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[Numpy] Add cross product backward #17637

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merged 1 commit into from
Apr 17, 2020

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Description

Add cross product backward.

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

  • If this change is a backward incompatible change, why must this change be made.
  • Interesting edge cases to note here

@sjtuWangDing sjtuWangDing force-pushed the np_cross_barkward branch 2 times, most recently from 9c6fcc3 to 7680bfc Compare February 20, 2020 13:27
@haojin2 haojin2 self-assigned this Feb 20, 2020
@haojin2 haojin2 added the Numpy label Feb 20, 2020
@sjtuWangDing sjtuWangDing force-pushed the np_cross_barkward branch 3 times, most recently from 34b4449 to 36f65b4 Compare February 26, 2020 05:17
@sjtuWangDing sjtuWangDing force-pushed the np_cross_barkward branch 3 times, most recently from 9fcc7b1 to ebcad81 Compare March 9, 2020 17:32
@sjtuWangDing sjtuWangDing force-pushed the np_cross_barkward branch 4 times, most recently from 36c1359 to 5b7f723 Compare March 25, 2020 08:07
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@mxnet-bot run ci [windows-gpu]

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Jenkins CI successfully triggered : [windows-gpu]

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haojin2 commented Apr 17, 2020

@mxnet-bot run ci [unix-gpu, windows-cpu, windows-gpu]

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Jenkins CI successfully triggered : [windows-cpu, unix-gpu, windows-gpu]

* implement - register op, infershape

* implement - cross product 2x2

* implement - cross product 2x3 3x2 3x3

* fix - cudaError: misaligned address

* add - test code

* fix - test axis=None

* add - Register _backward_npi_cross

* implement - get_cross_backward in test

* implement - cross backward 3x3 2x3 3x2

* implement - cross backward 2x2

* fix - sanity pylint

* fix - move the python wrapper to keep consistency

* impl - FFI for cross op

* impl - FFI benchmark

* fix - reset rtol and atol if dtype is np.float16 in test_optimizer.py:test_sparse_ftrl
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@mxnet-bot run ci [unix-cpu]

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Jenkins CI successfully triggered : [unix-cpu]

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@mxnet-bot run ci [unix-cpu]

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Jenkins CI successfully triggered : [unix-cpu]

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@mxnet-bot run ci [unix-cpu]

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Jenkins CI successfully triggered : [unix-cpu]

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@mxnet-bot run ci [unix-cpu]

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Jenkins CI successfully triggered : [unix-cpu]

@haojin2 haojin2 merged commit f882de0 into apache:master Apr 17, 2020
AntiZpvoh pushed a commit to AntiZpvoh/incubator-mxnet that referenced this pull request Jul 6, 2020
* implement - register op, infershape

* implement - cross product 2x2

* implement - cross product 2x3 3x2 3x3

* fix - cudaError: misaligned address

* add - test code

* fix - test axis=None

* add - Register _backward_npi_cross

* implement - get_cross_backward in test

* implement - cross backward 3x3 2x3 3x2

* implement - cross backward 2x2

* fix - sanity pylint

* fix - move the python wrapper to keep consistency

* impl - FFI for cross op

* impl - FFI benchmark

* fix - reset rtol and atol if dtype is np.float16 in test_optimizer.py:test_sparse_ftrl

Co-authored-by: Ding <[email protected]>
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