code: def test_prune_unconnected_ops(self):
      with ops.Graph().as_default():
          a = array_ops.placeholder(dtype=dtypes.float32, name="a")
          b = array_ops.placeholder(dtype=dtypes.float32, name="b")
          constant_op.constant(1.0, name="constant")
          x = variable_scope.get_variable(
              name="x",
              dtype=dtypes.float32,
              shape=[],
              use_resource=True,
              initializer=init_ops.constant_initializer(2.0),
          )
          y = variable_scope.get_variable(
              name="y",
              dtype=dtypes.float32,
              shape=[],
              use_resource=True,
              initializer=init_ops.constant_initializer(3.0),
          )
          math_ops.add(a, b)
          math_ops.add(x, y)
          graph_def = ops.get_default_graph().as_graph_def()
  
          for node in graph_def.node:
              # Attach a TPU_REPLICATE_ATTR to each node.
              node.attr[tpu_replication._TPU_REPLICATE_ATTR].s = b"0"
              # Rewire placeholder "a" and variable "y" leaving them unconnected.
              for input_index, node_input in enumerate(node.input):
                  if node_input == "b":
                      node.input[input_index] = "constant"
                  if node_input == "y":
                      node.input[input_index] = "x"
  
      with ops.Graph().as_default() as graph:
          # Reimport the graph and prune unconnected ops.
          importer.import_graph_def(graph_def)
          tpu.prune_unconnected_ops_from_xla(ops.get_default_graph())
  
          # Verify that ops "a" and "x" still have TPU_REPLICATE_ATTR.
          a = graph.get_operation_by_name("import/a").get_attr(
              tpu_replication._TPU_REPLICATE_ATTR
          )
          self.assertEqual(b"0", a)
          x = graph.get_operation_by_name("import/x").get_attr(
              tpu_replication._TPU_REPLICATE_ATTR
          )
          self.assertEqual(b"0", x)
          # Verify that ops "b" and "y" have TPU_REPLICATE_ATTR removed.
          with self.assertRaisesRegex(
              ValueError,
              "Operation 'import/b' has no attr named '_tpu_replicate'",
          ):
              graph.get_operation_by_name("import/b").get_attr(
                  tpu_replication._TPU_REPLICATE_ATTR
              )
          with self.assertRaisesRegex(
              ValueError,
              "Operation 'import/y' has no attr named '_tpu_replicate'",
          ):
              graph.get_operation_by_name("import/y").get_attr(
                  tpu_replication._TPU_REPLICATE_ATTR
              )
  
imports: from tensorflow.python.eager import def_function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import importer
  from tensorflow.python.framework import ops
  from tensorflow.python.layers import convolutional
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import control_flow_util
  from tensorflow.python.ops import init_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import special_math_ops
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.platform import test
  from tensorflow.python.tpu import tpu
  from tensorflow.python.tpu import tpu_feed
  from tensorflow.python.tpu import tpu_replication
  from tensorflow.python.tpu import training_loop
  from tensorflow.python.tpu.ops import tpu_ops
label_desc: Use image node_id 1 for calling the TPUGraphPruneTest obj's underlying member method code with example usage: obj.test_prune_unconnected_ops() without return types