Implement sparse computation for DirichletMultinomial.log_prob() #1740
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fehiepsi
approved these changes
Feb 8, 2019
| mask = (value != 0) | ||
| value = value[mask] | ||
| alpha = alpha[mask] | ||
| elementwise[mask] = torch.lgamma(value + alpha) - _log_factorial(value) - torch.lgamma(alpha) |
|
Good to merge? |
|
Yes, ready to merge. |
This was referenced Apr 12, 2021
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As recommended by @fehiepsi , this PR implements a sparse version of the
DirichletMultinomial.log_prob()computation, toggled by a constructor argis_sparse.Note this works with the jit and with cuda, but not with jit+cuda at the same time.
Note we could further speed things up by using a sparse data representation, but that is beyond the scope of this PR.
Tested
torch.lgamma)