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]

Args
`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.

tfma.default_evaluators

Args