[MKLDNN]Refactor requantize to speed up execution

[ZhennanQin]

Description

Currently, requantize is too slow to use. This PR is to refactor its MKLDNN implementation to make it usable. Other change is, add out_type option to make it align with quantizeV2. Now requantize can support output uint8 if could.

@pengzhao-intel @TaoLv @reminisce @anirudh2290

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

[piyushghai]

@ZhennanQin Thanks for your contributions. Can you also look into the CI failures ?

@mxnet-label-bot Add [pr-work-in-progress, Quantization, MKLDNN]

[glingyan]

@ZhennanQin further action for this PR？

[glingyan]

@ZhennanQin the patch could not be applied for with #14641

diff a/src/operator/quantization/mkldnn/mkldnn_quantize_v2-inl.h b/src/operator/quantization/mkldnn/mkldnn_quantize_v2-inl.h (rejected hunks)
@@ -70,7 +70,7 @@ static void MKLDNNQuantizeComputeKer(const std::vector& inputs,
}
}

• auto out_type = GetOutputType(param);

• auto out_type = GetQuantizeOutputType(param);
  if (out_type == mshadow::kUint8) {
  real_range = std::max(0.f, data_max);
  quantized_range = MaxValue();
  @@ -141,7 +141,7 @@ static void MKLDNNQuantizeV2Compute(const nnvm::NodeAttrs& attrs, const OpContex
  MKLDNNStream::Get()->Submit();
  }
  } else {

• auto out_type = GetOutputType(param);

• auto out_type = GetQuantizeOutputType(param);
  if (out_type == mshadow::kUint8) {
  MKLDNNQuantizeComputeKer<float, uint8_t>(inputs, outputs, param, req);
  } else if (out_type == mshadow::kInt8) {

[TaoLv]

@ZhennanQin please take a look at the conflicts and CI failures. Thank you.

[pengzhao-intel]

LGTM

[xinyu-intel]

.

[pengzhao-intel]

Thanks all of the contribution. Merging now :)