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[Quantization] Support zero-size tensor input for quantization flow #15031

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merged 4 commits into from
May 23, 2019
Merged

[Quantization] Support zero-size tensor input for quantization flow #15031

merged 4 commits into from
May 23, 2019

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ciyongch
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Description

This PR is to support zero-size tensor input for quantization flow.
Let's take RNN related model as an example, the begin_state is always initialized into shape (0, self._num_hidden), it worked well in FP32 pass, but failed in INT8 pass due to unknown dimension error with latest MXNet code base.
With this patch, models with such inputs are able to be quantized and run in INT8 mode.

@pengzhao-intel @TaoLv @ZhennanQin

Checklist

Essentials

Please feel free to remove inapplicable items for your PR.

  • The PR title starts with [MXNET-$JIRA_ID], where $JIRA_ID refers to the relevant JIRA issue created (except PRs with tiny changes)
  • Changes are complete (i.e. I finished coding on this PR)
  • All changes have test coverage:
  • Unit tests are added for small changes to verify correctness (e.g. adding a new operator)
  • Nightly tests are added for complicated/long-running ones (e.g. changing distributed kvstore)
  • Build tests will be added for build configuration changes (e.g. adding a new build option with NCCL)
  • Code is well-documented:
  • For user-facing API changes, API doc string has been updated.
  • For new C++ functions in header files, their functionalities and arguments are documented.
  • For new examples, README.md is added to explain the what the example does, the source of the dataset, expected performance on test set and reference to the original paper if applicable
  • Check the API doc at http:https://mxnet-ci-doc.s3-accelerate.dualstack.amazonaws.com/PR-$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
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@ZhennanQin @TaoLv @xinyu-intel please help take a review.

@pengzhao-intel
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Please also add a test case

@pengzhao-intel pengzhao-intel mentioned this pull request May 22, 2019
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@pengzhao-intel pengzhao-intel added this to Review in progress in CPU Performance and Quantization May 22, 2019
@pengzhao-intel pengzhao-intel mentioned this pull request May 22, 2019
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@ciyongch
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@pengzhao-intel @TaoLv test case is added, redundant file is remove. Please help to review again:)

pengzhao-intel
pengzhao-intel approved these changes May 22, 2019
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Thanks for the improvements.

LGTM

CPU Performance and Quantization automation moved this from Review in progress to Reviewer approved May 22, 2019
@ZhennanQin
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LGTM.

@pengzhao-intel
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Thanks for your contribution. Merging now.

@pengzhao-intel pengzhao-intel merged commit d4e458e into apache:master May 23, 2019
CPU Performance and Quantization automation moved this from Reviewer approved to Done May 23, 2019
haohuanw pushed a commit to haohuanw/incubator-mxnet that referenced this pull request Jun 23, 2019
@ciyongch
[Quantization] Support zero-size tensor input for quantization flow (a…
f39b0cc 
…pache#15031)

* [Quantization] Support zero-size tensor input for quantization flow

* Comment out quantized_act and quantized_sum

* retrigger CI

* Add test cases
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@TaoLv TaoLv TaoLv approved these changes

@pengzhao-intel pengzhao-intel pengzhao-intel approved these changes

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@ciyongch @pengzhao-intel @ZhennanQin @TaoLv