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pytorch-debug

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Diagnose PyTorch errors quickly and reliably.

Software Engineering#debugging#troubleshooting#pytorch#device#oom#gradient#dtype
Authormichaelrizvi
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Debug PyTorch runtime errors by tracing tensors from source to error points and proposing actionable fixes.

Core Features & Use Cases

  • Trace tensors through the data path from dataloader to model outputs to locate where dtype, device, shape, gradient, or memory issues originate
  • Detect and diagnose common PyTorch issues such as dtype mismatches, device placement, shape mismatches, gradient problems, and OOM errors
  • Provide structured diagnostic steps and lightweight code snippets to guide fixes in typical ML workflows

Quick Start

Trace the full data flow of a failing PyTorch tensor and propose an initial diagnosis.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: pytorch-debug
Download link: https://github.com/michaelrizvi/claude-config/archive/main.zip#pytorch-debug

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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