// 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() {

    // 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() {

    // 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() {

  }

  %0 = "tf.ReadVariableOp"(%arg1) : (tensor<*x!tf_type.resource<tensor<128x1024xf32>>>) -> tensor<128x1024xf32>
  %1:1 = "tf_device.cluster_func"(%arg0, %0) {func = @func_with_sharding_inside_while_body, step_marker_location = "STEP_MARK_AT_TOP_LEVEL_WHILE_LOOP", num_cores_per_replica = 2 : i64, use_spmd_for_xla_partitioning = true, use_tpu = true} : (tensor<i32>, tensor<128x1024xf32>) -> (tensor<128x1024xf32>)
  // CHECK: input_sharding_configuration