Compiler & Kernel Fusion (torch.compile) Integration

Community

Speed up training safely with torch.compile

Authorsovr610
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Torch-based compilation accelerates training/inference by reducing Python overhead and fusion improvements through TorchDynamo/AOT Autograd/TorchInductor, while maintaining safe fallbacks.

Core Features & Use Cases

  • Safe wrapper for safe compilation: maybe_compile ensures non-breaking fallback on failure.
  • Selective compilation via allowlist/blocklist and full-model compilation with various backends/modes.
  • Shape management and bucketing to reduce recompilations, including dynamic shape hints and bucketing strategies for variable-length inputs.
  • DDP/FSDP friendly workflows and smoketest health checks to verify correctness.

Quick Start

Wrap your model with maybe_compile(cfg, logger, sample_batch) to obtain a compiled model ready for training.

Dependency Matrix

Required Modules

torchyaml

Components

scriptsreferencesassets

💻 Claude Code Installation

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Please help me install this Skill:
Name: Compiler & Kernel Fusion (torch.compile) Integration
Download link: https://github.com/sovr610/refffiy/archive/main.zip#compiler-kernel-fusion-torch-compile-integration

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