Support Utilities

Configuration models (utils.config_models)

utils.config_models.normalize_split_column(series)[source]

Normalize split labels to train/valid/test while preserving pandas semantics.

Return type:

Any

utils.config_models.validate_yaml_mapping(data, *, source=None)[source]
Parameters:

  • data (Any)

  • source (Path | None)

Return type:

dict[str, Any]

utils.config_models.normalize_loader_config(cfg)[source]

Validate and normalize a loader config without mutating the caller’s dict.

Parameters:

cfg (Any)

Return type:

dict[str, Any]

utils.config_models.normalize_runtime_config(cfg)[source]

Validate a runtime config passed into run_one_config/builders.

Parameters:

cfg (Any)

Return type:

dict[str, Any]

utils.config_models.normalize_echo_config(cfg)[source]
Parameters:

cfg (Any)

Return type:

dict[str, Any]

Pydantic compatibility layer (utils.pydantic_compat)

utils.pydantic_compat.pydantic_model_validate(model_cls, payload)[source]

Compatibility wrapper for pydantic v1/v2 model validation.

Parameters:

  • model_cls (Type[T])

  • payload (Any)

Return type:

T

utils.pydantic_compat.pydantic_model_dump(instance, **kwargs)[source]

Compatibility wrapper for pydantic v1/v2 model dumps.

Parameters:

  • instance (Any)

  • kwargs (Any)

Return type:

dict[str, Any]