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[Numpy] Change semantics of ndim for operators in src/operator/contrib
#14409
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@mxnet-label-bot add [Numpy, Operator, pr-awaiting-review] |
marcoabreu
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Could we add a cast to be compatible with nnvm::TShape,Tuple? |
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@wkcn Are you referring to converting |
reminisce
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Mar 14, 2019
wkcn
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Mar 14, 2019
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@wkcn Are you referring to converting
nnvm::Tupletomxnet::Tuple? I wonder why it's needed?
Yes. I think some custom C++ operators by users may use nnvm::Tuple, so add a cast to be compatible with them. But it may be not necessary.
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@junrushao1994 Could you address the CR comments so that we can merge this PR? Thanks. |
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@reminisce of course! Will do it today! |
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@reminisce Hey I updated accordingly |
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Thank @junrushao1994 and @wkcn. This is merged. |
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* [numpy] Shape support scalar tensor (#14315) * Support scalar and zero-size tensors with np.sum * Add sanity check when ndim is set * [Numpy] Change semantics of ndim for operators in `src/operator/contrib` (#14409) * Initial commit * Address comments * [WIP] Use new shape definition (#14453) * Init checkin * Fix ndarray alloc bug * Use TShape(0) as default empty tuple params * Fix bugs * Fix TShape init value * Fix infer shape pass shape type and reshape infer shape func * [numpy] Fix unit tests after introducing numpy compatible shapes (#14487) * Fix infer shape rnn * Fix boolean mask and custom op unit tests * Fix multi proposal * Fix diag * Add global switch for backward compatibility and fix infer shape bugs * Fix slice op infer shape * Fix rnn infer shape * Add util funcs for ndim_is_known and dim_size_is_known * Revert rnn_cell.py * Fix a bug to pass the test in test_contrib_rnn (#14520) * fix. * remove type conversion. * remove type cast. * [numpy] Fix test_dynamic_shape.test_dynamic_shape (#14538) * Initial commit * Address comments from Jun * [numpy] Fix numpy import in python2 (#14537) * Fix several test failures * Fix subgraph op infer shape * Fix sparse slice * Fix deconv infer shape * Fix numpy import compatibility problem in python2 * fix concat and slice (#14549) * fix R-package (#14536) * Fix cpp package build after using new shape definition (#14554) * Fix pooling_v1 and deformable_convolution param initialization (#14577) * Fix pooling_v1 param initialization * Fix deformable_convolution param initialization * [Numpy] Misc fix (#14612) * [Numpy] Misc Fix * fix build * !shape_is_none => shape_is_known * Address comments * Fix * [Numpy] fix test_operator_gpu.test_upsampling_bilinear_with_type (#14557) * Fix test_operator_gpu.test_upsampling_bilinear_with_type * Address comments * [Numpy] Java/Scala modification (#14625) * modify jni to support 0 dim/shape * fix transpose axes default value * fix shape index bug (#14630) * fix jni lint (#14634) * [numpy] Fix numpy branch failing tests in CI (#14639) * Remove numpy namespaces for operator registration * Fix bug when shape is compeltely unknown * Fix singed/unsigned compare warning * Fix CI * Fix pylint * Avoid launching gpu kernels for zero-size output tensors * Fix test_ndarray * Fix binary broadcast with zero-size tensors * Better error message for infer shape failure in imperative * Fix TShape constructor ambiguity on certain platforms * Fix mkldnn build failure * Fix build failure in gpu and cpp test * Fix gpu cpp test build with mkldnn * Fix mkldnn cpp test * Fix concatenating zero-size tensors * Avoid letting mkldnn handle zero-size tensors in concat * Fix quantized_concat infer shape * Try to fix perl c api * fix invalid ndarray dispose (#14657) * swig fixes for the changes in c_api.h (#14655) * Rename np_comp to np_compat for readability * Fix import error * Keep old c apis unchanged * Fix lint * Rebase and fix build * Fix R build failure * Fix Perl build failure * Rebase with master * Address cr comments * Use just one scope to represent numpy compatibility * Add code comment to NumpyScope object in Scala * Add use_np_compat decorator * Fix pylint
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* [numpy] Shape support scalar tensor (apache#14315) * Support scalar and zero-size tensors with np.sum * Add sanity check when ndim is set * [Numpy] Change semantics of ndim for operators in `src/operator/contrib` (apache#14409) * Initial commit * Address comments * [WIP] Use new shape definition (apache#14453) * Init checkin * Fix ndarray alloc bug * Use TShape(0) as default empty tuple params * Fix bugs * Fix TShape init value * Fix infer shape pass shape type and reshape infer shape func * [numpy] Fix unit tests after introducing numpy compatible shapes (apache#14487) * Fix infer shape rnn * Fix boolean mask and custom op unit tests * Fix multi proposal * Fix diag * Add global switch for backward compatibility and fix infer shape bugs * Fix slice op infer shape * Fix rnn infer shape * Add util funcs for ndim_is_known and dim_size_is_known * Revert rnn_cell.py * Fix a bug to pass the test in test_contrib_rnn (apache#14520) * fix. * remove type conversion. * remove type cast. * [numpy] Fix test_dynamic_shape.test_dynamic_shape (apache#14538) * Initial commit * Address comments from Jun * [numpy] Fix numpy import in python2 (apache#14537) * Fix several test failures * Fix subgraph op infer shape * Fix sparse slice * Fix deconv infer shape * Fix numpy import compatibility problem in python2 * fix concat and slice (apache#14549) * fix R-package (apache#14536) * Fix cpp package build after using new shape definition (apache#14554) * Fix pooling_v1 and