// expected-error @+1 {{'tf.Identity' op is expected to have either both or none of '_replication_info' and '_xla_compile_device_type' attributes}}

  %0 = "tf.some_op"(%arg0) {_xla_compile_device_type = "TPU", _replication_info = "cluster"} : (tensor<i32>) -> tensor<i32>
  func.return %0 : tensor<i32>
}
func.func @while_cond_with_cluster_attr(%arg0: tensor<i32>) -> tensor<i1> {
  %0 = "tf.some_op"(%arg0) {_xla_compile_device_type = "TPU", _replication_info = "cluster"} : (tensor<i32>) -> tensor<i1>
  func.return %0 : tensor<i1>
}

      %outputs:4, %control = tf_executor.island {
       "tf.TPUReplicateMetadata"() {_xla_compile_device_type = "TPU", _replication_info = "cluster", device = "device", num_replicas = 1, topology = "topology"} : () -> ()
        %1 = "tf.opA"(%arg0) {_xla_compile_device_type = "TPU", _replication_info = "cluster"} : (tensor<i1>) -> tensor<i32>

  %1 = "tf.ReadVariableOp"(%arg1) : (!tf_res_f32) -> tensor<f32>
  %2 = "tf.ReadVariableOp"(%arg2) : (!tf_res_f32) -> tensor<f32>
  %device_output:2 = "tf_device.cluster_func"(%0, %1, %2) {_xla_compile_device_type = "TPU", _replication_info = "tpu", func = @device_func_0} : (tensor<i32>, tensor<f32>, tensor<f32>) -> (tensor<f32>, tensor<i32>)
  "tf.AssignVariableOp"(%arg1, %device_output#0) : (!tf_res_f32, tensor<f32>) -> ()

      }) {is_stateless = true, _xla_compile_device_type = "TPU", _replication_info = "x" } : (tensor<i1>) -> (tensor<f32>)
    tf_device.return %3 : tensor<f32>
  // CHECK: {_replication_info = "x", _xla_compile_device_type = "TPU", cluster_attr = "cluster_attr", device = "y"}
  }) {cluster_attr = "cluster_attr", _xla_compile_device_type = "TPU", _replication_info = "x", device = "y"} : () -> tensor<f32>
  // CHECK: "tf.Add"

       "tf.TPUReplicateMetadata"() {_xla_compile_device_type = "TPU", _replication_info = "cluster", device = "device", num_replicas = 1, topology = "topology"} : () -> ()
        %index = "tf.opA"(%arg0) {_xla_compile_device_type = "TPU", _replication_info = "cluster"} : (tensor<i1>) -> tensor<i32>
        %input = "tf.opB"(%arg0) {_xla_compile_device_type = "TPU", _replication_info = "cluster"} : (tensor<i1>) -> tensor<i32>

  // CHECK-NEXT: [[READ:%.*]] = "tf.ReadVariableOp"([[ARG2]])
  // CHECK-NEXT: [[CLUSTER:%.*]]:2 = "tf_device.cluster_func"([[ARG0]], [[ARG1]], [[READ]])
  // CHECK-SAME: _replication_info = "write", _xla_compile_device_type = "TPU"
  %0:2 = "tf_device.cluster_func"(%arg0, %arg1) {_replication_info = "write", _xla_compile_device_type = "TPU", func = @write_func} : (tensor<i32>, tensor<f32>) -> (tensor<f32>, tensor<i32>)

      "tf.TPUReplicateMetadata"() {_xla_compile_device_type = "TPU", _replication_info = "replicate", device = "device", num_replicas = 1, topology = "topology"} : () -> ()
      "tf.SomeTpuOp"() {_xla_compile_device_type = "TPU", _replication_info = "replicate"} : () -> ()
      "tf.SomeOtherTpuOp"() {_xla_compile_device_type = "TPU", _replication_info = "replicate"} : () -> ()
      tf_executor.yield
    }
    tf_executor.fetch

      "tf.TPUReplicateMetadata"() {_xla_compile_device_type = "TPU", _replication_info = "cluster", device = "device", num_replicas = 1 : i64, topology = "topology"} : () -> ()
      %0 = "tf.opA"(%arg0) {_xla_compile_device_type = "TPU", _replication_info = "cluster"} : (tensor<i1>) -> tensor<i32>

  func.func @missing_num_cores_per_replica() {
    // expected-error@+1 {{requires attribute 'num_cores_per_replica'}}