%1 = "tf.UnsupportedOp"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
    %2 = "tf.Identity"(%1) : (tensor<i32>) -> tensor<i32>
    tf_device.return %2 : tensor<i32>
  }) {allow_soft_placement = false, num_cores_per_replica = 1, topology =  "", device_assignment =  []} : () -> tensor<i32>
  func.return %0 : tensor<i32>
}

// -----

// CHECK-LABEL: func @assert_op_string_operand

    %control_4 = tf_executor.island(%control_2) wraps "tf.TPUReplicateMetadata"() {_replication_info = "cluster", _xla_compile_device_type = "TPU", allow_soft_placement = false, computation_shape = [], device = "", device_assignment = [], host_compute_core = [], num_cores_per_replica = 1 : i64, num_replicas = 1 : i64, padding_map = [], step_marker_location = "STEP_MARK_AT_ENTRY", topology = "", use_spmd_for_xla_partitioning...

  // CHECK-NEXT:     "tf.OpA"(%[[REDUCED]]) : (tensor<f32>) -> ()
  tf_device.replicate {n = 4 : i32} {
    "tf_device.cluster"() ({
      "tf.OpA"(%arg0) : (tensor<f32>) -> ()
      tf_device.return

  func.func @inference_Fn_101680(%arg0: tensor<*x!tf_type.string>, %arg1: tensor<*x!tf_type.string>, %arg2: tensor<*xi32>, %arg3: tensor<*xi32>) -> tensor<*xi32> {

    %cst_0 = "tf.Const"() {value = dense<0> : tensor<i32>} : () -> tensor<i32>
    %cst_1 = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>

      %control_2 = tf_executor.island wraps "tf.TPUReplicateMetadata"() {_tpu_replicate = "cluster", allow_soft_placement = false, computation_shape = [], device = "", device_assignment = [], host_compute_core = [], name = "TPUReplicateMetadata", num_cores_per_replica = 1 : i64, num_replicas = 1 : i64, step_marker_location = "STEP_MARK_AT_ENTRY", topology = "",...

    %0 = tf_executor.graph {
      %outputs, %control = tf_executor.island {

      %0 = "tf_device.cluster"() ( {
        %1 = "tf.UnsupportedOp"() : () -> tensor<i32>
        %2 = "tf.Identity"(%1) : (tensor<i32>) -> tensor<i32>
        tf_device.return %2 : tensor<i32>
      }) {allow_soft_placement = true, num_cores_per_replica = 1, topology =  "", device_assignment =  []} : () -> tensor<i32>
      return %0 : tensor<i32>
    }
    ```

// Whether soft placement is allowed. If true, the marked node is eligible for
// outside compilation.
inline constexpr llvm::StringRef kAllowSoftPlacementAttr =
    "allow_soft_placement";

// Marks a node for XLA compilation. The attribute value indicates the
// compilation device type.
inline constexpr llvm::StringRef kCompileDeviceTypeAttr =
    "_xla_compile_device_type";

  module attributes {tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 1610 : i32}} {
    func.func @main(%arg0: tensor<3x3x10xbf16>, %arg1: tensor<3xi32>) -> tensor<1x?x4xbf16> attributes {allow_soft_placement = false, tf.entry_function = {control_outputs = "", inputs = "_arg0,_arg1,_arg2", outputs = "_retval0"}} {
      %cst = "tf.Const"() {value = dense<[1, -1, 4]> : tensor<3xi32>} : () -> tensor<3xi32>