deformable_convolution param initialization (apache#14577) * Fix pooling_v1 param initialization * Fix deformable_convolution param initialization * [Numpy] Misc fix (apache#14612) * [Numpy] Misc Fix * fix build * !shape_is_none => shape_is_known * Address comments * Fix * [Numpy] fix test_operator_gpu.test_upsampling_bilinear_with_type (apache#14557) * Fix test_operator_gpu.test_upsampling_bilinear_with_type * Address comments * [Numpy] Java/Scala modification (apache#14625) * modify jni to support 0 dim/shape * fix transpose axes default value * fix shape index bug (apache#14630) * fix jni lint (apache#14634) * [numpy] Fix numpy branch failing tests in CI (apache#14639) * Remove numpy namespaces for operator registration * Fix bug when shape is compeltely unknown * Fix singed/unsigned compare warning * Fix CI * Fix pylint * Avoid launching gpu kernels for zero-size output tensors * Fix test_ndarray * Fix binary broadcast with zero-size tensors * Better error message for infer shape failure in imperative * Fix TShape constructor ambiguity on certain platforms * Fix mkldnn build failure * Fix build failure in gpu and cpp test * Fix gpu cpp test build with mkldnn * Fix mkldnn cpp test * Fix concatenating zero-size tensors * Avoid letting mkldnn handle zero-size tensors in concat * Fix quantized_concat infer shape * Try to fix perl c api * fix invalid ndarray dispose (apache#14657) * swig fixes for the changes in c_api.h (apache#14655) * Rename np_comp to np_compat for readability * Fix import error * Keep old c apis unchanged * Fix lint * Rebase and fix build * Fix R build failure * Fix Perl build failure * Rebase with master * Address cr comments * Use just one scope to represent numpy compatibility * Add code comment to NumpyScope object in Scala * Add use_np_compat decorator * Fix pylint
haohuanw
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Jun 23, 2019
* [numpy] Shape support scalar tensor (apache#14315) * Support scalar and zero-size tensors with np.sum * Add sanity check when ndim is set * [Numpy] Change semantics of ndim for operators in `src/operator/contrib` (apache#14409) * Initial commit * Address comments * [WIP] Use new shape definition (apache#14453) * Init checkin * Fix ndarray alloc bug * Use TShape(0) as default empty tuple params * Fix bugs * Fix TShape init value * Fix infer shape pass shape type and reshape infer shape func * [numpy] Fix unit tests after introducing numpy compatible shapes (apache#14487) * Fix infer shape rnn * Fix boolean mask and custom op unit tests * Fix multi proposal * Fix diag * Add global switch for backward compatibility and fix infer shape bugs * Fix slice op infer shape * Fix rnn infer shape * Add util funcs for ndim_is_known and dim_size_is_known * Revert rnn_cell.py * Fix a bug to pass the test in test_contrib_rnn (apache#14520) * fix. * remove type conversion. * remove type cast. * [numpy] Fix test_dynamic_shape.test_dynamic_shape (apache#14538) * Initial commit * Address comments from Jun * [numpy] Fix numpy import in python2 (apache#14537) * Fix several test failures * Fix subgraph op infer shape * Fix sparse slice * Fix deconv infer shape * Fix numpy import compatibility problem in python2 * fix concat and slice (apache#14549) * fix R-package (apache#14536) * Fix cpp package build after using new shape definition (apache#14554) * Fix pooling_v1 and deformable_convolution param initialization (apache#14577) * Fix pooling_v1 param initialization * Fix deformable_convolution param initialization * [Numpy] Misc fix (apache#14612) * [Numpy] Misc Fix * fix build * !shape_is_none => shape_is_known * Address comments * Fix * [Numpy] fix test_operator_gpu.test_upsampling_bilinear_with_type (apache#14557) * Fix test_operator_gpu.test_upsampling_bilinear_with_type * Address comments * [Numpy] Java/Scala modification (apache#14625) * modify jni to support 0 dim/shape * fix transpose axes default value * fix shape index bug (apache#14630) * fix jni lint (apache#14634) * [numpy] Fix numpy branch failing tests in CI (apache#14639) * Remove numpy namespaces for operator registration * Fix bug when shape is compeltely unknown * Fix singed/unsigned compare warning * Fix CI * Fix pylint * Avoid launching gpu kernels for zero-size output tensors * Fix test_ndarray * Fix binary broadcast with zero-size tensors * Better error message for infer shape failure in imperative * Fix TShape constructor ambiguity on certain platforms * Fix mkldnn build failure * Fix build failure in gpu and cpp test * Fix gpu cpp test build with mkldnn * Fix mkldnn cpp test * Fix concatenating zero-size tensors * Avoid letting mkldnn handle zero-size tensors in concat * Fix quantized_concat infer shape * Try to fix perl c api * fix invalid ndarray dispose (apache#14657) * swig fixes for the changes in c_api.h (apache#14655) * Rename np_comp to np_compat for readability * Fix import error * Keep old c apis unchanged * Fix lint * Rebase and fix build * Fix R build failure * Fix Perl build failure * Rebase with master * Address cr comments * Use just one scope to represent numpy compatibility * Add code comment to NumpyScope object in Scala * Add use_np_compat decorator * Fix pylint
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(This is the PR to the numpy branch, so please be aware it is not aimed for production until the numpy branch is merged successfully)
This PR in part of progress of #14323, which contains improvement of the following contrib operators.
In addition to the header files assigned to me, I also change some of the following
.ccfiles which relates tondim. I am not 100% sure about the coverage, so reviewers please let me know if there is anything I left.The contrib operators are mostly irregular workloads coming from many contributors, which is one of the most difficult part (another difficult part is customized/python operators). I am trying my best not to break it. However, if there is anything I didn't take into consideration, please don't hesitate to let me know. Many thanks!
CC: @reminisce @szha @eric-haibin-lin @zheng-da @yzhliu @wkcn