GitLab

* add support for video resnet models, restructure script test to just ignore RCNN models

* switch back to testing subset of the models

* add expected result tests

* fix wrong assertion

* start with only detection models

* remove unneeded rng setting

* fix test

* add tuple support

* update test

* syntax error

* treat .pkl files as binary data, see : https://git-scm.com/book/en/v2/Customizing-Git-Git-Attributes#_binary_files

* fix test

* fix elif

* Map tensor results and enforce maximum pickle size

* unrelated change

* larger rtol

* pass rtol atol around

* last commit i swear...

* respond to comments

* fix flake

* fix py2 flake

modified code of io.read_video and io.read_video_timestamps to intepret pts values in seconds (#1331)

* modified code of io.read_video and io.read_video_timestamps to interpret pts values in seconds

* changed default value for pts_unit to pts, corrected formatting

* hanndliing both fractions and floats for start_pts and end_pts, added test cases for pts_unit sec

* moved unit conversion logic to _read_from_stream method

* make googlnet scriptable

* Remove typing import in favor of torch.jit.annotations

* add inceptionnet

* flake fixes

* fix asssert true

* add import division for torchscript

* fix script compilation

* fix flake, py2 division error

* fix py2 division error

* Fix nightly builds

* Fix lint

* Disable video_reader tests on Travis

* Disable one more test that segfaults on Travis

* Fix typo in expression

* add _backend argument to __init__() of class VideoClips

* minor fix

* minor fix

* Make backend private in VideoClips

* Fix lint

* video transforms

* [video transforms]in ToTensorVideo, divide value by 255.0

* [video transforms] fix a bug

* fix linting

* Make changes backwards-compatible

* add tar.xz archive handler

* update unittest for tar.xz archive

* remove .tar.xz unittest

* add separate .tar.xz unittest

* update PY2 compatibility

* format param added

* lint fixes

* lint fixes

* lint fixes

* [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

* 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

* Support Exporting GeneralizedRCNNTransform

* refactor code to address comments

* update tests

* address comments

* revert min_size to test CI

* re-revert min_size

* 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

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

* Fix flakiness of test_randomresized_params

* Real fix

* Reduce number of iters

* test that torchhub models are scriptable

* fix lint

Following a similar line of inquiry to pytorch/audio#217

* [WIP] Minor cleanups on R3d

* Move all models to video/resnet.py

* Remove old files

* Make tests less memory intensive

* Lint

* Fix typo and add pretraing arg to training script

* Move RandomClipSampler to references

* Lint and bugfix

* Optimize read_video_timestamps for some formats

* Add some tests

* Miscellaneous fixes and improvements

* Guard against videos without video stream

* Fix lint

* Add test for packed b-frames videos

* Fix missing import

* [0.4_video] models - initial commit

* addressing fmassas inline comments

* pep8 and flake8

* simplify "hacks"

* sorting out latest comments

* nitpick

* Updated tests and constructors

* Added docstrings - ready to merge

* introduced function to verify str arguments

* flake8

* added FIXME to VOC

* Fixed error message

* added test for verify_str_arg

* cleanup todos

* added option for custom error message

* fix VOC

* fixed Caltech

Also extend video saving to support different codecs and options. Notably, we can now save with lossless compression

* in_channels_stage2 from backbone.inplanes

* remove type for backward compatible

* Add VideoClips and Kinetics dataset

* Lint + add back missing line

* Adds ClipSampler following Bruno comment

* Change name following Bruno's suggestion

* Enable specifying a target framerate

* Fix test_io for new interface

* Add comment mentioning drop_last behavior

* Make compute_clips more robust

* Flake8

* Fix for Python2

* Added mnasnet

* Fixed some stuff

* Fixed some stuff

* Finished MNASNet

* Fixed format error

* Fixed format error