def input_fn()

in src/inference.py [0:0]

• 11 lines of code
• 4 McCabe index (conditional complexity)

def input_fn(request_body, request_content_type):
    """
    The SageMaker XGBoost model server receives the request data body and the content type,
    and invokes the `input_fn`.
    Return a DMatrix (an object that can be passed to predict_fn).
    """
    if request_content_type == "text/libsvm":
        return xgb_encoders.libsvm_to_dmatrix(request_body)
    
    elif request_content_type == "text/csv":
        return xgb_encoders.csv_to_dmatrix(request_body.rstrip("\n"))
    
    elif request_content_type == "application/json":
        #-----------------
        # single input implementation
        #-----------------
        request = json.loads(request_body)
        feature = ",".join(request.values())
        return xgb_encoders.csv_to_dmatrix(feature.rstrip("\n"))
    else:
        raise ValueError("Content type {} is not supported.".format(request_content_type))