[GitHub] [incubator-mxnet] david-seiler opened a new pull request #14617: PDF operators for the random samplers, and also the Dirichlet

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david-seiler opened a new pull request #14617: PDF operators for the random samplers, and also the Dirichlet
URL: https://github.com/apache/incubator-mxnet/pull/14617
 
 
   ## Description ##
   This PR replaces https://github.com/apache/incubator-mxnet/pull/14579; when I retargeted that from 1.3.x to master, the Jenkins CI build got confused somehow, and refuses to start new test runs (though the Travis build was fine).  All the comments from the review of that PR should be addressed in this changeset.
   
   This PR adds operators for computing the densities of samples drawn from any of the various distributions defined in operator/random, as well as their gradients, plus also the Dirichlet even though we don't yet have a sampler for it.  There are lots of changes to test_random.py to test each PDF alongside its distribution; aside from that, the patch should be entirely stand-alone.  See pdf_op.cc for more-detailed description strings.
   
   ## Checklist ##
   ### Essentials ###
   - [x] Changes are complete (i.e. I finished coding on this PR)
   - [x] All changes have test coverage:
   - Unit tests are added for small changes to verify correctness (e.g. adding a new operator)
   - [x] 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. 
   - [x] To the my best knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change

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