Does torch.bmm support batch sparsexdense->dense?

I have found several topics related to sparse x dense -> dense batch-mulbatch-mul-2 and also found the to-do list.
However, it’s not clear about the most up to date status of this question.

So my question is, does torch.bmm support batch version of sparse x dense -> dense?
For example, the expected operation is GxM = Y, where G is sparse of (5, 100, 100), M is dense of (5, 100, 3) and Y is a dense matrix of (5, 100, 3).
Or does torch.spmm support this batch operation?

Sorry that I cannot find the detailed documentation and forgive me if I repost this question.

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I don’t know to be honest. There seems to be a promising package here: https://github.com/cornellius-gp/gpytorch

Check out BDSMM on line 83:

Seems like they change the indices of what would be the 3d sparse matrix to a 2d by adding the number of rows of the each matrix to the next set of indices.