GitLab

* Revert "[FBcode->GH] remove unused requests functionality (#5014)"

This reverts commit 33123bee.

* Revert "replace requests with urllib (#4973)"

This reverts commit 8d25de7b.

* add requests as hard dependency

* install library stubs in CI

* fix syntax

* add requests to conda dependencies

* fix mypy CI

* chore: Updated pillow version specifier

* docs: Updated issue ref in comment

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

* Removed unnecessary if from setup.py

* Removed empty line

* fix category file inclusion

* fix deprecated import

* add ufmt as code formatter

* cleanup

* quote ufmt requirement

* split imports into more groups

* regenerate circleci config

* fix CI

* clarify local testing utils section

* use ufmt pre-commit hook

* split relative imports into local category

* Revert "split relative imports into local category"

This reverts commit f2e224cde2008c56c9347c1f69746d39065cdd51.

* pin black and usort dependencies

* fix local test utils detection

* fix ufmt rev

* add reference utils to local category

* fix usort config

* remove custom categories sorting

* Run pre-commit without fixing flake8

* got a double import in merge
Co-authored-by: Nicolas Hug <nicolashug@fb.com>

* add prototype for `Caltech256` dataset

* silence mypy

* Enable building torchvision with ffmpeg regardless of version on Linux

* Skip tests with python 3.9

* Removed PY39_SKIP

* Cleaned up a bit

* Skip building torchvision with ffmpeg when python==3.9

* Add FIXME to comments

* Fix ffmpeg version

* Ignore platforms other than Linux for ffmpeg

* Removed unnecessary changes

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

* string manipulation for ffmpeg version retrieval

* ffmpeg version 4.2 control

* commenting solution

* removing all escapes for spaces
Co-authored-by: Vincent Moens <vmoens@fb.com>

* Added warning message for unsupported ffmpeg version

* Replaced os.popen with subprocess.run

* Removed capture_true argument

Do this after the version check to avoid failures on import for earlier
torch where that module did not exist.
See #3901
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

Co-authored-by: James Thewlis <james@unitary.ai>

* Proper error message

Now when there are missing ffmpeg libraries the error displayed is:
```
{0} header files were not found, disabling ffmpeg.
```
This is because the missing `.format`.

This PR fixes the warning message by appending the proper format operation.

* Use f-string
Co-authored-by: Prabhat Roy <prabhatroy@fb.com>

* bump to 5.3.0

* Also make 3.6 CI runs rely on 5.3.0

* Add quantized version of nms

* Added tests

* Compute areas only once

* remove calls to dequantize_val

* fix return type for empty tensor

* flake8

* remove use of scale as it gets cancelled out

* simpler int convertion in tests

* explicitly set ovr to double

* add tests for more values of scale and zero_point

* comment about underflow

* remove unnecessary accessor

* properly convert to float for division

* Add comments about underflow

* explicitely cast coordinates to float to allow vectorization

* clang

* clang  again

* hopefully OK now

Co-authored-by: Philip Meier <pmeier.github@posteo.de>
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

This reverts commit 74de51d6.

Summary:
* Reduce unnecessary header inclusions in models and io.

* Move autocast to separate folder and hide autograd implementation in an anonymous namespace.

* Moving files in subfolders.

Reviewed By: fmassa

Differential Revision: D25461523

fbshipit-source-id: 756eeb6848aacaa474de4825ed4c1045d17e2cea

* Encapsulate and standardize deform_conv2d (#3074)

* Rename files.

* Standardizing method names.

* Adding anonymous namespaces.

* Applying C++ naming rules and alinging variable names across headers and cpp files.

* Syncing names across implementations.

* Rename deform_conv2d.h to deform_conv2d.cpp

* Use header files:
- Create header files for kernel implementation and remove definitions from vision_*.h files.
- Eliminate unnecessary headers and ensure all cpp include their headers.

* Change the naming convention for kernel implementations.

