Summary:
Hi guys,
I'd like to build Caffe2 with more supported options in Windows with Microsoft Visual Studios.
This is the first pull request.
Running scripts/build_windows_shared.bat is able to build Caffe2 with both CMAKE_BUILD_TYPE=Debug and CMAKE_BUILD_TYPE=Release with Visual Studio 14 2015.
CUDA is 9.0, cudnn is 7.0.5, glog, gflags and lmdb are supported on my system.
Python is 3.5, Detectron works from python interface as well.
It was even possible to debug detectron code and step into caffe2_gpu.dll with pdbs built.
What is disappointing, that c10/experimental ops don't build with this Visual Studio generator, I added special option INCLUDE_EXPERIMENTAL_C10_OPS (default ON) to deal with it in build_windows_shared.bat.
After this pull request the next step is to add Visual Studio 2017 support in the script.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/13550
Reviewed By: ezyang
Differential Revision: D13042597
Pulled By: orionr
fbshipit-source-id: f313f909f599cd582a1d000eff766eef3a9fc4fc
Summary:
Breaking out of #8338
This PR is a workaround for a bug with CUDA9.2 + GCC7.
Here is the error this PR fixed:
.../pytorch/caffe2/operators/elementwise_ops.h: In constructor ‘caffe2::BinaryElementwiseWithArgsOp<InputTypes, Context, Functor, OutputTypeMap>::BinaryElementwiseWithArgsOp(const caffe2::OperatorDef&, caffe2::Workspace*)’:
.../pytorch/caffe2/operators/elementwise_ops.h:106:189: error: ‘GetSingleArgument<bool>’ is not a member of ‘caffe2::BinaryElementwiseWithArgsOp<InputTypes, Context, Functor, OutputTypeMap>’
BinaryElementwiseWithArgsOp(const OperatorDef& operator_def, Workspace* ws)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10510
Reviewed By: orionr
Differential Revision: D9319742
Pulled By: mingzhe09088
fbshipit-source-id: ce59e3db14539f071f3c20301e77ca36a6fc3f81
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/9403
In BBoxTransform and GenerateProposal ops, clip_boxes makes sure the bbox fits
within the images. For rotated boxes, this doesn't always make sense as there
could be multiple ways to clip a rotated box within an image boundary.
Moreover, clipping to a horizontal box means we leave out pixels of interest
potentially. Therefore, we clip only boxes with angle almost equal to 0 (with a
specified `angle_thresh` tolerance).
Reviewed By: pjh5
Differential Revision: D8828588
fbshipit-source-id: 39c1eafdb5d39d383780faa0a47e76149145e50c
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/9056
Closes https://github.com/pytorch/pytorch/pull/9056
Updates bbox_transform for rotated boxes with angle info to normalize the
predicted angle to be within [angle_bound_lo, angle_bound_hi] range.
Reviewed By: pjh5
Differential Revision: D8706240
fbshipit-source-id: f3ee834cf362736136e285f0f8f0c063af94a879
Summary:
Updated bbox_transform op to match detectron training code better.
- Set apply_scale=False and correct_transform_coords=True to match detectron training/inference code.
Reviewed By: wat3rBro
Differential Revision: D6782894
fbshipit-source-id: 053d9847bf2b3c62a535499017a8413d78871ee0
Summary:
- Moved mask-rcnn inference operators to open source caffe2.
- Registered GeneratedProposalsOp as GenerateProposals in addition to GenerateProposalsCPP.
Reviewed By: rbgirshick
Differential Revision: D6747190
fbshipit-source-id: be98d6b56b5b53b13af46e839f5ceaf27f7fddc3
