tensorflow / tensorflow/probability

PyTorch support

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Description

Would it be feasible at all to add PyTorch support as a substrate?

Besides the obvious use case, this would enable researchers to implement framework-agnostic probabilistic algorithms that use a Numpy-like API to execute on TF2, JAX, PyTorch.

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First steps

  1. Read the whole issue, then the project's contributing guide.
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  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

No files, tests, or entry points are named. Start by reviewing how the existing TensorFlow 2 and JAX substrates expose the Numpy-like API, then assess the scope of adding PyTorch support. Done should include a clear feasibility conclusion and an agreed implementation scope.

Written by the indexing model from the issue text.

Assessment

Tech stack
numpy, pytorch, tensorflow
Domain
machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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