GitLab

* Removed _max_value method and added a dictionary

Related to https://github.com/pytorch/vision/issues/5502

* Addressed failing tests and restored _max_value method

* Added xfailing test to switch quicker

* Switch to if/else impl

* Refactor preset transforms

* Making presets public.

* Adding improved MobileNetV2 weights

* Fix eval sizes.

* Update accuracy with batch-size 1 run

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

* port FiveCrop and TenCrop to prototype API

* fix ten crop for pil

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

* simplify implementation

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

* fix vanilla tensor image detection

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

* Fix accimage tests

* Adding workaround for accimage

* Refactoring

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

* Remove from models and references.

* Adding most tests and docs.

* Adding transforms tests.

* Remove unnecesary ipython notebook.

* Simplify tests.

* Addressing comments.

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

* simplify Feature implementation

* fix mypy

* add eurosat

* revert formatting

* port test and make style changes

* add eurosat to __init__

* fix pathlib error

* create dataset zipfile and revert pre commit changes

* remove unecessary variable in resources

* revert auto formatter changes and modify ufmt version

* revert change to contributing guide
Co-authored-by: Dbhasin1 <drishti_b@me.iitr.c.in>
Co-authored-by: Nicolas Hug <nicolashug@fb.com>

* add country211

* remove unused import

* map val to valid and use path comparator

* remove unused import

* resolve keyerror

* map split names in dataset mock
Co-authored-by: Dbhasin1 <drishti_b@me.iitr.c.in>
Co-authored-by: Nicolas Hug <nicolashug@fb.com>

* improve StrEnum

* use StrEnum for model weights

* fix test

* migrate StrEnum to main area

* Extend the EfficientNet class to support v1 and v2.

* Refactor config/builder methods and add prototype builders

* Refactoring weight info.

* Update dropouts based on TF config ref

* Update BN eps on TF base_config

* Use Conv2dNormActivation.

* Adding pre-trained weights for EfficientNetV2-s

* Add Medium and Large weights

* Update stats with single batch run.

* Add accuracies in the docs.

* Move VideoReader out of __init__

* Fix linter error

* fix grayscale to RGB for batches

* make unsupported types in auto augment a parameter

* make auto augment kwargs explicit

* add missing error message

* add support for specifying probabilites on RandomChoice

* remove TODO for deprecating p on random transforms

* streamline sample type checking

* address comments

* split image_size into height and width in auto augment
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* expand prototype functional scriptability tests

* remove obsolete skips

* add prototype AugMix transform

* cleanup

* refactor auto augment subclasses to only trnasform a single image

* address review comments

* Replace get_image_size/num_channels with get_image_dims

* Reduce verbosity

* Fix JIT-scriptability

* Refactoring

* More refactoring

* Replace all _FP/_FT direct calls.

* Remove usages of get_image_size and get_image_num_channels from code-base.

* Fix JIT issues

* Adding missing assertion.

* Create dropblock.py

* add dropblock2d

* fix pylint

* refactor dropblock

* add dropblock

* Rename dropblock.py to drop_block.py

* fix pylint

* add dropblock

* add dropblock3d

* add drop_block3d

* add dropblock

* Update drop_block.py

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

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

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

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

* Update drop_block.py

* Update drop_block.py

* import torch.fx

* fix lint

* fix lint

* Update drop_block.py

* improve dropblock

* add dropblock

* refactor dropblock

* fix doc

* remove the limitation of block_size

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

* fix lint

* fix lint

* add dropblock

* Fix linter

* add dropblock random check

* reduce test time

* Update test_ops.py

* speed the dropblock test

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

* add prototype transforms that don't need dispatchers

* cleanup

* remove legacy_transform decorator

* remove legacy classes

* remove explicit param passing

* streamline extra_repr

* remove obsolete ._supports() method

* cleanup

* remove Query

* cleanup

* fix tests

* kernels -> functional

* move image size and num channels extraction to functional

* extend legacy function to extract image size and num channels

* implement dispatching for auto augment

* fix auto augment dispatch

* revert some naming changes

* remove ability to pass params to autoaugment

* fix legacy image size extraction

* align prototype.transforms.functional with transforms.functional

* cleanup

* fix image size and channels extraction

* fix affine and rotate

* revert image size to (width, height)

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

* Add ops.conv3d

* Refactor for conv2d and 3d

* Refactor

* Fix bug

* Addres review

* Fix bug

* nit fix

* Fix flake

* Final fix

* remove documentation

* fix linter

* Update all the implementations to use new Conv

* Small doc fix
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Joao Gomes <jdsgomes@fb.com>

* Use onnx function only in tracing mode

* Add missing import

* Address review comments

* Fix type annotation

* Ignore return type error

* Remove unused import

* Add fake cast

* Fix mypy error

* Fix mypy error

* Update torchvision/models/detection/_utils.py
Co-authored-by: Shubham Bhokare <32080845+shubhambhokare1@users.noreply.github.com>

* _fake_cast_onnx approach
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Shubham Bhokare <32080845+shubhambhokare1@users.noreply.github.com>

* Add topk minimizer function to _utils

* Apply ufmt formatting

* Apply min function for tracing and scripting

* Add type ignore to avoid cast

* fix flake

* Fix python_type_check
Co-authored-by: Prabhat Roy <prabhatroy@fb.com>

* add tensor kernels for normalize and erase

* add image tensor assertion

* fix prototype resource loading

* revert unrelated change

* 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>

* add option to fail a transform on certain types rather than passthrough

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

* add prototype transforms that use the prototype dispatchers

Conflicts:
	torchvision/prototype/transforms/__init__.py

* simplify

* add logger

* remove legacy classes

Conflicts:
	torchvision/prototype/transforms/_augment.py
	torchvision/prototype/transforms/_auto_augment.py
	torchvision/prototype/transforms/_geometry.py

* make get_params private

* remove randbool method

* remove AutoAugmentDispatcher

* add high level kernels for meta conversion

* remove transforms meta abstraction from auto augment transforms

* appease mypy

* add smoke tests for transforms

* remove Query object

* remove extra_repr helper

* fix tests

* appease mypy

* revert some changes on the kernel tests

* fix dispatcher annotations

* remove float cast for torch.rand

* add helper to query image

* fix imports

* address auto augment comments

* cleanup