def METHOD_NAME(result_dict, output_tensors):
    output = {}
    if "outputs" in result_dict:
        keyname = "outputs"
        if type(result_dict[keyname]) is dict:
            for output_tensor in output_tensors:
                output[output_tensor] = np.asarray(
                    result_dict[keyname][output_tensor])
        else:
            output[output_tensors[0]] = np.asarray(result_dict[keyname])
    elif "predictions" in result_dict:
        keyname = "predictions"
        if type(result_dict[keyname][0]) is dict:
            for row in result_dict[keyname]:
                logger.info(row.keys())
                for output_tensor in output_tensors:
                    if output_tensor not in output:
                        output[output_tensor] = []
                    output[output_tensor].append(row[output_tensor])
            for output_tensor in output_tensors:
                output[output_tensor] = np.asarray(output[output_tensor])
        else:
            output[output_tensors[0]] = np.asarray(result_dict[keyname])
    else:
        logger.debug("Missing required response in {}".format(result_dict))
    return output