GitLab

* Add CircleCI job for python lint

* Break lint

* Fix

* Fix lint

* Re-enable all tests and remove travis python lint

* fixes and tests for variable input size

* transform test fix

* Fix comment

* Dynamic shape for keypoint_rcnn

* Update test_onnx.py

* Update rpn.py

* Fix for split on RPN

* Fixes for feedbacks

* flake8

* topk fix

* Fix build

* branch on tracing

* fix for scalar tensor

* Fixes for script type annotations

* Update rpn.py

* clean up

* clean up

* Update rpn.py

* Updated for feedback

* Fix for comments

* revert to use tensor

* Added test for box clip

* Fixes for feedback

* Fix for feedback

* ORT version revert

* Update ort

* Update .travis.yml

* Update test_onnx.py

* Update test_onnx.py

* Tensor sizes

* Fix for dynamic split

* Try disable tests

* pytest verbose

* revert one test

* enable tests

* Update .travis.yml

* Update .travis.yml

* Update .travis.yml

* Update test_onnx.py

* Update .travis.yml

* Passing device

* Fixes for test

* Fix for boxes datatype

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

* remove sys.version_info == 2

* remove sys.version_info < 3

* remove from __future__ imports

* modified FasterRCNN to accept negative samples

* remove debug lines

* Change torch.zeros_like to torch.zerros

* Add unit tests

* take the `device` into account
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* docs for faster+mask rcnn coords is clearer

* keypoint rcnn coords format is clearer
Co-authored-by: rvirgolireply <51229032+rvirgolireply@users.noreply.github.com>

Co-authored-by: rvirgolireply <51229032+rvirgolireply@users.noreply.github.com>

* feat: Added __repr__ attribute to GeneralizedRCNNTransform

Added more details to default __repr__ attribute for printing.

* fix: Put back relative imports

* style: Fixed pep8 compliance

Switched strings with  syntax to f-strings.

* test: Added test for GeneralizedRCNNTransform __repr__

Checked integrity of __repr__ attribute

* test: Fixed unittest for __repr__

Fixed the formatted strings in the __repr__ integrity check for GeneralizedRCNNTransform

* fix: Fixed f-strings for earlier python versions

Switched back f-strings to .format syntax for Python3.5 compatibility.

* fix: Fixed multi-line string

Fixed multiple-line string syntax for compatibility

* fix: Fixed GeneralizedRCNNTransform unittest

Fixed formatting of min_size argument of the resizing part

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

* Type of input featmap_names fixed in example.

* Added missing imports.

* update doc

* update doc

* Fix AnchorGenerator if moving from one device to another

* Fixes for the test

* Fix lint following #1695

* V2

* V3

* Make R-CNN models less verbose in script mode

* Fix typo in warning message

* Update KeypointRCNN weights with correct file

* Fix model

* Fix

* Add tests for results in script vs eager mode

This copies some logic from `test_jit.py` to check that a TorchScript'ed
model's outputs are the same as outputs from the model in eager mode.

To support differences in TorchScript / eager mode outputs, an
`unwrapper` function can be provided per-model.

* Fix inception, use PYTORCH_TEST_WITH_SLOW

* Update

* Remove assertNestedTensorObjectsEqual

* Add PYTORCH_TEST_WITH_SLOW to CircleCI config

* Add MaskRCNN unwrapper

* fix prec args

* Remove CI changes

* update

* Update

* remove expect changes

* Fix tolerance bug

* Fix breakages

* Fix quantized resnet

* Fix merge errors and simplify code

* DeepLabV3 has been fixed

* Temporarily disable jit compilation

* almost working...

* respond to comments

* add empty tensor op, handle different output types in generalized rcnn

* clean ups

* address comments

* more changes

* it's working!

* torchscript bugs

* add script/ eager test

* eval script model

* fix flake

* division import

* py2 compat

* update test, fix arange bug

* import division statement

* fix linter

* fixes

* changes needed for JIT master

* cleanups

* remove imagelist_to

* requested changes

* Make FPN backwards-compatible and torchscript compatible

We remove support for feature channels=0, but support for it was already a bit limited

* Fix ONNX regression

* code changes to enable onnx export for keypoint rcnn

* add import

* fix copy paste error

* enable faster rcnn test

* flake8

* smaller image size

* set min/max

* Support Exporting Mask Rcnn to ONNX

* update tetst

* add control flow test

* fix

* update test and fix img_shape

* onnx esport faster rcnn

* test

* address PR comments

* revert unbind workaround

* disable tests for older versions of pytorch

* Support Exporting RPN to ONNX

* address PR comments

* fix cat

* add flatten

* replace cat by stack

* update test to run only on rpn module

* use tolerate_small_mismatch

* Make AnchorGenerator support half precision

* Add test for fasterrcnn with double

* convert gt_boxes to right dtype

* Support Exporting GeneralizedRCNNTransform

* refactor code to address comments

* update tests

* address comments

* revert min_size to test CI

* re-revert min_size

* in_channels_stage2 from backbone.inplanes

* remove type for backward compatible

updated all docstrings and code references for boxes to be consistent with the scheme (x1, y1, x2, y2) (#1110)

* add float32 to keypoint_rcnn docs

* add float32 to faster_rcnn docs

* add float32 to mask_rcnn

* Update faster_rcnn.py

* Update keypoint_rcnn.py

* Update mask_rcnn.py

* Update faster_rcnn.py

* make keypoints float

* make masks uint8

* Update keypoint_rcnn.py

* make labels Int64

* make labels Int64

* make labels Int64

* Add checks for boxes, labels, masks, keypoints

* update mask dim

* remove dtype

* check only if targets is not None

* account for targets being a list

* update target to be list of dict

* Update faster_rcnn.py

* Update keypoint_rcnn.py

* allow boxes to be of float16 type as well

* remove checks on mask

Fixes #1047.