GitLab

* [video reader] inception commit

* add method save_metadata to class VideoClips in video_utils.py

* add load_metadata() method to VideoClips class

* add Exception to not catch unexpected events such as memory erros, interrupt

* fix bugs in video_plus.py

* [video reader]remove logging. update setup.py

* remove time measurement in test_video_reader.py

* Remove glog and try making ffmpeg finding more robust

* Add ffmpeg to conda build

* Add ffmpeg to conda build [again]

* Make library path finding more robust

* Missing import

* One more missing fix for import

* Py2 compatibility and change package to av to avoid version conflict with ffmpeg

* Fix for python2

* [video reader] support to decode one stream only (e.g. video/audio stream)

* remove argument _precomputed_metadata_filepath

* remove save_metadata method

* add get_metadata method

* expose _precomputed_metadata and frame_rate arguments in video dataset __init__ method

* remove ssize_t

* remove size_t to pass CI check on Windows

* add PyInit__video_reader function to pass CI check on Windows

* minor fix to define PyInit_video_reader symbol

* Make c++ video reader optional

* Temporarily revert changes to test_io

* Revert changes to python files

* Rename files to make it private

* Fix python lint

* Fix C++ lint

* add a functor object EnumClassHash to make Enum class instances usable as key type of std::unordered_map

* fix cpp format check

* script_fcn_resnet

* Make old models load

* DeepLabV3 also got torchscript-ready

* [TEST][DO NOT MERGE] Testing CI

* Try fixing build

* make densenet scriptable

* make py2 compat

* use torch List polyfill

* fix unpacking for checkpointing

* fewer changes to _Denseblock

* improve error message

* print traceback

* add typing dependency

* add typing dependency to travis too

* Make loading old checkpoints work

* Remove C++ extensions in favor of custom ops

* Remove unused custom_ops.cpp file

* Rename _custom_ops.py

* Reorganize functions

* Minor improvements and fixes

* Fix lint

* Fully scriptable ops

* Import types used by annotations

* Add Hub tests in torchvision

* Run test_hub in its own interpreter

* Make AnchorGenerator support half precision

* Add test for fasterrcnn with double

* convert gt_boxes to right dtype

* Fix Windows CI

* Use correct version

* Windows build scripts

Add testing yaml

* Change urls

* Test MS agent

* Switch base image

* Use fb links

* Set block style serialization in yaml

* Add new checkout command

* Put on a different branch name

* Support Exporting GeneralizedRCNNTransform

* refactor code to address comments

* update tests

* address comments

* revert min_size to test CI

* re-revert min_size

use flake8 with Python 3 on .circleci directory

* Adds optional fill colour to rotate

* bug fix

* Make custom ops differentiable

and replace autograd.Function. Use ops unconditionally.

We may consider removing the extension functions in a follow-up.

The code-path is tested by the exisitng tests for differentiability.

* add scripting gradchecks tests and use intlist

* fix implicit tuple conversion for gcc-5

* fix merge

* Revert "Revert "Register Torchvision Ops as Cutom Ops (#1267)" (#1316)"

This reverts commit fe234fc8.

* Make import of C++ extensions lazy

* define python initialization functions for extension

* Fix lint

* fix url

* update comment

This reverts commit 78f169b5.

* [WIP] Add CircleCI for CI

* Make jobs only run on master

* Add initial CI

* [wip] testing if works

* Trying some basic GPU tests

* [WIP] maybe it will work?

* [WIP] One more try

* Pin versions

* Simplify and reuse

* Fix

* [WIP] testing windows

* [WIP] testing windows

* Try windows

* Try Windows

* Try windows

* Try windows

* Try windows

* Try windows

* Try windows

* Try windows

* Windows speedup

* Windows multicores

* Add parallel flags for Windows

* Skip some tests on Windows

* Sync config.yml and config.yml.in

* Regenerate

* Run all tests

* Limit python and cuda version for finding pytorch

* Skip darwin for previous check

* Add description

* Fix logic

* Remove space

* Add CUDA test back

* Add back .travis.yml for now and remove duplicate test

* Add newline

* Register torchvision ops

* install ORT only with python 3

* remane lib + address other comments

* fix lint

* fix lib copy

* find file with pattern instead of suffix

* use relative path

* revert rename and use imp to find lib

* fix typo

* make shufflenet scriptable

* make resnet18 scriptable

* set downsample to identity instead of __constants__ api

* use __constants__ for downsample instead of identity

* import tensor to fix flake

* use torch.Tensor type annotation instead of import

* fixed typo

* fixed some more typos and grammer

* Fix flakiness of test_randomresized_params

* Real fix

* Reduce number of iters

* Added initial code

* Changed clang version

* Changed travis script

* Changed travis script

* Updated travis script

* Updated travis script

* Updated travis script

* Use Tensor.data_ptr instead of .data

* use pytorch-nightly in CI

* Fix bug of changing input tensor in function

The original code will change the image tensor passed in by multiplying it by 255. The PR fixes that.

* fix inplace multiplication in save_image

* test that torchhub models are scriptable

* fix lint

Fixed video labelling after `subset` call for HMDB51 dataset (hmdb51.py) (EDIT: UCF101 as well) (#1240)

* Fixed video labelling after subset for HMDB51 dataset

* Fixed video labelling after subset for HMDB51 dataset
Co-authored-by: Eric Tang <etang21@stanford.edu>
Co-authored-by: Ryan Cao <ryancao@stanford.edu>

* UCF 101 Labeling fixes

- Analogous fix to HMDB51 to maintain correct labels after the train-test split
- Additional change to the `select_fold` method in `ucf101.py` to correctly reflect the annotation format
Co-authored-by: Ryan Cao <ryancao@stanford.edu>
Co-authored-by: Eric Tang <etang21@stanford.edu>

* explain lr and batch size in references/detection/train.py

* fix typo

Signed-off-by: Edward Z. Yang <ezyang@fb.com>