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compile-bisect

Bisect PyTorch compiler stages to isolate failing backend, subsystem, and operation.

6|8|Updated May 7, 2026
Search Tags:#pytorch#failure diagnosis#torch.compile#inductor#binary search#compiler debugging#aot autograd
One-click install
npx skills add https://github.com/TorchedHat/ai-marketplace --skill compile-bisect
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: compile-bisect
Source: https://github.com/TorchedHat/ai-marketplace/tree/main/torch-compile/skills/compile-bisect
Command: npx skills add https://github.com/TorchedHat/ai-marketplace --skill compile-bisect

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill isolates the exact PyTorch compiler backend, subsystem, and operation responsible for a compilation failure, reducing debugging time and guesswork.

Core Features & Use Cases

  • Backend Bisection: Binary-search compilation stages from eager through AOT Autograd and Inductor.
  • Subsystem Isolation: Identify failing lowerings, optimization passes, decompositions, CUDA graphs, or common subexpression elimination.
  • Operation-Level Diagnosis: Report precise debug information, such as the failing ATen operation, to guide stage-specific fixes.
  • Use Case: When a torch.compile reproducer crashes in Inductor, run the bisector to determine whether a lowering or optimization pass causes the failure before tracing and fixing the relevant compiler code.

Quick Start

Use the compiler bisector on a deterministic Python reproducer to identify the failing backend, subsystem, and operation.

Frequently Asked Questions about compile-bisect

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I pinpoint the source of a torch.compile failure?▼

To pinpoint a torch.compile failure, apply compiler bisection to binary-search compilation stages from eager through AOT Autograd and Inductor, isolating the exact backend, subsystem, and failing ATen operation responsible for the crash.

What types of PyTorch compiler errors can be diagnosed with bisection?▼

Bisection diagnoses deterministic torch.compile crashes, assertion errors, and incorrect outputs across eager, AOT Autograd, and Inductor stages to identify failing lowerings, optimization passes, decompositions, or CUDA graphs.

How do I isolate a failing ATen operation during PyTorch compilation?▼

Isolate a failing ATen operation by running a deterministic Python reproducer through the compiler bisector, which performs subsystem isolation to report precise debug information for stage-specific fixes.

Do I need a specific reproducer to debug Inductor compilation crashes?▼

Yes, debugging Inductor crashes requires a pass-fail reproducer with backend selection through TORCH_COMPILE_BACKEND, clean Dynamo state, and fresh compilation caches to ensure deterministic bisection results.

What's the best way to determine if an Inductor optimization pass causes a compilation failure?▼

The best way to determine if an Inductor optimization pass causes a failure is using subsystem isolation to binary-search lowerings, optimization passes, and decompositions, reducing guesswork before tracing compiler code.

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