inference_schema/parameter_types/standard_py_parameter_type.py
def input_to_swagger(self):
        """
        Generates a swagger schema for the provided sample type

        :return: The swagger schema object.
        :rtype: dict
        """
        if self.sample_input is None:
            raise ValueError("Sample input cannot be None")

        schema = handle_standard_types(self.sample_input)

        # ensure the schema is JSON serializable
        try:
            json.dumps(schema)
        except TypeError as te:
            raise TypeError(ERR_PYTHON_DATA_NOT_JSON_SERIALIZABLE.format(str(te)))

        return schema

        Generates a swagger schema for the provided sample type

        :return: The swagger schema object.
        :rtype: dict
        
Generates a swagger schema for the provided sample type
Generates a swagger schema for the provided sample type
def input_to_swagger(self):
        if self.sample_input is None:
            raise ValueError("Sample input cannot be None")
        schema = handle_standard_types(self.sample_input)
        try:
            json.dumps(schema)
        except TypeError as te:
            raise TypeError(ERR_PYTHON_DATA_NOT_JSON_SERIALIZABLE.format(str(te)))
        return schema
def input_to_swagger ( self ) : if self . sample_input is None : raise ValueError ( "Sample input cannot be None" ) schema = handle_standard_types ( self . sample_input ) try : json . dumps ( schema ) except TypeError as te : raise TypeError ( ERR_PYTHON_DATA_NOT_JSON_SERIALIZABLE . format ( str ( te ) ) ) return schema
Generates a swagger schema for the provided sample type
Generates a swagger schema for the provided sample type
"""
        Generates a swagger schema for the provided sample type

        :return: The swagger schema object.
        :rtype: dict
        """ # ensure the schema is JSON serializable
The swagger schema object.
The swagger schema object .
dict
self