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cirron compile

Compile your ML models for production deployment with architecture-specific optimizations and validation.

Usage

Options

Architecture and Framework Support

Without --arch, the architecture comes from inference.device in the model config, then from the project’s hardware block. PyTorch on Apple Silicon hardware (type: gpu, architecture: arm64, which the “Apple Silicon” preset in cirron hardware writes) resolves to mps. Compilation reads src/model.py, optimizes for the target architecture, and writes:
  • PyTorch → models/model_{arch}.pth
  • TensorFlow → models/model_{arch}/
  • Scikit-learn → models/model_{arch}.joblib (via joblib)
Metadata is written to artifacts/model_info.json.

Validation

With --validate, the command verifies required files (src/model.py, requirements.txt), Python version compatibility, architecture-specific requirements (e.g. CUDA availability), model instantiation, and index file format. Every failed check is reported. Without --strict the failures are warnings and compilation continues; with --strict the command stops before compiling and exits with code 35 (VALIDATION_FAILED). If compilation itself fails, the command exits non-zero (36, COMPILE_FAILED, unless a more specific code applies), with or without --strict, so CI jobs fail when no artifacts were produced.

Index Files

YAML form is also accepted. Pass with --index config/index.json or --index config/index.yaml.

Examples

Output

Troubleshooting

Integration