juliusshufan opened a new pull request #12893: Dummy-data based benchmarking 
script for Gluon RNN-API via fused and unfused kernel 
URL: https://github.com/apache/incubator-mxnet/pull/12893
 
 
   ## Description ##
   To easily evaluate the overall status on the performance diffs between the 
fused and unfused/stacked achieved on Gluon RNN API, this script can measure 
the  dummy-data based benchmarking on LSTM and GRU RNN cell, the input-shape 
can either be explictly specified, or a predefined input-shape list. (The 
selected input shaped referring to the 
[Deepbench](https://github.com/baidu-research/DeepBench)). 
   
   ## Checklist ##
   ### Essentials ###
   Please feel free to remove inapplicable items for your PR.
   - [ ] The PR title starts with [MXNET-$JIRA_ID], where $JIRA_ID refers to 
the relevant [JIRA issue](https://issues.apache.org/jira/projects/MXNET/issues) 
created (except PRs with tiny changes)
   - [ ] Changes are complete (i.e. I finished coding on this PR)
   - [ ] All changes have test coverage:
   - Unit tests are added for small changes to verify correctness (e.g. adding 
a new operator)
   - Nightly tests are added for complicated/long-running ones (e.g. changing 
distributed kvstore)
   - Build tests will be added for build configuration changes (e.g. adding a 
new build option with NCCL)
   - [ ] Code is well-documented: 
   - For user-facing API changes, API doc string has been updated. 
   - For new C++ functions in header files, their functionalities and arguments 
are documented. 
   - For new examples, README.md is added to explain the what the example does, 
the source of the dataset, expected performance on test set and reference to 
the original paper if applicable
   - Check the API doc at 
http://mxnet-ci-doc.s3-accelerate.dualstack.amazonaws.com/PR-$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 ###
   Add a standalone python file benchmark_gluon_rnn.py under 
benchmark/python/gluon
   
   ## Comments ##
   - If this change is a backward incompatible change, why must this change be 
made.
   - Interesting edge cases to note here
   

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