GitLab

* basic stanford cars structure added.

* added class in the init.

* how to decode the images

* fix typo in init

* works partially

* formatting

* formatting

* formatting

* formatting

* formatting

* minor changes

* minor changes

* issue resolved

* both datapipes are in sync

* checksum dict keys changed

* formatting

* "ufmt formatting"

* "ufmt formatting"

* formatting

* minor change

* minor change

* test added

* lint (end of line issue)

* lint (end of line issue)

* minor changes

* mock dataset formatting

* minor changes

* hopefully final

* formatting

* prototype test

* prototype test

* prototype test

* prototype test

* prototype test

* prototype test

* prototype test

* prototype test

* Update builtin_dataset_mocks.py

* Update stanford_cars.py

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

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

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

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

* formatting and cleaning

* formatting and cleaning

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

* generate catefories script

* generate categories script added

* sigh

* sigh

* sigh

* minor changes

* linting
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* fix documentation version problems

* add missing import

* linting

* Measuring execution times of models.

* Speed up models by avoiding re-estimation of eager output

* Fixing linter

* Reduce input size for big models

* Speed up jit check method.

* Add simple jitscript fallback check for flaky models.

* Restore pytest filtering

* Fixing linter

* support grayscale / RGB alpha conversions

* use _max_valu from stable

* remove extra copy for PIL conversion

* simplify test image generation for color spaces with alpha channel

* use common _max_value in tests

* replace dynamically created dicts with if/else

* make color space conversion more explicit

* make even more explicit

* simplify alpha image generation

* fix if / elif

* add error for unknown conversions

* rename RGBA to RGB_ALPHA

* cleanup

* GRAYSCALE to GRAY

* 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.

* Dsiabling smoke test for nightly builds

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

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.

Co-authored-by: Dbhasin1 <drishti_b@me.iitr.c.in>

* Improve test_video_reader

* Fix linter error

* 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

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

* 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.

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

* 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>