tfma.default_evaluators

Returns the default evaluators for use in ExtractAndEvaluate.

tfma.default_evaluators(
    eval_shared_model: Optional[tfma.types.EvalSharedModel] = None,
    eval_config: Optional[tfma.EvalConfig] = None,
    schema: Optional[schema_pb2.Schema] = None,
    compute_confidence_intervals: Optional[bool] = False,
    min_slice_size: int = 1,
    serialize: bool = False,
    random_seed_for_testing: Optional[int] = None,
    config_version: Optional[int] = None
) -> List[tfma.evaluators.Evaluator]

eval_shared_model Optional shared model (single-model evaluation) or list of shared models (multi-model evaluation). Only required if there are metrics to be computed in-graph using the model.
eval_config Eval config.
schema A schema to use for customizing default evaluators.
compute_confidence_intervals Deprecated (use eval_config).
min_slice_size Deprecated (use eval_config).
serialize Deprecated.
random_seed_for_testing Provide for deterministic tests only.
config_version Optional config version for this evaluation. This should not be explicitly set by users. It is only intended to be used in cases where the provided eval_config was generated internally, and thus not a reliable indicator of user intent.