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np.broadcast_to extension #17358

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merged 1 commit into from
Jan 23, 2020
Merged

np.broadcast_to extension #17358

merged 1 commit into from
Jan 23, 2020

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haojin2
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@haojin2 haojin2 commented Jan 17, 2020

Description

Extending broadcast_to to infer shape from input tensor, useful under symbolic mode.

Checklist

Essentials

Please feel free to remove inapplicable items for your PR.

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

Changes

  • Feature1, tests, (and when applicable, API doc)
  • Feature2, tests, (and when applicable, API doc)

Comments

FYI @szhengac @sxjscience @xidulu

@haojin2 haojin2 added the Numpy label Jan 17, 2020
@haojin2 haojin2 self-assigned this Jan 17, 2020
@szhengac
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Great!

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@xidulu xidulu left a comment

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LGTM.

Thx for your contribution!

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4 participants