%out, %c1 = tf_executor.island wraps "tf.opA"(%ri) {_tpu_replicate="cluster"}: (tensor<i32>) -> tensor<i32>
    // expected-warning @+1 {{TF2XLA TPU bridge input check: cluster op = tf.opA with cluster = cluster has successor as non cluster op tf.opB}}
    %out2, %c2 = tf_executor.island wraps "tf.opB"(%out) : (tensor<i32>) -> tensor<i32>

    For example, the following:

    ```mlir
    func @single_op_launch() {
      %a = "tf.opA"() {device = "CPU:0"} : () -> tensor<i1>
      return %a
    }
    ```

    will be transformed into:

    ```mlir
    func @single_op_launch() {
      %1 = tf_device.launch() ( {
        %a = "tf.opA"() : () -> tensor<i1>
        tf_device.return %a
      }) {device = "CPU:0"} : () -> tensor<i1>

  //
  // Two ops with the same groups and different branches are considered
  // parallel so are not made dependent. For example if `OpA` has parallel_ids
  //   `{group0:branch0, group1:branch0}`
  // and `OpB` has parallel_ids
  //   `{group0:branch1, graph1:branch0}`
  // then `OpA` and `OpB` are executed in parallel because `group0` is common
  // with a different branch.
  //

	case config.PolicyOPASubSys:
		// In case legacy OPA config is being set, we treat it as if the
		// AuthZPlugin is being set.
		subSys = config.PolicyPluginSubSys
		fallthrough
	case config.PolicyPluginSubSys:
		if ppargs, err := polplugin.LookupConfig(s, GetDefaultConnSettings(), xhttp.DrainBody); err != nil {
			return err
		} else if ppargs.URL == nil {
			// Check if legacy opa is configured.

      "tf.OpA"(%0) : (tensor<f32>) -> ()
    }
    ```

    will be transformed into:

    ``mlir
    %0 = "tf.ReadVariableOp"(%arg0) : (tensor<*x!tf_type.resource<tensor<f32>>>) -> tensor<f32>
    tf_device.replicate {n = 2 : i32} {
      "tf.OpA"(%0) : (tensor<f32>) -> ()
    }
    ```

}

// CHECK-LABEL: func @variant_input_output_already_marked
func.func @variant_input_output_already_marked() {
  // CHECK: "tf.opA"
  // CHECK-SAME: _xla_outside_compilation = "0"
  // CHECK: "tf.opB"
  // CHECK-SAME: _xla_outside_compilation = "0"
  "tf_device.cluster"() ({
    %1= "tf.opA"() {_xla_outside_compilation = "0"} : () -> tensor<!tf_type.variant<tensor<f32>>>

    enableNamespacesByDefault: false
    # Mutations that occur after the sidecar injector are not handled by default, as the Istio sidecar injector is only run
    # once. For example, an OPA sidecar injected after the Istio sidecar will not have it's liveness/readiness probes rewritten.
    # Setting this to `IfNeeded` will result in the sidecar injector being run again if additional mutations occur.

        // a role as connection between `tf.TPUReplicatedInput` or
        // `tf.TPUPartitionedInput`. For example, we have the follow pseudocode:
        // %0 = tf_executor.island wraps "tf.OpA" (){_replication_info = 'c'}
        // %1 = tf_executor.island wraps "tf.Identity(%0)
        // %2 = tf_executor.island wraps "tf.TPUReplicatedInput"(%1)

        if (!isa<TF::TPUReplicatedInputOp, TF::TPUPartitionedInputOp,

    enableNamespacesByDefault: false

    # Mutations that occur after the sidecar injector are not handled by default, as the Istio sidecar injector is only run
    # once. For example, an OPA sidecar injected after the Istio sidecar will not have it's liveness/readiness probes rewritten.
    # Setting this to `IfNeeded` will result in the sidecar injector being run again if additional mutations occur.