pytorch/xla

[torch_xla] scan_layers fails if the layer have no weights

Open

#8,748 opened on Feb 26, 2025

View on GitHub
 (1 comment) (0 reactions) (1 assignee)C++ (575 forks)github user discovery
enhancementgood first issue

Repository metrics

Stars
 (2,786 stars)
PR merge metrics
 (PR metrics pending)

Description

Seen on https://github.com/pytorch/xla/pull/8734/files#diff-fd0b937d2fd231d227ae1901d62379ae35208c19b3e90f4188a1e272764eaae4

We should support scanning over layers that don't even have any weights and just do pure compute.

Contributor guide

Research direction
Examine the scan layers function in torch xla to understand how it iterates over layers and handles layers with no weights. Look at the referenced PR #8734 for context. The fix should allow scanning layers without weights, possibly by skipping weight related operations when weight list is empty.
Tech stack
python
Domain
machine learningbackend
Issue type
Bug
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
Half day
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Mostly clear
Prerequisites
PyTorchXLA basics
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
50