Validate Training Setup

This page documents the lightweight validation helper used to confirm that a TE training configuration can produce a valid first batch and finite metrics.

One-batch validation check for TE training and tree baselines.

scripts.training.validate_training_setup.build_validation_summary(config_path, output_directory, batch_summary, batch_output_dictionary, training_config)[source]

Build the persisted validation summary for one setup check.

Parameters:
  • config_path (Path) – Canonical training configuration path.

  • output_directory (Path) – Validation artifact directory.

  • batch_summary (dict[str, object]) – Structural batch summary from the validation step.

  • batch_output_dictionary (dict[str, Tensor]) – Output tensors and metrics computed by the regression module.

  • training_config (dict[str, object]) – Prepared training configuration with artifact metadata.

Returns:

YAML-serializable validation summary.

Return type:

dict[str, object]

scripts.training.validate_training_setup.validate_training_setup(config_path, output_suffix='validation_check')[source]

Run a lightweight validation check for the configured training setup.

Parameters:
  • config_path (Path) – YAML training configuration path.

  • output_suffix (str) – Suffix appended to the validation artifact run name.

Returns:

Validation summary YAML path plus generated Markdown report path.

Return type:

tuple[Path, Path]

scripts.training.validate_training_setup.parse_command_line_arguments()[source]

Parse command-line arguments for the validation helper script.

Return type:

Namespace

scripts.training.validate_training_setup.main()[source]

Run the validation helper entry point from the command line.

Return type:

None