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Previously, when doing a CUDA build, we would pass -O0 to build cpu
bits. This PR removes that `-O0` (so we build in `-O3` instead.

Test Plan:
- wait for CI

Python 2.7 was EOL on January 1, 2020

The last torchvision release to support Python 2.7 was 0.5.0
Signed-off-by: Eli Uriegas <eliuriegas@fb.com>

* Type of input featmap_names fixed in example.

* Added missing imports.

* update doc

* update doc

* Fixes #1716

Fixes EMNIST classes attribute is wrong #1716

* Fixed the Classes for Letters Split

* Update mnist.py

* Move classes attribute inside init definition

* Fix Linting errors

* Fix AnchorGenerator if moving from one device to another

* Fixes for the test

* Testing CI

* Disable tests for Pillow 7

Previous weights are not compatible with current PyTorch

* Fix lint following #1695

* V2

* V3

1. Let the IOU function compare with threshold. This avoid a division. Similar strategy is also used in https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/non_max_suppression_op.cu.cc
2. Only compute the upper triangle of the mask.

This speeds up the kernel about 20% (tested on GTX 1080Ti, with 20 input cases dumped from a Mask R-CNN inference job).

* fix a little bug about resume

When resuming, we need to start from the last epoch not 0.

* the second way for resuming

the second way for resuming

* scriptability checks

* tests upds

* linter upds

* linter upds

* upds

* tuple list changes

* linter updates

Bugfix on GroupedBatchSampler for corner case where there are not enough examples in a category to form a batch (#1677)

* Make R-CNN models less verbose in script mode

* Fix typo in warning message

* remove windows skips from video_utils tests, now that they pass

* replace lambda in videoclips in order to be pickled on windows and update tests

* out_place checks

* lint ups

* tgz updates

* tgz updates

* tgz updates

* Update KeypointRCNN weights with correct file

* Fix model

* Fix

* add scriptable transform: center_crop

* add test: center_crop

* add scriptable transform: five_crop

* add scriptable transform: five_crop

* add scriptable transform: fix minor issues