code: def test_defun():
      x = tf.constant([[1.0], [1.0], [1.0]])
      y = tf.constant([[2.0], [2.0], [2.0]])
  
      # Verify that the function defined using function.Defun
      # has a corresponding tf.LegacyCall op.
      # CHECK:      func {{@[a-zA-Z_0-9]+}}(
      # CHECK-SAME: [[ARG0:%.*]]: tensor<3x1xf32> {tf_saved_model.index_path = ["y"]},
      # CHECK-SAME: [[ARG1:%.*]]: tensor<3x1xf32> {tf_saved_model.index_path = ["x"]}
      #
      # CHECK-NEXT: [[R0:%.*]] = "tf.LegacyCall"([[ARG1]], [[ARG0]])
      z = plus(x, y)
  
      tensor_info_x = tf.compat.v1.saved_model.utils.build_tensor_info(
          x
      )
      tensor_info_y = tf.compat.v1.saved_model.utils.build_tensor_info(
          y
      )
      tensor_info_z = tf.compat.v1.saved_model.utils.build_tensor_info(
          z
      )
  
      return (
          {
              "key": (
                  tf.compat.v1.saved_model.signature_def_utils.build_signature_def(
                      inputs={"x": tensor_info_x, "y": tensor_info_y},
                      outputs={"z": tensor_info_z},
                      method_name="test_function",
                  )
              )
          },
          None,
          None,
      )
  
imports: import tensorflow.compat.v1
  from tensorflow.compiler.mlir.tensorflow.tests.tf_saved_model import common_v1
  from tensorflow.python.framework import function
label_desc: Use image node_id 2 for calling a global function with example usage: test_defun() and returns: dict,  None,  None