def default_input_fn()

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

• 3 lines of code
• 2 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 = encoders.decode(input_data, content_type)
    return np_array.astype(np.float32) if content_type in content_types.UTF8_TYPES else np_array