GitLab

* 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.

Replace tabs with spaces, add newlines to files and replace whitelist with allowlist

Operator registration of functions with noexcept doesn't work on some compilers, see https://github.com/pytorch/pytorch/issues/48667

* Fill color support for tensor affine transforms

* PEP fix

* Docstring changes and float support

* Docstring update for transforms and float type cast

* Cast only for Tensor

* Temporary patch for lack of Union type support, plus an extra unit test

* More plausible bilinear filling for tensors

* Keep things simple & New docstrings

* Fix lint and other issues after merge

* make it in one line

* Docstring and some code modifications

* More tests and corresponding changes for transoforms and docstring changes

* Simplify test configs

* Update test_functional_tensor.py

* Update test_functional_tensor.py

* Move assertions
Co-authored-by: vfdev <vfdev.5@gmail.com>

* add UUID in LOG() in decoder

* Fix lint

* More lint

* concatenate small tensors into big ones to reduce the use of shared file descriptor (#1694)

Summary:
Pull Request resolved: https://github.com/pytorch/vision/pull/1694



- PT dataloader forks worker process to speed up the fetching of dataset example.  The recommended way of multiprocess context is `forkserver` rather than `fork`.

- Main process and worker processes will share the dataset class instance, which avoid duplicating the dataset and save memory. In this process, `ForkPickler(..).dumps(...)` will be called to serialize the objects, including objects within dataset instance recursively. `VideoClips` instance internally uses O(N) `torch.Tensor` to store per-video information, such as pts, and possible clips, where N is the No. of videos.

- During dumping, each `torch.Tensor` will use one File Descriptor (FD). The OS default max limit of FD is 65K by using `ulimit -n` to query. The number of tensors in `VideoClips` often exceeds the limit.

- To resolve this issue, we use a few big tensors by concatenating small tensors in the `__getstate__()` method, which will be called during pickling. This will only require O(1) tensors.

- When this diff is landed, we can abondon D19173248

In D19173397, in ClassyVision, we change the mp context from `fork` to `forkserver`, and finally can run the PT dataloader without hanging issues.

Reviewed By: fmassa

Differential Revision: D19179991

fbshipit-source-id: c8716775c7c154aa33d93b25d112d2a59ea688a9

* Try to fix Windows

* Try fix Windows v2

* Disable tests on Windows

* Add back necessary part

* Try fix OSX (and maybe Windows)

* Fix

* Try enabling Windows
Co-authored-by: Zhicheng Yan <zyan3@fb.com>

* Fix: Improve the bounding boxes implementation

Use write_png instead of PIL in test_draw_boxes()
Initialize txt_font only once

* Remove channels permutation in test_draw_boxes
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Aditya Khursale <akhursale@nvidia.com>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Add option to write audio to video file

Summary:
I was trying to use torchvision's `write_video` function and realized there was no option to add in the audio.

Thus, this diff contains the changes necessary such that this is possible. This is my first time trying to contribute to this project, so be as harsh as you need!

Reviewed By: fmassa

Differential Revision: D21480083

fbshipit-source-id: 2e11f2c8728d42f86c94068f75b843793d5a94aa

* Fix typo

* Try fix Windows

* Disable test on Windows
Co-authored-by: Joanna Bitton <jbitton@fb.com>

Summary:
* Link libav change into fbcode
* Set rw_timeout value

Differential Revision: D23412524

fbshipit-source-id: 5755950be1b1b4c37cb0c3a69a8c875f8862a92c
Co-authored-by: Keyun Tong <ktong@fb.com>

* Fix spelling mistake: orignal -> original

* Spelling fix: orignal -> original
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Fix spelling: dimenions -> dimensions

* Fix spelling mistake: dimenions -> dimensions

* Correcting incorrect types

* Add missing type statement

* Fix type annotations in unittest

* Fix TypeError

* Fix TypeError

* Fix type equality judgment

* Fix recursive compile

* Use string for class name annotation.
Co-authored-by: zhiqiang <zhiqwang@outlook.com>

* Enable support for images without annotations

* Ensuring gradient propagates to RegressionHead.

* Rewriting losses to remove branching.

* Fix the seed on DeformConv autocast test.

[BC-breaking] Introduced InterpolationModes and deprecated arguments: resample and fillcolor (#2952)

* Deprecated arguments: resample and fillcolor
Replaced by interpolation and fill

* Updates according to the review

* Added tests to check warnings and asserted BC

* [WIP] Interpolation modes

* Added InterpolationModes enum

* Added supported for int values for interpolation for BC

* Removed useless test code

* Fix flake8

* initital prototype

* flake

* Adds documentation

* minimal working bboxes

* Adds label display

* adds colors :-)

* adds suggestions and fixes CI

* handles image of dim 4

* fixes image handling

* removes dev file

* adds suggested changes

* Updating the API.

* Update test.

* Implementing code review improvements.

* Further refactoring and adding test.

