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Pickler override for np ndarrays #16561

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merged 1 commit into from
Oct 21, 2019

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@haojin2 haojin2 commented Oct 21, 2019

Description

...for speeding up data loading under numpy 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 my best knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change

Changes

  • Similar pickler override as nd.NDArray for np.ndarray
  • Unit test

Comments

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

@haojin2 haojin2 added the Numpy label Oct 21, 2019
@haojin2 haojin2 requested a review from szha as a code owner October 21, 2019 08:37
@haojin2 haojin2 self-assigned this Oct 21, 2019
@haojin2 haojin2 removed the request for review from szha October 21, 2019 08:37
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otherwise lgtm

python/mxnet/gluon/data/dataloader.py Outdated Show resolved Hide resolved
@reminisce reminisce merged commit 261d09d into apache:master Oct 21, 2019
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3 participants