func.return
}

// CHECK: [[CLUSTER:%.*]] = "tf_device.cluster"() ({
// CHECK:    [[OPA:%.*]] = "tf.opA"() {is_stateless = true} : () -> tensor<i32>
// CHECK:    "tf.opB"() ({
// CHECK:      "tf.opC"([[OPA]])
// CHECK:    tf_device.return [[OPA]]
// CHECK:    "tf.opD"([[CLUSTER]])

// Preceding user is using resource updated by a nested op.

func.func @simple_independent_chains(%arg0: !tf_res, %arg1: !tf_res, %arg2: tensor<f32>) {
  // CHECK: tf_executor.graph {
  tf_executor.graph {
    // CHECK: %[[A_CONTROL:.*]] = tf_executor.island wraps "tf.OpA"() : () -> ()
    %control_A = tf_executor.island wraps "tf.OpA"() : () -> ()
    // CHECK: %[[CHAIN_CONSTANT:.*]], %{{.*}} = tf_executor.island wraps "tf.Const"() <{value = dense<1> : tensor<i32>}> : () -> tensor<i32>

 during TPURewritePass.

 For example, the tf.OpA with the `mini_batch_splits` attribute will be
 moved after _TPUCompileMlir and the first input will use the
 _TPUCompileMlir program output:

 ```mlir
 "tf_device.launch"() ({
  %cst_0 = "tf.Const"() {value = dense<""> : tensor<1x!tf_type.string>} : () -> tensor<1x!tf_type.string>
  "tf.OpA"(%cst_0) { mini_batch_splits = ""} : (tensor<1x!tf_type.string>) -> ()

	}

	if authZPluginCfg.URL == nil {
		opaCfg, err := opa.LookupConfig(s[config.PolicyOPASubSys][config.Default],
			NewHTTPTransport(), xhttp.DrainBody)
		if err != nil {
			iamLogIf(ctx, fmt.Errorf("Unable to initialize AuthZPlugin from legacy OPA config: %w", err))
		} else {
			authZPluginCfg.URL = opaCfg.URL
			authZPluginCfg.AuthToken = opaCfg.AuthToken

  %0 = "tf.VarHandleOp"() {container = "c", shared_name = "v"} : () -> tensor<*x!tf_type.resource<tensor<2x8xi32>>>
  %1 = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
  "tf_device.cluster"() ({
    "tf.OpA"(%0, %1) {f = @reachable_function} : (tensor<*x!tf_type.resource<tensor<2x8xi32>>>, tensor<i32>) -> ()
    tf_device.return
  }) : () -> ()
  func.return
}

// CHECK-LABEL: func @reachable_function