%handle = "tf.HashTableV2"() {container = "", device = "/job:localhost/replica:0/task:0/device:CPU:0", key_dtype = !tf_type.string, shared_name = "hash_table", use_node_name_sharing = false, value_dtype = i64} : () -> tensor<!tf_type.resource>

  // CHECK: tf.LookupTableFindV2
  // CHECK-NOT: tf.Assert
  // CHECK: tf.LookupTableFindV2
  // CHECK: tf.Assert

// CHECK: }, {
// CHECK-EMPTY
// CHECK: } ]
// CHECK: }

func.func @main() -> tensor<*x!tf_type.resource> {
  %0 = "tf.HashTableV2"() {container = "" , shared_name= "table", use_node_name_sharing = false, key_dtype = i32, value_dtype = i32 } : () -> tensor<*x!tf_type.resource>
  func.return %0 : tensor<*x!tf_type.resource>

func.func @set_readonly_stateless(%arg: tensor<i32>, %cond: tensor<i1>) -> tensor<i32> {
  %handle = "tf.HashTableV2"() {container = "", key_dtype = i32, shared_name = "hash_table", use_node_name_sharing = false, value_dtype = i32} : () -> tensor<!tf_type.resource>
  // CHECK: tf.While
  // CHECK-SAME: is_stateless = true

      %out_1, %ctl_2 = tf_executor.island wraps "tf.HashTableV2"() {container = "", device = "", key_dtype = !tf_type.string, shared_name = "1", use_node_name_sharing = false, value_dtype = i64} : () -> tensor<!tf_type.resource>
      %ctl_3 = tf_executor.island wraps "tf.LookupTableImportV2"(%out_1, %out, %out_0) {device = ""} : (tensor<!tf_type.resource>, tensor<1x!tf_type.string>, tensor<1xi64>) -> ()

  // CHECK-DAG: [[r:%.*]] = "tf.LookupTableFindV2"([[v0]]
  // CHECK-DAG: return [[v1]], [[r]]
  %0 = "tf.HashTableV2"() {container = "", device = "", key_dtype = !tf_type.string, shared_name = "x", use_node_name_sharing = false, value_dtype = i64} : () -> tensor<!tf_type.resource>
  %1 = "tf.LookupTableSizeV2"(%0) {device = ""} : (tensor<!tf_type.resource>) -> tensor<i64>

    %outputs, %control = tf_executor.island wraps "tf.HashTableV2"() {container = "", device = "", key_dtype = !tf_type.string, shared_name = "hash_table_ce3dfbfc-7367-4d62-9d48-d13bf8125391", use_node_name_sharing = false, value_dtype = i64} : () -> tensor<!tf_type.resource>
    %outputs_0, %control_1 = tf_executor.island wraps "tf.LookupTableSizeV2"(%outputs) {device = ""} : (tensor<!tf_type.resource>) -> tensor<i64>

      initializer=tf.random_normal_initializer(),
      trainable=True)
  table_initializer = tf.lookup.KeyValueTensorInitializer(
      keys=[1, 2, 3, 4],
      values=[5, 6, 7, 8],
      key_dtype=tf.int32,
      value_dtype=tf.float32)
  table = tf.lookup.StaticHashTable(
      table_initializer, default_value=tf.constant(0.0))

  x = tf.placeholder(tf.int32, shape=(), name='input')
  y = table.lookup(x)
  r = tf.add(y, z)

    %cst_0 = "tf.Const"() {value = dense<1.000000e+00> : tensor<2xf32>} : () -> tensor<2xf32>
    // Note: this is a contrived example and is an invalid input.
    %var_0 = "tf.HashTableV2"() {key_dtype = i64, value_dtype = !tf_type.string} : () -> tensor<!tf_type.resource>
    "tf.AssignVariableOp"(%var_0, %cst_0) : (tensor<!tf_type.resource>, tensor<2xf32>) -> ()
    return
  }
  // CHECK: @init_func_restore_op

    "tf.AssignVariableOp"(%0, %1) : (tensor<*x!tf_type.resource<tensor<!tf_type.string>>>, tensor<!tf_type.string>) -> ()
    %2 = "tf.HashTableV2"() {key_dtype = !tf_type.string, shared_name = "table", value_dtype = i64} : () -> tensor<!tf_type.resource>
    %3 = "tf.ReadVariableOp"(%0) : (tensor<*x!tf_type.resource<tensor<!tf_type.string>>>) -> tensor<!tf_type.string>

          %o, %c = tf_executor.island wraps "tf.HashTableV2"() <{container = "", key_dtype = !tf_type.string, shared_name = "vocab_file.txt", use_node_name_sharing = false, value_dtype = i64}> {device = ""} : () -> tensor<!tf_type.resource>