Status:            workloadapi.WorkloadStatus_HEALTHY,
					ClusterId:         testC,
					Services: map[string]*workloadapi.PortList{
						"ns/a.example.com": {
							Ports: []*workloadapi.Port{{
								ServicePort: 80,
								TargetPort:  80,
							}},
						},
					},
				},
				{
					Uid:               "cluster0/networking.istio.io/ServiceEntry/ns/name/b.example.com",

    "tf_device.cluster_func"() {_xla_compile_device_type = "TPU", _replication_info = "cluster0", func = @empty_func, num_cores_per_replica = 1, step_marker_location = "", topology = "", device_assignment = [], input_sharding_configuration = [], output_sharding_configuration = [], use_spmd_for_xla_partitioning = false} : () -> ()
    func.return
  }
  func.func @empty_func() {
    func.return
  }

}

    %compile_result = "tf.TPUCompilationResult"() {_tpu_compilation_status = "cluster0"} : () -> tensor<!tf_type.string>
    %compile_result2 = "tf.TPUCompilationResult"() {_tpu_compilation_status = "cluster0"} : () -> tensor<!tf_type.string>

    // CHECK-NOT: "tf.TPUCompilationResult"

    // CHECK: return %[[EXECUTE_OUTPUT]], %[[COMPILE_OUTPUT]]#0, %[[COMPILE_OUTPUT]]#0

  func.func @missing_num_cores_per_replica() {
    // expected-error@+1 {{requires attribute 'num_cores_per_replica'}}
    "tf_device.cluster_func"() {_xla_compile_device_type = "TPU", _replication_info = "cluster0", func = @empty_func, step_marker_location = "STEP_MARK_AT_TOP_LEVEL_WHILE_LOOP", topology = "", device_assignment = [], input_sharding_configuration = [], output_sharding_configuration = [], use_spmd_for_xla_partitioning = false} : () -> ()

    func.return
  }
  func.func @empty_func() {
    func.return
  }

  func.func @main() {
    "tf_device.cluster_func"() {_xla_compile_device_type = "TPU", _replication_info = "cluster0", func = @empty_func, num_cores_per_replica = 1, step_marker_location = "", topology = "", device_assignment = [], input_sharding_configuration = [], output_sharding_configuration = [], use_spmd_for_xla_partitioning = false} : () -> ()

    For example, a non replicated `tf_device.cluster_func`:

    ```mlir
    func @tf_tpu_rewrite(%arg0: tensor<i8>) {
      %0 = "tf_device.cluster_func"(%arg0) {_xla_compile_device_type = "TPU", _replication_info = "cluster0", func = @func} : (tensor<i8>) -> tensor<i8>
      return
    }
    ```

    will be rewritten as:

    ```mlir
    func @tf_tpu_rewrite(%arg0: tensor<i8>) {
      %0:2 = "tf_device.launch"() ( {

		Kind:        "Config",
		APIVersion:  "v1",
		Preferences: api.Preferences{},
		Clusters: map[string]*api.Cluster{
			clusterName: newCluster(&c.restConfig),
		},
		AuthInfos: map[string]*api.AuthInfo{
			authInfoName: newAuthInfo(&c.restConfig),
		},
		Contexts: map[string]*api.Context{
			contextName: {
				Cluster:  clusterName,
				AuthInfo: authInfoName,
			},
		},
		CurrentContext: contextName,
	}

     // CHECK-NEXT: "tf.A"
     // CHECK-NEXT: "tf.E"
     // CHECK: device_assignment =  [], num_cores_per_replica = 1 : i64, topology =  ""
    "tf_device.cluster"() ({
      "tf.A"() : () -> ()
      "tf.B"() {_xla_outside_compilation = "cluster1"} : () -> ()
      "tf.C"() {_xla_outside_compilation = "cluster1"} : () -> ()
      "tf.D"() {_xla_outside_compilation = "cluster1"} : () -> ()
      "tf.E"() : () -> ()

  auto clusters = GetClusters(*graph);
  EXPECT_EQ(4, clusters.size());
  EXPECT_EQ(clusters["B"], clusters["C"]);
  EXPECT_EQ(clusters["E"], clusters["F"]);
  EXPECT_NE(clusters["B"], clusters["E"]);
  EXPECT_TRUE(clusters.find("A") == clusters.cend());
  EXPECT_TRUE(clusters.find("D") == clusters.cend());
}

TEST(XlaCompilationTest, UncompilableCycles) {