%1 = "tf.TPUCompilationResult"() {_tpu_compilation_status = "cluster", device = ""} : () -> tensor<!tf_type.string>

    "tf.AssignVariableOp"(%arg6,...

    %0 = "tf_device.cluster_func"(%arg0) {_xla_compile_device_type = "TPU", _replication_info = "cluster0", func = @empty_func, num_cores_per_replica = 1, step_marker_location = "STEP_MARK_AT_ENTRY", topology = "", device_assignment = [], output_sharding_configuration = [], use_spmd_for_xla_partitioning = false} : (tensor<?xi32>) -> tensor<?xi32>
    func.return
  }

  %1 = "tf.ReadVariableOp"(%arg0) {_xla_compile_device_type = "TPU", _replication_info = "cluster_test_fn"} : (tensor<*x!tf_type.resource<tensor<f32>>>)...

  %const = "tf.Const"() {device = "/CPU:0", value = dense<1> : tensor<i32> } : () -> tensor<i32>

      %outputs_19, %control_20 = tf_executor.island(%control_18) wraps "tf.Const"() {_tpu_replicate = "cluster_sample_sequence",...

    ```

    wll be replaced by `_replication_info="cluster"` and  `_xla_compile_device_type="TPU"`.

    ```mlir

```

wll be replaced by `_replication_info="cluster"` and  `_xla_compile_device_type="TPU"`.

```mlir

    return
  }
}

// -----

  }) {_tpu_replicate = "cluster_0", allow_soft_placement = false, computation_shape = [], device_assignment = [], host_compute_core = [], num_cores_per_replica = 1 : i64, padding_map = [], step_marker_location = "STEP_MARK_AT_ENTRY", topology = "", tpu_compile_options_proto = "", use_spmd_for_xla_partitioning = false, use_tpu = true} : () -> (tensor<i32>, tensor<i32>)