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Numpy take operator implementation & bug fix in ndarray.take #15699

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hgt312
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@hgt312 hgt312 commented Jul 30, 2019

Description

Implementation of numpy take operator in mxnet.
Fix a bug that backward computation of ndarray.take does not check argument mode.

The version that cherry-pick on new numpy branch, old pr -> #15567.

Checklist

Essentials

Please feel free to remove inapplicable items for your PR.

  • The PR title starts with [MXNET-$JIRA_ID], where $JIRA_ID refers to the relevant JIRA issue created (except PRs with tiny changes)
  • Changes are complete (i.e. I finished coding on this PR)
  • All changes have test coverage:
  • Unit tests are added for small changes to verify correctness (e.g. adding a new operator)
  • Nightly tests are added for complicated/long-running ones (e.g. changing distributed kvstore)
  • Build tests will be added for build configuration changes (e.g. adding a new build option with NCCL)
  • Code is well-documented:
  • For user-facing API changes, API doc string has been updated.
  • For new C++ functions in header files, their functionalities and arguments are documented.
  • For new examples, README.md is added to explain the what the example does, the source of the dataset, expected performance on test set and reference to the original paper if applicable
  • Check the API doc at http://mxnet-ci-doc.s3-accelerate.dualstack.amazonaws.com/PR-$PR_ID/$BUILD_ID/index.html
  • To the my best knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change

Changes

  • add op take
  • bug fix of nd.take
  • auto remove some whitespaces

Comments

Welcome @reminisce, @haojin2 and others for reviewing.

@hgt312 hgt312 requested a review from szha as a code owner July 30, 2019 06:44
@piyushghai
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@mxnet-label-bot Add [Numpy, Operator]

commits:
improve unittest (+4 squashed commits)
Squashed commits:
[413caa2] fix errors when building gpu
[d576306] add test, local test pass
[dfba360] finish operator, need test
[f82f375] start
@@ -341,6 +341,53 @@ struct Take {
}
};

template<bool clip = true>
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Why are you moving device-specific kernel to .h ?

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Are you looking to share the kernels with the numpy version?

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Are you looking to share the kernels with the numpy version?

Yes, I want to reuse kernels of ndarray version.

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4 participants