* Remove the _param postfix from the variables and standardizing names.

* Exposing public forward/backward methods to the C++ API and moving methods around to minimize git blame changes.

* Encapsulate and standardize nms (#3081)

* Syncing, where possible, the names of functions across devices.

* Adding all internal functions in anonymous namespaces.

* Renaming C++/CUDA kernel files and moving operator code from header to cpp file.

* Create foreach cpp file a separate header file with "public" functions.

* Removing unnecessary repeated includes.

* Update CMakeLists.txt to include all headers.

* Encapsulate and standardize ps_roi_align (#3082)

* Renaming C++ files & methods according to recommended naming conventions and aligning them with Python's API.
Syncing, where possible, the names of functions across devices.

* Adding all internal functions in anonymous namespaces.

* Renaming C++/CUDA kernel files and moving operator code from header to cpp file.

* Create foreach cpp file a separate header file with "public" functions.

* Removing unnecessary repeated includes.

* Encapsulate and standardize ps_roi_pool (#3084)

* Renaming C++ files & methods according to recommended naming conventions and aligning them with Python's API.

* Adding all internal functions in anonymous namespaces.

* Renaming C++/CUDA kernel files and moving operator code from header to cpp file.

* Create foreach cpp file a separate header file with "public" functions.

* Removing unnecessary repeated includes.

* Encapsulate and standardize roi_align (#3085)

* Renaming C++ files & methods according to recommended naming conventions and aligning them with Python's API.

* Adding all internal functions in anonymous namespaces.

* Renaming C++/CUDA kernel files and moving operator code from header to cpp file.

* Create foreach cpp file a separate header file with "public" functions.

* Removing unnecessary repeated includes.

* Encapsulate and standardize roi_pool  (#3088)

* Renaming C++ files & methods according to recommended naming conventions and aligning them with Python's API.

* Adding all internal functions in anonymous namespaces.

* Syncing variable names between the cpp files and their header files.

* Renaming C++/CUDA kernel files and moving operator code from header to cpp file.

* Create foreach cpp file a separate header file with "public" functions.

* Removing unnecessary repeated includes.

* Encapsulate and standardize new_empty_tensor_op (#3089)

* Renaming C++ files & methods according to recommended naming conventions and aligning them with Python's API.

* Create foreach cpp file a separate header file with "public" functions.

* Adding all internal functions in anonymous namespaces.

* Convert to const ref all possible parameters.

* Removing unnecessary repeated includes.

* Encapsulate and standardize C++ Ops - Clean up (#3094)

* Removing unnecessary repeated includes.

* Remove unnecessary vision_cpu.h, vision_cuda.h, autocast.h.

* Fixing naming convention and correcting method names on macros.

* Turn on clang formatter for cu files and fixing broken styles.

* Replace "#ifndef ... #define ... #endif" with "#pragma once" on header files.

* Adding operator methods in vision::ops namespace. (#3096)

* Adding operator methods in vision::ops namespace.

* Replace general.h with macros.h

* Adding vision.h to the necessary cpp files.

* Fixes #2783
- Added "-fopenmp" cflags
- Refactored cxx flags creation

* Fixed for macosx

I.e. put all file system altering operations under `if __name__ == "__main__":`

* adding base files

* setup modification to actually build the thing

* video api constructor registration

* FAIL metadata

* FAIL update for QS

* revert

* debugging with Victor

* adding base files

* setup modification to actually build the thing

* video api constructor registration

* FAIL metadata

* FAIL update for QS

* revert

* debugging with Victor

* metadata registration works

* API build next

* test

* Merge change

* formatting parameters to avoid the segfault

* next now works on a video

* make size of the output tensor format dependent

* Make next work on audio stream only as well

* refactoring the _setCurrentStream param

* Fixing the last frame return and sensor

* todo docs

* Formatting

* cleanup and comments

* introducing new tests for the API

* cleanup

* Comment out unnecesary format (will add following FFMPEG fix)

