import tensorflow as tf


    if tf_output1_dtype == tf.string:
        cast1 = tf.dtypes.as_string(sub if not swap else add, name="TOSTR1")
    else:
        cast1 = tf.cast(sub if not swap else add, tf_output1_dtype, "CAST1")

    out0 = tf.identity(cast0, "TENSOR_OUTPUT0")
    out1 = tf.identity(cast1, "TENSOR_OUTPUT1")

    # Use a different model name for the non-batching variant
    model_name = tu.get_model_name(
        "savedmodel_nobatch" if max_batch == 0 else "savedmodel", input_dtype,
