---
title: "torch.compile & Kernel Fusion"
description: "What torch.compile records from a decode step, the fused kernels it generates, how inference engines use it by default, and how to see what compiled."
canonical_url: "https://fanout.sh/inference-eng/curriculum/15-02"
md_url: "https://fanout.sh/inference-eng/curriculum/15-02.md"
access: "pro-preview"
---

# torch.compile & Kernel Fusion

What torch.compile records from a decode step, the fused kernels it generates, how inference engines use it by default, and how to see what compiled.

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## Public preview

A runtime that already knows the sequence it is about to run has nothing left to decide. The eager execution overhead lesson closed on that property and priced its absence: several hundred separately arranged operations inside a decode step whose whole budget is a few milliseconds. PyTorch's route from deciding to knowing is one function, torch.compile, introduced in PyTorch 2.x…

## In this lesson

- The recorded program
- The generated kernel
- A decode step through the compiler
- The engine's default path
- Seeing what compiled

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