pymc-devs/pymc

Add function that goes from transformed space to untransformed space

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#6,721 建立於 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

貢獻者指南

技術棧
python
領域
machine learning
議題類型
feature
難度面向新貢獻者的預計實作難度，1 表示很小改動，5 表示專家級工作。
3
預計時間有經驗貢獻者完成調查、實作、測試並準備 pull request 的粗略時間範圍。
1-3 hours
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stale
清晰度議題是否清楚說明預期改動、驗收標準和下一步。
clear
前置要求
PythonPyMCBayesian inferencetransforms
新手友善度1-100 的估計分數，表示該議題對首次貢獻者的友善程度。
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.