

* remove hardcoded paths. improved valid dataset selection and sync

* removed extras from gitignore
Co-authored-by: Joao Gomes <jdsgomes@fb.com>
Co-authored-by: vfdev <vfdev.5@gmail.com>
Co-authored-by: YosuaMichael <yosuamichaelm@gmail.com>

* Align and Clean up transform types

* Move type definitions to `_utils.py`

* fixing error message on tests

* Apply code review suggestions
Co-authored-by: vfdev <vfdev.5@gmail.com>

* Centralizing types and switching to always getting dicts.

* Fixing linter

* Refactoring typing definitions.

* Remove relative imports.

* Reuse type.

* Temporarily remove the TorchData tests.

* Restore the TorchData tests.
Co-authored-by: vfdev <vfdev.5@gmail.com>

* Added maxvit architecture and tests

* rebased + addresed comments

* Revert "rebased + addresed comments"

This reverts commit c5b28398cd48d2f3403c7c8eeefbaba9df05fcfe.

* Re-added model changes after revert

* aligned with partial original implementation

* removed submitit script fixed lint

* mypy fix for too many arguments

* updated old tests

* removed per batch lr scheduler and seed setting

* removed ontap

* added docs, validated weights

* fixed test expect, moved shape assertions in the begging for torch.fx compatibility

* mypy fix

* lint fix

* added legacy interface

* added weight link

* updated docs

* Update references/classification/train.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Update torchvision/models/maxvit.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* adressed comments

* update ra_maginuted and augmix_severity default values

* adressed some comments

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

* add coverage to prototype tests CI

* line continuation

* add KernelInfo for adjust_brightness

* add KernelInfo for adjust_contrast

* add KernelInfo for adjust_hue

* add KernelInfo for adjust_saturation

* add KernelInfo for clamp_bounding_box

* add KernelInfo for {five, ten}_crop_image_tensor as well as skip functionality

* add KernelInfo for normalize

* add KernelInfo for adjust_gamma

* cleanup

* add DispatcherInfo's for previously add KernelInfo's

* add dispatcher info for elastic

* cleanup prototype transforms functional tests

* fix

* oust local functions

* [proto] Fixed fill type in AA

* Fixed missed typehints

* Set fill as None by default

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

* Added transforms for Stereo Matching

* changed implicit Y scaling to 0.

* Adressed some comments

* addressed type hint

* Added interpolation random interpolation strategy

* Aligned crop get params

* fixed bug in RandomErase

* Adressed scaling and typos

* Adressed occlusion typo

* Changed parameter order in F.erase

* fixed random erase

* Added inference preset transform for stereo matching

* added contiguous reshape to output tensors

* Adressed comments

* Modified the transform preset to use Tuple[int, int]

* adressed NITs

* added grayscale transform, align resize -> mask

* changed max disparity default behaviour

* added fixed resize, changed masking in sparse flow masking

* update to align with argparse

* changed default mask in asymetric pairs

* moved grayscale order

* changed grayscale api to accept to tensor variant

* mypy fix

* changed resize specs

* adressed nits

* added type hints

* mypy fix

* mypy fix

* mypy fix
Co-authored-by: Joao Gomes <jdsgomes@fb.com>

* Moved more losses into classes

* Added photometric loss

* quick fix for ssim loss return value

* added references

* replaced with unsqueeze

* renaming variables

* add ref to consistency loss

* made mask optional everywhere. generalised photometric displacement

* smoothness typo

* fixed flow channel selection bug

* aligned with training script
Co-authored-by: Joao Gomes <jdsgomes@fb.com>

* port vertical_flip

* port rotate

* port crop

* port resized_crop

* port pad

* port perspective

* port elastic

* port center_crop

* port gaussian_blur

* port equalize

* port invert

* port posterize

* port solarize

* port autocontrast

* port adjust_sharpness

* port erase

* fix kernel infos

* renable crop references

* add tolerances to gaussian_blur kernel info