add crp_alpha support

[aluminumbox]

I've noticed that the training args accepts a given value of crp_alpha, and there were issues about adding support for estimation of crp_alpha.

I've added a script, which accepts the train_sequence and train_cluster_id loaded from './data/toy_training_data.npz', iterate through a searching range, and gives the best crp_alpha value estimated from training data.

The script is pretty simply actually. The steps were as follows:

1. Iterate through a range of alpha
2. Iterate through all training samples
3. Calculate p(y|z) for each sample
4. Return the alpha with highest p(y|z)

I hope this script will help some people.

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[aluminumbox]

@googlebot I signed it!

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[wq2012]

@AnzCol Please take a look to see if it is correct. This is trying to address #4

However this PR is trying to do it via a brute force search.

Also, this PR does not have any docstring or unit test for now.

[wq2012]

@aluminumbox Thanks for your contribution.

Please see our updated community contribution guidelines here: https://github.com/google/uis-rnn/blob/master/CONTRIBUTING.md

Specifically, please:

1. Move your submitted file to uisrnn/contrib.
2. Add your contributor information to the submitted files.
3. Add unit tests in tests/contrib.
4. Make sure travis-ci passes.

Thanks.

[codecov-io]

Codecov Report

Merging #70 into master will increase coverage by 0.99%. The diff coverage is 100%.

@@            Coverage Diff             @@
##           master      #70      +/-   ##
==========================================
+ Coverage   90.42%   91.41%   +0.99%     
==========================================
  Files           7        7              
  Lines         449      501      +52     
==========================================
+ Hits          406      458      +52     
  Misses         43       43

Impacted Files	Coverage Δ
uisrnn/contrib/range_search_crp_alpha.py	100% <100%> (ø)
uisrnn/__init__.py

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[wq2012]

@aluminumbox Thanks for your new changes. I left some more comments, but I think we are close.

Also, please be aware that if in the future someone wants to change the code you authored, I will add you as reviewer.

[aluminumbox]

@aluminumbox Thanks for your new changes. I left some more comments, but I think we are close.

Also, please be aware that if in the future someone wants to change the code you authored, I will add you as reviewer.

Thanks for the review. It really improved the code readability.