GitLab

* Check target boxes input on generalized_rcnn.py

* Fix target box validation in generalized_rcnn.py

* Add tests for input validation of detection models

Fix https://github.com/pytorch/vision/issues/2193.

* feat: Added eps argument to FrozenBatchNorm2d

* test: Added unittest for eps addition in FrozenBatchNorm2d

See #2169

* fix: Reverted forward changes for JIT fuser

* fix: Added back n argument for backward-compatibility

* fix: Fixed FrozenBatchNorm2d forward

Added back eps

* feat: Specified deprecation warnings in FrozenBatchNorm2d

* test: Added unittest for deprecation warninig in FrozenBatchNorm2d

* style: Fixed lint

* style: Fixed block comment lint

* feat: Restored support of tuple of Tensors for roi_align & roi_pool

* test: Added unittest for Tensor sequence support by region pooling

* test: Fixed typo in unittest

* test: Fixed data type

* test: Fixed roi pooling tensor unittest

* test: Fixed box format conversion

* Add all the latest models to hubconf

* remove detection models from hubconf

* fix link error

adding slight clarification to evaluation logic area, regarding images

* add mypy config

* fix syntax error

* fix annotations in torchvision/utils.py

* add mypy type check to CircleCI

* add mypy cache to ignore files

* try fix CI

* ignore flake8 F821 since it interferes with mypy

* add mypy type check to config generator

* explicitly set config files

* Fix mypy type annotations

* follow torchscript Tuple type

* redefine torch_choice output type

* change the type in cached_grid_anchors

* minor bug
Co-authored-by: Guanheng Zhang <zhangguanheng@devfair0197.h2.fair>
Co-authored-by: Guanheng Zhang <zhangguanheng@learnfair0341.h2.fair>

* Fixing nms on boxes when no detection

* test

* Fix for scale_factor computation

* remove newline

* Fix for mask_rcnn dynanmic axes

* Clean up

* Update transform.py

* Fix for torchscript

* Fix scripting errors

* Fix annotation

* Fix lint

* Fix annotation

* Fix for interpolate scripting

* Fix for scripting

* refactoring

* refactor the code

* Fix annotation

* Fixed annotations

* Added test for resize

* lint

* format

* bump ORT

* ort-nightly version

* Going to ort 1.1.0

* remove version

* install typing-extension

* Export model for images with no detection

* Upgrade ort nightly

* update ORT

* Update test_onnx.py

* updated tests

* Updated tests

* merge

* Update transforms.py

* Update cityscapes.py

* Update celeba.py

* Update caltech.py

* Update pkg_helpers.bash

* Clean up

* Clean up for dynamic split

* Remove extra casts

* flake8

Now the dataset is not working properly because of this line of code `indices = [i for i in range(len(video_list)) if video_list[i][len(self.root) + 1:] in selected_files]`. 
Performing the `len(self.root) + 1` only make sense if there is no training / to root

```
>>> root = 'data/ucf-101/videos'
>>> video_path = 'data/ucf-101/videos/activity/video.avi'
>>> video_path [len(root ):]
'/activity/video.avi'
>>> video_path [len(root ) + 1:]
'activity/video.avi'
```

Appending the root path also to the selected files is a simple solution and make the dataset works with and without a trailing slash.

* Fix missing compilation files for video-reader

* Disable IO tests in travis

* feat: Added number of features in FrozenBatchNorm2d repr

While BatchNorm layers have extensive information in their repr, FrozenBatchNorm2d has one

* refactor: Refactored FrozenBatchNorm2d __repr__

* test: Added unittest for FrozenBatchNorm2d __repr__

* style: Removed blank lines in test_ops

* refactor: Avoids creating an extra attribute for __repr__

* style: Switched __repr__ to f-string

Since support of Python version ealier than 3.6 have been dropped, f-string can be used.

* fix: Fixed typo in __repr__

* style: Switched unittest .format to f-string

`Mn`, `Sn` are used as mean and std, but their suddenly turned to be
`mean[n]` and `std[n]` in about 10 words later

At the moment in the ASPP-Layer the number of output channels are predefined as a constant,
which is good for DeepLab but not necessairly in other projects, where another out-channel Nr. is required.

Also the number of "atrous rates" is fixed to three, which also could be sometimes more or less depending on the notwork-arch.
Again these fixed values may make sense in DeepLab-Model but not necessarily in other type of models.

This pull-req. contains the needed changes to make ASPP-Layer generic.

* Don't include CUDAApplyUtils.cuh

* fix format

* fix atomic

* Improve documentation for NMS

* update nms doc for special case

* only display extensions if available

* add tests

* fix lint

* For detection model, replace L1 loss with beta smooth L1 loss to achieve better performance.

* Add type annotations for torchscript

* Resolve E226

* fix the use of contiguous() in kernels

* clang-format

* add a contiguous in nms
Co-authored-by: Yuxin Wu <ppwwyyxx@users.noreply.github.com>

* Fixing nms on boxes when no detection

* test

* Fix for scale_factor computation

* remove newline

* Fix for mask_rcnn dynanmic axes

* Clean up

* Update transform.py

* Fix for torchscript

* Fix scripting errors

* Fix annotation

* Fix lint

* Fix annotation

* Fix for interpolate scripting

* Fix for scripting

* refactoring

* refactor the code

* Fix annotation

* Fixed annotations

* Added test for resize

* lint

* format

* bump ORT

* ort-nightly version

* Going to ort 1.1.0

* remove version

* install typing-extension