Problematic casting of integers in `convert_observed_data`
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Description
Description
When we use pytensor.config.floatX=="float32", integer data is downcast to "int16" which has a pretty limited range of 32k. For count-based likelihoods this is way too narrow. I am not sure we should be doing anything with integers to begin with. Why are PyTensor casting rules (and customization flags) not sufficient?
Contributor guide
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Research direction
Start by locating convert_observed_data and tracing how integer observed data is converted when pytensor.config.floatX is set to float32. Review PyTensor's casting rules and customization flags before deciding whether integer conversion should occur. Done requires an agreed behavior that preserves an appropriate integer range for count-based likelihoods.
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Assessment
- Tech stack
- python
- Domain
- backend
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100