xidulu edited a comment on issue #18140:
URL:
https://github.com/apache/incubator-mxnet/issues/18140#issuecomment-618131555
Hi @leandrolcampos
Currently, pathwise gradient is only implemented for `mx.np.random.{normal,
gumbel, logistic, weibull, exponential, pareto}` in the backend.
We are planning to implement (in C++ backend) implicit reparam grad for
Gamma related distribution in the future, which is extremely useful, as you
pointed out, in scenarios like `BBVI for LDA`.
Another possible solution, is to wrap the sampling Op as a CustomOp, which
allows you to manually define the backward computation with Python.
https://mxnet.apache.org/api/python/docs/tutorials/extend/customop.html
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
[email protected]
