"tf_device.parallel_execute"() ({
// expected-error@-1 {{'tf_device.parallel_execute' op number of output types (3) must match the total number of outputs from all regions (2).}}
    %0 = "tf.opA"() : () -> (tensor<*xi1>)
    %1 = "tf.opB"() : () -> (tensor<*xi32>)
    tf_device.return %0, %1 : tensor<*xi1>, tensor<*xi32>
  },
  {
    %2 = "tf.opC"() : () -> (tensor<*xi1>)
    tf_device.return

	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>) -> ()
    }
    ```

// `tf_device.parallel_execute`.
//
// For example, the following:
//
//  %0 = tf_executor.island {
//    tf_executor.yield
//  }
//  %1:2 = tf_executor.island {
//    %2 = "tf.opA"(%arg0) : (tensor<i1>) -> tensor<i1>
//      tf_executor.yield %2 : tensor<i1>
//  }
//  %3:2 = tf_executor.island(%0) {
//    %4 = "tf_device.parallel_execute"() ({
//      %5 = "tf.opB"() : () -> tensor<i1>

//               devices = {DEVICE_ALIAS_0 = ["/DEVICE:0", "/DEVICE:1"],
//                          DEVICE_ALIAS_1 = ["/DEVICE:2", "/DEVICE:3"]}} {
//     %a = "tf_device.launch"() ({
//       %2 = "tf.opA"(%ri) : (tensor<i1>) -> tensor<i1>
//       tf_device.return %2 : tensor<i1>
//     }) {device = "DEVICE_ALIAS_0"} : () -> tensor<i1>
//     %b = "tf_device.launch"() ({
//       %3 = "tf.opB"(%a) : (tensor<i1>) -> tensor<i1>

  %0 = tf_executor.graph {
    %1:2 = tf_executor.island {
      %3 = "tf.opA"(%arg0) : (tensor<i1>) -> tensor<i1>
      tf_executor.yield %3 : tensor<i1>
    }
    %2:2 = tf_executor.island(%1#1) {
      %4 = "tf.opB"() : () -> tensor<f32>
      tf_executor.yield %4 : tensor<f32>
    }

// CHECK: "tf.opA"
// CHECK: tf_executor.island
// CHECK: "tf.opB"

    tf_executor.fetch %2#0 : tensor<f32>
  }

func.func @island_not_direct_parent_of_user() -> () {
  tf_executor.graph {
    %island1:2 = tf_executor.island {
      // CHECK: %[[VAL_0:.*]], %[[VAL_1:.*]] = tf_executor.island wraps "tf.OpA"() : () -> tensor<i64>
      %0 = "tf.OpA"() : () -> (tensor<i64>)
      // CHECK: %[[VAL_2:.*]] = tf_executor.island(%[[VAL_1]]) wraps "tf.OpB"() : () -> ()
      "tf.OpB"() : () -> ()
      tf_executor.yield %0 : tensor<i64>
    }

}

// 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>>>

replicas and is mapped to a single region argument.

Operands not replicated can be implicitly captured by ops in the region. Results
are replicated each from the regions terminator.

For example:
```
%0 = "tf.opA"() : () -> tensor<i32>
%1 = "tf.opB"() : () -> tensor<i32>
%2 = "tf.opC"() : () -> tensor<f32>
%3 = "tf.opD"() : () -> tensor<f32>
%4 = "tf.opE"() : () -> tensor<!tf_type.resource>

      tf_executor.yield
    }
    // CHECK: tf_executor.fetch
    tf_executor.fetch
  }
  func.return
}

func.func @then_function() {
  tf_executor.graph {
    tf_executor.island {
      "tf.OpA"() : () -> ()
      tf_executor.yield
    }
    tf_executor.fetch
  }
  func.return
}

func.func @else_function() {
  tf_executor.graph {
    tf_executor.island {
      "tf.OpB"() : () -> ()