tensorflow / tensorflow/probability
fix shape inconsistencies for lambertw_transform between tailweight and input tensors
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Description
When tailweight is not a simple float, but a tensor with shape != shape of input/output, then the _HeavyTailOnly transform needs to overwrite the forward/inverse _batch_shape[_tensor] methods appropriately.
This is in preparation of LambertWDistribution classes, where the distribution property tests fail due to these inconsistencies.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the _HeavyTailOnly transform and inspect its forward/inverse _batch_shape and _batch_shape_tensor methods, then trace how LambertWDistribution classes use them. Reproduce the distribution property-test failures with a tensor tailweight whose shape differs from the input/output, and consider the issue done when those shape inconsistencies no longer occur.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- tensorflow
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100