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This reverts commit 4b0b332a.

This is triggering crazy amounts of API calls for internal tools. I'm reverting this to stop the problem.

* Ported places365 dataset's tests to the new test framework

* Made some attributes private

* Removed unnecessary compute_md5()

* Added test_images_download_preexisting()
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* fix check for exceeded quota on Google Drive

* safeguard quota exceed check

Co-authored-by: Nicolas Hug <nicolashug@fb.com>

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

* refactor test_models to use pytest

* Also xfail the detection models

* Remove xfail and just comment out expected failing parts

* Comment out some more

* put back commented checks

* cleaning + comment

* docs

* void unnecessary changes

* r2plus1d_18 seems  to segfault on linux gpu??

* put back test, failure is unrelated
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* fix test

* more robust test

* flake8
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Phew

* not sure CI got properly triggered?

* Edited roi transforms docs

* remove incorrect param desc

* Fixed confusion  about feature maps according to comment

* Ported STL10 dataset's tests to new test framework

* Added additional tests

* Removed unused import

* Made private methods static and other minor changes

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

* Try using the pyortch theme

* directly embed script in layout.html instead

* use more mordern script
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Ported SVHN dataset to new test framework

* Fixed flake8 error and added REQUIRED_PACKAGES=scipy

* Remove pandas dependecy for CelebA dataset

* address PR comments

* Apply suggestions from code review
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* packaging: Remove pin for jpeg, numpy

These may no longer be necessary due to the default anaconda channel
having the necessary packages now.
Signed-off-by: Eli Uriegas <eliuriegas@fb.com>

* Update packaging/torchvision/meta.yaml
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Added KITTI dataset

* Addressed review comments

* Changed type of target to List[Dict] and corrected the data types of the returned values.

* Updated unit test to rely on ImageDatasetTestCase

* Added kitti to dataset documentation

* Cleaned up test and some minor changes

* Made data_url a string instead of a list

* Removed unnecessary try and print
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Make two methods as similar as possible.

* Introducing conditional fake casting.

* Change the casting mechanism.

* WIP

* clang

* docs

* extracted out common utils

* Use better quantization function and pass tensors as parameters

* proper dequantization

* Some tests

* Dequantization optimization, seems to gain a few ms

* clang-format

* again

* more correct test. Had to remove optimization although it almost works

* Also test aligned=True

* remove useless part

* more docs and comments

* Put back optimization with more robust test

* Added check for index upper bound

* avoid possible overflow

* Move common function into common.h

* oops

* scale=1,zero_point=0 makes more sense

* Force batch size of 1 to prevent any indexingbug

* format

* format again

* updated docstring

* put back description comment for pre_calc_bilinear_interpolate

* revert most changes to docstring as it's taken care of in another PR

* Fixed return docstrings

* Added some refs and corrected some parts

* more refs, and a note about dtypes
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Added defusedxml to parse untrusted XML data

* Added typecheck disable for defusedxml
Co-authored-by: Nicolas Hug <nicolashug@fb.com>