pyro-ppl/pyro

FR Tutorial: how to implement custom distributions/transforms/constraints

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#2,657 opened on Oct 8, 2020

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Description

A common pattern in applied probabilistic modeling is to implement domain-specific distributions, constraints, and transforms for individual data science projects. That is, it is common for users to extend Pyro/NumPyro with new components.

Contributor guide

Research direction
Examine Pyro's distribution, transform, and constraint base classes in the source code. Review existing tutorials and the documentation structure. Write a tutorial that guides users through creating a custom distribution, transform, and constraint with examples and validation tests.
Tech stack
pythonpytorch
Domain
machine learning
Issue type
Documentation
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-2 days
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Clear
Prerequisites
PythonGitPyro
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
70