// CHECK: [[HASHTABLE:%.+]] = "tf.HashTableV2"()
    // CHECK: "tf.InitializeTableFromTextFileV2"([[HASHTABLE]], [[CST]])
    // CHECK: [[HASHTABLE_1:%.+]] = "tf.HashTableV2"()
    // CHECK: "tf.InitializeTableFromTextFileV2"([[HASHTABLE_1]], [[CST_1]])
    func.return
  }
}

// -----

module attributes {tf_saved_model.semantics} {

// Test hoisting hash table op.

// CHECK-LABEL: func @_tfrt_resource_init
// CHECK: [[handle:%.*]] = "tf.HashTableV2"()
// CHECK-SAME: shared_name = "x"
// CHECK: "tf._TfrtSetResource"([[handle]]) <{index = [[handle_id:.*]] : i64}> {device = "/job:localhost/replica:0/task:0/device:CPU:0"}
// CHECK: [[x:%.*]] = "tf.LookupTableSizeV2"([[handle]])

    %cst_6 = "tf.Const"() {value = dense<0.00156862743> : tensor<f32>} : () -> tensor<f32>
    %0 = "tf.HashTableV2"() {container = "", device = "", key_dtype = !tf_type.string, shared_name = "hash_table_1", use_node_name_sharing = false, value_dtype = i64} : () -> tensor<!tf_type.resource>

  // CHECK-NEXT:  "tf.HashTableV2"
  // CHECK-NEXT:  "tf.LookupTableRemoveV2"
  func.return
}

// -----

// Test for case with import op.
func.func @hashtable_import(%arg0: tensor<5x!tf_type.string>) {
  %cst = arith.constant dense<["emerson", "lake", "palmer"]> : tensor<3x!tf_type.string>
  %cst_0 = arith.constant dense<[0, 1, 2]> : tensor<3xi64>

    %cst = arith.constant dense<[1, 2, 3, 4]> : tensor<4xi64>
    %cst_0 = arith.constant dense<["a", "b", "c", "d"]> : tensor<4x!tf_type.string>
    %0 = "tf.HashTableV2"() {container = "", device = "", key_dtype = i64, shared_name = "hash_table_dba2ccaa-f1b1-46d6-b276-98008f69da71", use_node_name_sharing = false, value_dtype = !tf_type.string} : () -> tensor<!tf_type.resource>

      %out_0, %ctl_1 = tf_executor.island wraps "tf.Const"() {device = "", value = dense<[1]> : tensor<1xi64>} : () -> tensor<1xi64>
      %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>

# CHECK:      func @[[init]]
# CHECK-SAME: tf_saved_model.initializer_type = "init_op"
# CHECK-NEXT: [[R6:%.*]] = "tf.Const"()
# CHECK-NEXT: [[R5:%.*]] = "tf.Const"() <{value = dense<[1, 2,
# CHECK-NEXT: [[R7:%.*]] = "tf.HashTableV2"()
# CHECK-SAME: shared_name = "[[hash_table:.*]]"
# CHECK-NEXT: "tf.LookupTableImportV2"([[R7]], [[R5]], [[R6]])

# CHECK:      func {{@[a-zA-Z_0-9]+}}(
# CHECK-SAME: [[ARG0:%.*]]: tensor<i32>

    %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
  }

              StrEq("arg_0:0"));
}

TEST_F(ConvertMlirModuleToExportedModelTest,
       InitNodeNameSetToLocOfControlOutput) {
  // Define a module that initializes a tf.HashTableV2 whose control output node
  // for the initialization is named "init_op_init_all_tables".
  mlir::OwningOpRef<mlir::ModuleOp> module_op = ParseModuleOpString(R"mlir(
    module attributes {tf_saved_model.semantics} {

# CHECK-SAME: [[ARG1:%.*]]: tensor<!tf_type.string> {tf_saved_model.bound_input = @[[asset1]]}
# CHECK-SAME: tf_saved_model.initializer_type = "init_op"
# CHECK-NEXT: [[R0:%.*]] = "tf.HashTableV2"()
# CHECK-SAME: shared_name = "[[hash_table:.*]]"
# CHECK-NEXT: "tf.InitializeTableFromTextFileV2"([[R0]], [[ARG0]])


def write_vocabulary_file(vocabulary):
  """Write temporary vocab file for module construction."""