import tensorflow as tf

        return

    tf_input_dtype = np_to_tf_dtype(input_dtype)
    tf_output0_dtype = np_to_tf_dtype(output0_dtype)
    tf_output1_dtype = np_to_tf_dtype(output1_dtype)

    # Create the model. If non-batching then don't include the batch
    # dimension.
    tf.reset_default_graph()
    if max_batch == 0:
        in0 = tf.placeholder(tf_input_dtype, tu.shape_to_tf_shape(input_shape),
                             "TENSOR_INPUT0")
        in1 = tf.placeholder(tf_input_dtype, tu.shape_to_tf_shape(input_shape),
                             "TENSOR_INPUT1")
    else:
        in0 = tf.placeholder(tf_input_dtype, [
