[MXNET-836] RNN Example for Scala

[lanking520]

Description

This is the example written in new API in Scala. It include the following two tests:

• LSTM Bucketing
• charRNN Training
  RNN Example not supported for MXNet Scala #11571
  @yzhliu @nswamy @andrewfayres

This example also include a change on the DataDesc by defining a default settings for shape size = 2 in NT format

Checklist

Essentials

Please feel free to remove inapplicable items for your PR.

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

[lanking520]

Please skip these section from your code review as it did not change

[lanking520]

Add download: #11866

[Roshrini]

@yzhliu @nswamy Can you review this PR and approve it if ready? tracking this one for MXNet 1.3 release. Thanks!

[nswamy]

I would like this PR to wait until we have #11844 is merged in so we make sure that DataDesc works with RNN & Bucketing moduel

[lanking520]

So I think probably we cannot make this as 1.3 release for now @Roshrini.

[Roshrini]

@nswamy @lanking520 Thanks for the update :)

[andrewfayres]

lgtm

Unfortunately github makes looking at this far more confusing than it should be.

[nswamy]

@lanking520 thanks for fixing the RNN example, @andrewfayres Thanks for the review and yes indeed the whitespace/formatting changes make it hard to look at it.