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* streamline category file generation for prototype datasets

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

* Start adding types

* add typing

* Type prototype models

* fix optional type bug

* transient import

* Fix weights type

* fix import

* Apply suggestions from code review

Address nits
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Khushi Agrawal <khushiagrawal411@gmail.com>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Updated compatibility matrix to include LTS version

* Backed out inadvertent change
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* initial commit

* initial commit

* flake8

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

* Fixing minor issue on typing.

* Sample implementation for quantized resnet50.

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

* adding test for trainable paramters in detection models

* modifying range of trainable layers
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

We no longer cache the data in a custom binary, but simply read from the raw data directly.
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Annotate rpn

* Small fix

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

* Adding FasterRCNN ResNet50.

* Refactoring to remove duplicate code.

* Adding typing info.

* Setting weights_backbone=None as default value.

* Overwrite eps only for specific weights.

* Add scripts for facilitating generating release notes

* remove unused lists, and added instructions, applied balck

* renamed file

* Added pandas script directly
Co-authored-by: Nicolas Hug <nicolashug@fb.com>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Adding lightweight API for models.

* Adding resnet50.

* Fix preset

* Add fake categories.

* Fixing mypy.

* Add string=>weight conversion support on Enums.

* Temporarily hardcoding imagenet categories.

* Minor refactoring.

* Added Dropout parameter of Models

* Added argument description for dropout in MobileNet v2 and v3
Updated quantization/googlenet.py as per the changes in constructor in googlenet

* Moved new dropout parameter n the end

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

Co-authored-by: deepsource-autofix[bot] <62050782+deepsource-autofix[bot]@users.noreply.github.com>
Co-authored-by: deepsource-autofix[bot] <62050782+deepsource-autofix[bot]@users.noreply.github.com>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* adding tests to check output of quantized models

* adding test quantized model weights

* merge test_new_quantized_classification_model with test_quantized_classification_model

* adding skipif removed by mistake

* addressing comments from PR

* removing unused argument

* fixing lint errors

* changing model to eval model and updating weights

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

* enforce single test in circleci

* changing random seed

* updating weights for new seed

* adding missing empty line

* try 128 random seed

* try 256 random seed

* try 16 random seed

* disable inception_v3 input/output quantization tests

* removing ModelTester.test_inception_v3_quantized_expect.pkl

* reverting temporary ci run_test.sh changes
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Add typing for imagelist, move params to docstring

* Add docs

* Start annotating utils

* checking

* Add annotations at _utils.py

* Remove unnecessary comments.

* re-checked typings

* Update typing

* Ignore small error

* Use optional tensor

* Ignore for JIT
Co-authored-by: Khushi Agrawal <khushiagrawal411@gmail.com>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

Co-authored-by: Jane (Yuan) Xu <31798555+janeyx99@users.noreply.github.com>

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

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

* mExplicitly copying array in pil_to_tensor

* Update torchvision/transforms/functional.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Adding comments regarding implicit array deep copy in PILToTensor transform

* Update torchvision/transforms/transforms.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* add benchmark utility for datasets

* cleanup

* cleanup

* add benchmarks for MNIST and variants

* simplifiy return if exeception

* refactor benchmark instantiation logic
Co-authored-by: Prabhat Roy <prabhatroy@fb.com>

* Use FX feature extractor for segm model

* Removed use_fe option

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

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