pytorch/ignite

Tracking the metrics with performance gaps on XLA

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#2,109 opened on Jul 14, 2021

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HacktoberfestPyDataGlobalenhancementhelp wantedmodule: metrics

Description

🚀 Feature

Since this commit, the metrics have been disabled with xla device due to a performance regression.

https://github.com/pytorch/ignite/blob/7bdf92322a15ba0bea71ad76f3f785b7ea5907c3/ignite/metrics/metric.py#L224-L225

To solve this, it would be interesting to track which metrics work fine and which have lack of performance. Thus, we could think about more specific enable / disable process.

Contributor guide

Tech stack
python
Domain
performancemachine learning
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
4
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.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
needs investigation
Prerequisites
None
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
25
Research direction
Investigate the referenced commit 002b595daa8a8345286c5e096c33e278948686a7 to understand why metrics were disabled on XLA. Examine the code in ignite/metrics/metric.py lines 224-225 to identify the performance regression. Then, measure which metrics (e.g., Accuracy, Loss) perform well on XLA and which cause slowdowns. The goal is to propose a more granular enabling/disabling mechanism for metrics on XLA devices.