def _is_parameter_valid()

in src/python/tensorflow_cloud/tuner/utils.py [0:0]

• 56 lines of code
• 17 McCabe index (conditional complexity)

def _is_parameter_valid(param: Dict[Text, Any]):
    """Checks if study_config parameter is valid."""
    if not param.get("parameter"):
        raise ValueError('"parameter" (name) is not specified.')
    if not param.get("type"):
        raise ValueError("Parameter {} type is not specified.".format(param))
    if param["type"] == _DISCRETE:
        if not param.get("discrete_value_spec"):
            raise ValueError(
                "Parameter {} is missing discrete_value_spec.".format(param)
            )
        if not isinstance(param["discrete_value_spec"].get("values"), list):
            raise ValueError(
                'Parameter spec {} is missing "values".'.format(
                    param["discrete_value_spec"]
                )
            )
    elif param["type"] == _CATEGORICAL:
        if not param.get("categorical_value_spec"):
            raise ValueError(
                "Parameter {} is missing categorical_value_spec.".format(param)
            )
        if not isinstance(param["categorical_value_spec"].get("values"), list):
            raise ValueError(
                'Parameter spec {} is missing "values".'.format(
                    param["categorical_value_spec"]
                )
            )
    elif param["type"] == _DOUBLE:
        if not param.get("double_value_spec"):
            raise ValueError(
                "Parameter {} is missing double_value_spec.".format(param))
        spec = param["double_value_spec"]
        if not (
            isinstance(spec.get("min_value"), float)
            and isinstance(spec.get("max_value"), float)
        ):
            raise ValueError(
                'Parameter spec {} requires both "min_value" and '
                '"max_value".'.format(spec)
            )
    elif param["type"] == _INTEGER:
        if not param.get("integer_value_spec"):
            raise ValueError(
                "Parameter {} is missing integer_value_spec.".format(param)
            )
        spec = param["integer_value_spec"]
        if not (
            isinstance(spec.get("min_value"), int)
            and isinstance(spec.get("max_value"), int)
        ):
            raise ValueError(
                'Parameter spec {} requires both "min_value" and '
                '"max_value".'.format(spec)
            )
    else:
        raise ValueError("Unknown parameter type: {}.".format(param["type"]))