GitLab

* 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)

momet -> moment
Signed-off-by: Hollow Man <hollowman@hollowman.ml>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* 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>

* Enable jit tests in all models and add warning if checkModule() tests are skipped.

* Turning on JIT tests on CI.

* Fixing broken unit-tests.

* Refactoring and cleaning up duplicate code.

* 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

* Add AnchorGenerator with ground-truth outputs

* Minor fixes

* 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.

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

* Fixed for macosx

* 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

* Replace the Pallete with an RGB + Alpha file.

* Correct typo on name.

Revert "Change the `SUM_OF_PRETRAINED_RESNET18_PARAMS` decimal values to resolve broken tests. (#2978)" (#2990)

This reverts commit 1f4e3a46.

* Add support of different color types in readpng.

* Adding test images and unit-tests.

* Use closest possible type.

* Fix formatting.

* tries adding anchor tests

* fixes lint

* tries fixing

* tries one more time

* fixes the test

* 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

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

* 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

- fixed problem with error computation between results
- refactored tensor cast for resize
- fixed round usage