pymc-devs/pymc

Add rewrite for Mixture when `comp_dists` can be "fused"

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#6,803 opened on 2023年6月29日

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説明

Description

The following distributions are equivalent:

import pymc as pm

pm.Mixture.dist(w=[0.5, 0.5], comp_dists=[pm.Normal.dist(-1), pm.Normal.dist(1)])
pm.Mixture.dist(w=[0.5, 0.5], comp_dists=pm.Normal.dist([-1, 1]))

But the second one is more efficient, because the logp is vectorized among a single batched Normal.

We could add a rewrite in the logprob_rewrites to convert the former to the second, so that users are not penalized from using the first form (which may be more intuitive for some).

Actually that sort of rewrite stack([rv1, rv2]) -> rv3 could be useful in many places in the logprob submodule

コントリビューターガイド

技術スタック
python
領域
backend
Issue 種別
feature
難度新しい貢献者にとっての実装難度です。1 は非常に小さな変更、5 は専門的な作業です。
3
推定時間経験ある貢献者が調査、実装、テスト、pull request 準備にかけるおおよその時間範囲です。
1-3 hours
活動状況Issue が今どれだけ取り組みやすいかを示します。新しい、活発、古い、ブロック中、またはメンテナー入力待ちなどです。
fresh
明確さ期待される変更、受け入れ条件、次の手順がどれだけ明確かを示します。
clear
前提条件
Familiarity with PyMC's Mixture distributionUnderstanding of logp rewrites in PyMC
初心者向け度初回貢献者にどれだけ取り組みやすいかを 1-100 で推定したスコアです。
30
調査方針
Investigate the logprob rewrites module in the PyMC codebase (likely in pymc/logprob/rewrites.py or similar). The goal is to add a rewrite that detects when a Mixture's comp dists are all instances of the same distribution (e.g., Normal) with different parameters, and replaces them with a single batched distribution. Look at existing rewrites for patterns. Implement the transformation and add corresponding tests to ensure correctness. Check if any linked PRs or comments provide guidance; currently none.