code: def save(multiplex_op, path):
      """Save a model that contains the given `multiplex_op`.
  
      Args:
        multiplex_op: A multiplex Custom Op, e.g. multiplex_4_op.multiplex. This is
          parameterized so it can also be used to create an "old" model with an
          older version of the op, e.g. multiplex_2_op.multiplex.
        path: Directory to save model to.
      """
      example_cond, example_a, example_b = _get_example_tensors()
  
      class UseMultiplex(tf.Module):
          @tf.function(
              input_signature=[
                  tf.TensorSpec.from_tensor(example_cond),
                  tf.TensorSpec.from_tensor(example_a),
                  tf.TensorSpec.from_tensor(example_b),
              ]
          )
          def use_multiplex(self, cond, a, b):
              return multiplex_op(cond, a, b)
  
      model = UseMultiplex()
      tf.saved_model.save(
          model,
          path,
          signatures=model.use_multiplex.get_concrete_function(
              tf.TensorSpec.from_tensor(example_cond),
              tf.TensorSpec.from_tensor(example_a),
              tf.TensorSpec.from_tensor(example_b),
          ),
      )
  
imports: import tensorflow
label_desc: Use image node_id 2 for calling a global function with example usage: save(multiplex_op, path) and returns: multiplex_op