CLAUDE.md

ExecuTorch

Skills

• /setup - Set up environment
• /export - Export model to .pte
• /building - Build runners or C++ libs
• /profile - Profile execution
• /cortex-m - Build, test, or develop the Cortex-M backend
• /binary-size - Analyze and reduce binary size

Reference docs in .claude/: backends, runtime-api, quantization, llm-export, faq, tokenizers

Quick Reference

Install Python package:

./install_executorch.sh        # first time (or .bat on Windows)
pip install -e . --no-build-isolation  # subsequent installs

Build C++ libraries: see CMakeLists.txt; for LLM/ASR runners use Makefile and CMakePresets.json

Run tests: pytest -n auto (Python), ctest --output-on-failure (C++)

Lint: lintrunner init && lintrunner -a

Details: docs/source/using-executorch-building-from-source.md

Naming

• Use "executorch" (lowercase) or "ExecuTorch" (camel case)
• Never "ExecutorTorch"
• "ET" only when space-constrained (unofficial)

Commits

• Only commit when explicitly asked
• No bullet lists of changes; explain review order for large PRs, or omit for small ones
• Disclose PR was authored with Claude

Code Style

• Minimal comments; code should be self-documenting
• Comments only for non-obvious global context
• No trivial (1-2 LOC) single-use helpers unless significantly improving readability
• Explicit state management; no dynamic setattr/getattr patterns
• Match existing style and architecture
• Assume reader knows ExecuTorch/PyTorch basics

When uncertain: choose simpler, more concise.