* Replace random to white to reduce size and change font on tests.
Co-authored-by: Vasilis Vryniotis <vvryniotis@fb.com>

Adding Python type hints, correcting incorrect types, removing unnecessary vars and simplifying code. (#3045)

* Add a warning if a clip can't be get from a video in VideoClips

* Update torchvision/datasets/video_utils.py
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Add a test
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Add explicit check for number of channels

Example why you need to check it:
`M = torch.randint(low=0, high=2, size=(6, 64, 64), dtype = torch.float)`
When you put this input through to_pil_image without mode argument, it converts to uint8 here:
```
if pic.is_floating_point() and mode != 'F':
            pic = pic.mul(255).byte()
```
and change the mode to RGB here:
```
if mode is None and npimg.dtype == np.uint8:
            mode = 'RGB'
```
Image.fromarray doesn't raise if provided with mode RGB and just cut number of channels from what you have to 3

* Check number of channels before processing

* Add test for invalid number of channels

* Add explicit check for number of channels

Example why you need to check it:
`M = torch.randint(low=0, high=2, size=(6, 64, 64), dtype = torch.float)`
When you put this input through to_pil_image without mode argument, it converts to uint8 here:
```
if pic.is_floating_point() and mode != 'F':
            pic = pic.mul(255).byte()
```
and change the mode to RGB here:
```
if mode is None and npimg.dtype == np.uint8:
            mode = 'RGB'
```
Image.fromarray doesn't raise if provided with mode RGB and just cut number of channels from what you have to 3

* Check number of channels before processing

* Add test for invalid number of channels

* Put check after channel dim unsqueeze

* Add test if error message is matching

* Delete redundant code

* Bug fix in checking for bad types
Co-authored-by: Demyanchuk <demyanca@mh-hannover.local>
Co-authored-by: vfdev <vfdev.5@gmail.com>

* Add support of mode and remove channels.

* Replacing integer mode with define constants.

* refactor: Fixed typing exception throwing issues with JIT

* style: Added back mypy typing to forward

* chore: Added back densenet module as mypy exception

* Adding output channels implementation for pngs.

* Adding tests for png.

* Adding channels in the API and documentation.

* Fixing formatting.

* Refactoring test_image.py to remove huge grace_hopper_517x606.pth file from assets and reduce duplicate code. Moving jpeg assets used by encode and write unit-tests on their separate folders.

* Adding output channels implementation for jpegs. Fix asset locations.

* Add tests for JPEG, adding the channels in the API and documentation and adding checks for inputs.

* Changing folder for unit-test.

* Fixing windows flakiness, removing duplicate test.

* Replacing components to channels.

* Adding reference for supporting CMYK.

* Minor changes: num_components to output_components, adding comments, fixing variable name etc.

* Reverting output_components to num_components.

* Replacing decoding with generic method on tests.

* Palette converted to Gray.

* Fix MNASNet docstrings so they are rendered correctly

* Add dot after url link in models docstrings for consistency

* Removing python headers and code for Python2 compatibility.

* Restoring python3 inits.

* ColorJitter gets its random params by calling get_params().

* Update arguments.

* Styles.

* Add description for Nones.

* Chainging Nones to optional.

* [DOC] Added paper citation for DeformConv2d

* Fixes Pylint error

* Added citation of the previous paper

* Add support of different color types in readpng.

* Adding test images and unit-tests.

* Use closest possible type.

* Fix formatting.

* Making quantized inception torchscriptable.

* Adding a test.

* Fix mypy warning.

* Remove model download from tests

* Refactor trainable_layers checks in detection models

* Bugfix

* Finish tests and fixes

* Fix lint

* Change children() to modules() to ensure init happens in all blocks.

* Update expected values of all detection models.

* Revert "Update expected values of all detection models."

This reverts commit 050b64ae

* Update expecting values.

* make_grid should not avoid DBZ by adding eps

While this doesn't matter in most cases where the images is quantized to [0,255] afterwards, it still is not a faithful de-normalization. It is a simple change to make it use clamp instead.

* fix max/min shadowing

* Add modulation input for DeformConv2D

* lint

* Patch for GPU CI

* Remove bad cache on CI

* style: Added annotation typing for shufflenet

* fix: Removed duplicate type hint

* refactor: Removed un-necessary import

* fix: Fixed constructor typing

* style: Added black formatting on depthwise_conv

* style: Fixed stage typing in shufflenet

* initial docstring

* Revert "initial docstring"

This reverts commit 2bf68ca26e58096885901da0cfa330530974e731.

* revert the formatting changes

* clear up per Victor's comment

* Addressing PR comments
Co-authored-by: Bruno Korbar <korbar@vggdev9.vggdev.cluster>

* style: Added annotation typing for densenet

* fix: Fixed import

* refactor: Removed un-necessary import

* fix: Fixed constructor typing

* chore: Updated mypy.ini

* fix: Fixed tuple typing

* style: Ignored some mypy errors

* style: Fixed typing

* fix: Added missing constructor typing