* Reformat parsing function

* removing the seek bug `get_decoder_params`

* Removing unnecessary code/variables

* enforce RGB24 as a reading format (will crash before ffmpeg fix)

* permute the dimensions to return (RGB x H x W)

* Changing the return type to std::tuple<torch::Tensor, double> as opposed to tensor list

* Adjusting tests for the new return type

* remove unnecessary jitter

* clangangangang

* Metadata return changes (#1)

* remove implicit calls to set a current stream (#2)

* Adding new tests to check the accuracy of the seek

* cleanup debugging statements

* adding base files

* setup modification to actually build the thing

* video api constructor registration

* FAIL metadata

* FAIL update for QS

* revert

* debugging with Victor

* adding base files

* video api constructor registration

* FAIL metadata

* FAIL update for QS

* revert

* debugging with Victor

* metadata registration works

* API build next

* test

* Merge change

* formatting parameters to avoid the segfault

* next now works on a video

* make size of the output tensor format dependent

* Make next work on audio stream only as well

* refactoring the _setCurrentStream param

* Fixing the last frame return and sensor

* todo docs

* Formatting

* cleanup and comments

* introducing new tests for the API

* cleanup

* Comment out unnecesary format (will add following FFMPEG fix)

* Reformat parsing function

* removing the seek bug `get_decoder_params`

* Removing unnecessary code/variables

* enforce RGB24 as a reading format (will crash before ffmpeg fix)

* permute the dimensions to return (RGB x H x W)

* Changing the return type to std::tuple<torch::Tensor, double> as opposed to tensor list

* Adjusting tests for the new return type

* remove unnecessary jitter

* clangangangang

* Metadata return changes (#1)

* remove implicit calls to set a current stream (#2)

* Adding new tests to check the accuracy of the seek

* cleanup debugging statements

* Addressing PR comments

* addressing Francisco's comments

* CLANG build formatting

* Updated testing to test against pyav for the video tensor reads

* Formatting

* remove pyav from pip deps and add it to conda build

* add pyav and ffmeped to conda builds

* Formatting?

* Setting up linter once and for all hopefully

* Testing pyav

* Fix to 8.0.0

* Try 6.2.0

* See what happens with av from pip

* Remove FFMPEG blocker

* What is going on?

* More tests

* Forgot something

* unblocker

* Check if cache is messing up with things

* Now try with different ffmpeg

* Now try with different ffmpeg

* Testing pyav

* Fix to 8.0.0

* Try 6.2.0

* See what happens with av from pip

* What is going on?

* More tests

* Forgot something

* Check if cache is messing up with things

* Now try with different ffmpeg

* Now try with different ffmpeg

* Do not install av

* Test with ffmpeg 4.2

* clean up video tests

* cleaning up the tests a bit to better test partial reading

* arrgh linter

* Forgot the av test

* forgot av test

* checkout build files from master

* revert circleci

* addressing Franciscos comments

* addressing Franciscos comments

* Ignore ffmpeg in travis
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>
Co-authored-by: Edgar Andrés Margffoy Tuay <andfoy@gmail.com>

* Add PyTorch FFmpeg to wheel and conda distributions

* Try to install wget from conda

* Add yq flag on Mac

* Correct copy instructions

* Use cURL on Windows

* Call bzip2 directly due to msys2/MSYS2-packages#1548

* Copy ffmpeg binaries to system-wide directories

* Try to use std:c++17 on Windows

* Try to define ssize_t on Windows

* Use C++14

* Declare AVRational structs explicitly

* Initialize AVRational explicitly

* Replace macro to prevent errors on Windows

* Replace AV_TIME_BASE_Q

* Add library paths for video extension

* Force ffmpeg from pytorch channels?

