GitLab

* remove explicit install of Pillow throughout CI

* explicitly install zlib in windows conda env

* check pillow on Windows

* move check into conda env

* fix

* more debug output

* more debug

* add debug also to linux

* retry w/ and w/o packaging third party library

* tag debug

* more debug

* pin setuptools < 61

* install setuptools from pip

* cleanup

* try remove one more
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

To mitigate missing `libcupti.so` dependency

* bump version

Otherwise, it `setuptools.py`  will try to install latest, which is not compatible with Python runtime older than 3.8

Fixes https://github.com/pytorch/vision/issues/4985

Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Move TorchVision conda package to use pytorch-mutex

This is follow up after https://github.com/pytorch/builder/pull/823

 that gets rids of `feature` and migrate it to `run_constrained`

* Update packaging/torchvision/meta.yaml
Co-authored-by: Eli Uriegas <1700823+seemethere@users.noreply.github.com>

* Update packaging/torchvision/meta.yaml
Co-authored-by: Eli Uriegas <1700823+seemethere@users.noreply.github.com>
Co-authored-by: Eli Uriegas <1700823+seemethere@users.noreply.github.com>

* add cuda envs

* packaging doesn't need cuda env now

* fix cmake_windows_gpu

* minor fix

* rename suffix

* minor change

* update vs integration

* Add deprecation warnings on vision::models

* Change the C++ example.

* Chage readme.

* Update deprecation warning.

* fix MacOS cmake workflow

* try only mkl

* only pin mkl on MacOs

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

* Fix inconsistent version pinning across yaml files.

* Pin pillow to >=5.3.0

* Pin pillow>=5.3.0 everywhere

* Speedup test_ucf101 (#2623 

* Speedup Cmake builds (#3186)

* Speedup test_autoaugment (#3190)

* Speedup DeformConvTester (#3191)

* Speedup InceptionV3 and GoogleNet on Windows (#3196)

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

* Run C++ torchvision example as part of cmake tests

* Enable C++14 support

* Minor error correction

* Add GPU forward on example

* Use arrow operator

* Add CMake build pipeline

* Add CMake build workflow

* Add executable permissions to script

* Install cmake on Windows/MacOS

* Install conda-build before setting up MSVC

* Install PyTorch from nightly

* Do not use conda-build variables

* Add path to CMake

* Install libpng and libjpeg

* Perform make

* Call msbuild on Windows

* Add missing yq

* Use vc_env_helper

* Use string instruction

* Escape configuration option

* Remove configuration flag

* Try to pass -p

* Use caret to escape equal sign

* Escape string option in Windows

* Try to call other bat

* Remove Windows/GPU CMake

* Add tracing cpp test

* Script model instead of tracing it

* Try to register operators manually

* Use manylinux-cuda102

* Activate conda env on Linux

* Build and run sample tracing test

* Add empty echo

* Remove unnecessary register

* Copy headers on Mac

* Revert to 2xlarge

* Include /usr/local/include on Mac

* Install pillow on Windows

* Install future

* Install torchvision on Windows

* Set include flag

* Add torchlib to PATH

* Normalize path via cygpath

* Register ops on Windows

* Minor error correction

* Register CPU/GPU ops on DLL library and register ops via reference

* Install dataclasses

* Install dataclasses using pip

* Address clang formatting issue

* Try to use an actual GPU instance on Linux

* Remove extra environment section

* Declare environment explicitly

* Regenerate

* Pass env variables to Dokcer

* Regenerate circleci

* Test tracing on GPU

* Use GPU medium

* Regenerate

* Use cuda101

* Regenerate

* Do not use pre-trained weights

Avoids having to download pretrained files, which could cause flaky tests
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>