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Quantized Embedding #16691

Merged
merged 13 commits into from
Dec 9, 2019
Merged

Quantized Embedding #16691

merged 13 commits into from
Dec 9, 2019

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xinyu-intel
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Description

Quantized Embedding operator maps integer indices to quantized int8 vector representations, and will pass down min,max values to the next operator.

This operator has been tested on NCF model and the accuracy loss is acceptable.#16689

Due to the limited model accuracy evaluation, we registered this operator with kSupport QuantizeType.

@pengzhao-intel @TaoLv @ZhennanQin @ciyongch

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

  • 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

@pengzhao-intel pengzhao-intel added MKLDNN Quantization Issues/Feature Requests related to Quantization labels Nov 1, 2019
@pengzhao-intel
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@xinyu-intel is this still WIP?

@xinyu-intel xinyu-intel changed the title [WIP] Quantized Embedding Quantized Embedding Nov 28, 2019
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@pengzhao-intel pengzhao-intel left a comment

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LGTM

@pengzhao-intel pengzhao-intel merged commit e48ff96 into apache:master Dec 9, 2019
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2 participants