* Fix clang style warnings

* Update CONDA_CHANNEL_FLAGS

* Fix clang style issues

* Update unittest

* Use FFmpeg 4.2

* Install correct version on Mac

* Pin av version to 8.0.0

* Fix string formatting issue

* Fix pip pinning

* Try with 8.0.1

* Use av 8.0.2

* Remove trailling whitespaces

* Disable test_io_opt.py

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

- can be helpful for debugging C++ extensions

* Remove linux distribution detection, search first on local paths for libraries

* Use not in

* Remove unused variables

* Add libpng requirement into conda recipe

* Try to install libjpeg-turbo

* Add PNG reading capabilities

* Remove newline

* Add image extension to compilation instructions

* Include png functions as part of the main library

* Update CMakeLists

* Detect if building on conda-build

* Debug

* More debug messages

* Print globbed libreries

* Print globbed libreries

* Point to correct PNG path

* Remove libJPEG preventively

* Debug extension loading

* Link libpng explicitly

* Link with PNG

* Add PNG reading capabilities

* Add libpng requirement into conda recipe

* Try to install libjpeg-turbo

* Remove newline

* Add image extension to compilation instructions

* Include png functions as part of the main library

* Update CMakeLists

* Detect if building on conda-build

* Debug

* More debug messages

* Print globbed libreries

* Print globbed libreries

* Point to correct PNG path

* Remove libJPEG preventively

* Debug extension loading

* Link libpng explicitly

* Link with PNG

* Install libpng on conda-based wheel distributions

* Add -y flag

* Add -y flag to yum

* Locate LibPNG on windows conda

* Remove empty else

* Copy libpng16.so

* Copy dylib on Mac

* Improve check on Windows

* Try to install ninja using conda on windows

* Use libpng on Windows

* Package lib on windows wheel

* Point library to the correct place

* Include binaries as part of wheel

* Copy libpng.so on linux

* Look for png.h on Windows when using conda-build

* Do not skip png tests on Mac/Win

* Restore libjpeg-turbo

* Install jpeg-turbo on wheel distributions

* Install libjpeg-turbo from conda-forge on wheel distributions

* Do not pull av on conda-build

* Add pillow disclaimer

* Vendors libjpeg-turbo 2.0.4

* Merge JPEG work

* Remove submodules

* Regenerate circle config

* Fix style issues

* Fix C++ style issues

* More style corrections

* Add JPEG-turbo to linking libraries

* More style corrections

* More style corrections

* More style corrections

* Install libjpeg-turbo-devel

* Install libturbo-jpeg on typing pipeline

* Update Circle template

* Windows and Unix turbojpeg have the same linking name

* Install turbojpeg-devel instead of libjpeg-turbo

* Copy TurboJPEG binaries to wheel

* Move test image

* Move back test image

* Update JPEG test path

* Remove dot from extension

* Move image functions to extension

* Use stdout arg in subprocess

* Disable image extension if libpng or turbojpeg are not found

* Append libpng stdout

* Prevent list appending on lists

* Minor path correction

* Minor error correction

* Add linking flags

* Style issues correction

* Address minor review corrections

* Refactor library search

* Restore access index

* Fix JPEG tests

* Update libpng version in Travis

* Add -y flag

* Remove dot

* Update libpng using apt

* Check libpng version

* Change libturbojpeg binary

* Update import

* Change call

* Restore av in conda recipe

* Minor error correction

* Remove unused comment in travis.yml

* Update README

* Fix missing links

* Remove fixes for 16.04

* Enable JPEG support using libjpeg directly

* Install libjpeg-turbo8 on Travis

* Fix styling issues

* Do not append to paths if library found in standard library locations

* Add macro flag

* Use custom error handler

* Use 3?

* Use short-lived buffer

* Return TRUE instead of true

* Assert RuntimeError

* Use .jpg extension

* Remove conda-forge

* Use data_ptr instead of accessor

* Use assertTrue for jpeg verification

* Remove unnecessary memcpy

* Debug test on Windows

* Remove PIL from jpeg verification
Co-authored-by: Ryad ZENINE <r.zenine@gmail.com>