pytorch/ignite

More EpochMetric's compute_fn output types

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#1,757 创建于 2021年3月8日

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 (3 评论) (0 反应) (0 负责人)Python (4,313 star) (602 fork)batch import
HacktoberfestPyDataGlobalenhancementhelp wantedmodule: metrics

描述

🚀 Feature

Following https://github.com/pytorch/ignite/pull/1700#issuecomment-787151203 we would like to improve EpochMetric by supporting more output types returned by compute_fn:

  • EpochMetric should work with compute_fn outputs: scalars, tensors, tuple/list/mapping of tensors vs currently only scalars

A code snippet on possible implementation: https://github.com/pytorch/ignite/pull/1700#issuecomment-790413236 (It is not tested and maybe wrong, just an idea of how to do it).

It would be also helpful to raise a more user friendly error message if output type is not supported.

We need to update the docs as well.

If interested in fixing this issue, please leave a comment to assign the issue to you.

贡献者指南

技术栈
pythonpytorch
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
预计时间有经验贡献者完成调查、实现、测试并准备 pull request 的粗略时间范围。
1-2 days
活动状态议题当前的可参与程度：新鲜、活跃、陈旧、阻塞或等待维护者输入。
stale
清晰度议题是否清楚说明期望改动、验收标准和下一步。
mostly clear
前置要求
Familiarity with PyTorchUnderstanding of EpochMetric class
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。
60
研究方向
Review the existing implementation of EpochMetric in the ignite codebase (likely in ignite/metrics/epoch metric.py). Understand how compute fn is currently used and the output types it supports. Examine the code snippet in the linked comment for a potential approach. Then implement support for scalars, tensors, and tuple/list/mapping of tensors. Also add a more user friendly error message for unsupported types. Finally, update the documentation to reflect the new capabilities.