pymc-devs/pymc

Add function that goes from transformed space to untransformed space

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#6,721 创建于 2023年5月18日

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enhancementshelp wantedtrace-backend

描述

Description

Because we don't save transformed variables in the returned InferenceData (why not?) it's not easy to evaluate the model logp once we have a trace.

One could rewrite the model without transforms (and we can make this automatically for the user) This is possible with https://www.pymc.io/projects/docs/en/stable/api/model/generated/pymc.model.transform.conditioning.remove_value_transforms.html

But someone might still want to evaluate it in the original model (with jacobians and all that).

One dirty implementation is given here: https://discourse.pymc.io/t/logp-questions-synthetic-dataset-to-evaluate-modeling/12129/6?u=ricardov94

贡献者指南

技术栈
python
领域
machine learning
议题类型
feature
难度面向新贡献者的预计实现难度，1 表示很小改动，5 表示专家级工作。
3
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stale
清晰度议题是否清楚说明期望改动、验收标准和下一步。
clear
前置要求
PythonPyMCBayesian inferencetransforms
新手友好度1-100 的估计分数，表示该议题对首次贡献者的友好程度。
40
研究方向
Investigate the existing `remove value transforms` function in pymc.model.transform.conditioning to understand current support for evaluating without transforms. Review the Discourse post linked in the issue for a potential implementation approach. Examine how transformed variables are stored in InferenceData to determine the best way to expose an inverse transform function.
Add function that goes from transformed space to untransformed space · pymc-devs/pymc#6721 | Good First Issue