def default_input_fn()

in src/sagemaker_sklearn_container/handler_service.py [0:0]

• 5 lines of code
• 3 McCabe index (conditional complexity)

        def default_input_fn(input_data, content_type):
            """Takes request data and de-serializes the data into an object for prediction.
                When an InvokeEndpoint operation is made against an Endpoint running SageMaker model server,
                the model server receives two pieces of information:
                    - The request Content-Type, for example "application/json"
                    - The request data, which is at most 5 MB (5 * 1024 * 1024 bytes) in size.
                The input_fn is responsible to take the request data and pre-process it before prediction.
            Args:
                input_data (obj): the request data.
                content_type (str): the request Content-Type.
            Returns:
                (obj): data ready for prediction.
            """
            np_array = decoder.decode(input_data, content_type)
            if len(np_array.shape) == 1:
                np_array = np_array.reshape(1, -1)
            return np_array.astype(np.float32) if content_type in content_types.UTF8_TYPES else np_array