Comprehensive validation of ML project structure, configurations, code quality, and training readiness. Use when setting up a new project, before training runs, or debugging configuration issues. Validates config loading, data pipeline, model architecture, and dependencies.
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ML Project Validation
Comprehensive validation of ML project structure, configurations, code quality, and training readiness.
Quick Start
# Run full validation
python scripts/validate_project.py
# Quick config check
python src/train.py --cfg job
# Fast dev run (1 batch train/val/test)
python src/train.py trainer.fast_dev_run=true
Validation Checks
1. Project Structure
Required directories:
src/ - Source code
src/models/ - Model implementations
`src/
[Description truncada. Veja o README completo no GitHub.]
