No torch gradient with respect to the gamma shape parameter
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Assessment
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Newbie friendliness
- 76/100
- Issue type
- Documentation
- Clarity
- Clearly specified
- Activity status
- Active
- Domain
- documentation, machine-learning
Research direction
Start with docs/special_functions_audit.md and check how its torch gradient results are recorded for the incomplete gamma functions. The issue demonstrates the limitation with sr.crps_gamma and a gradient with respect to shape; clarify that the reported PASS applies only to the second argument. Done when the audit accurately describes this limitation.
Written by the indexing model from the issue text.
Description
torch's gammainc has no derivative with respect to its first argument, so for example crps_gamma cannot be differentiated with respect to shape on torch.
a = torch.tensor(2.0, dtype=torch.float64, requires_grad=True)
sr.crps_gamma(torch.tensor(1.5, dtype=torch.float64), a, torch.tensor(1.0, dtype=torch.float64)).backward()
# NotImplementedError: the derivative for 'igamma: input' is not implemented.
docs/special_functions_audit.md lists the incomplete gamma functions as torch grad PASS, which only holds for the second argument. At minimum the doc should say so.
- Dominant language
- Python
- Stars
- 108
- Forks
- 15
- Avg merge
- 1h 42m
- Merged PRs (30d)
- 9
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