"some_dialect.some_op"() {
    tf_saved_model.exported_names = ["foo"]
  } : () -> ()

}

// -----

module attributes {tf_saved_model.semantics} {

  // expected-error@+1 {{'tf_saved_model.exported_names' must be an array of strings}}
  func.func @f() attributes { tf_saved_model.exported_names = 1 : i32} {
    func.return

func.func @init1() attributes {tf_saved_model.exported_names = ["init1"]} {
  %0 = "tf.Const"() {value = dense<42> : tensor<1xi64>} : () -> tensor<1xi64>
  return
}
func.func @init2() attributes {tf_saved_model.exported_names = ["init2"]} {
  %0 = "tf.Const"() {value = dense<43> : tensor<1xi64>} : () -> tensor<1xi64>
  return
}
func.func @init3() attributes {tf_saved_model.exported_names = ["init3"]} {

  "tf_saved_model.session_initializer"() {initializers = [@NoOp]} : () -> ()
  func.func @NoOp() attributes {tf_saved_model.exported_names = ["__tf_saved_model_session_initializer_NoOp"]} {
    func.return
  }
// CHECK: func @NoOp() attributes {tf_saved_model.exported_names = ["__tf_saved_model_session_initializer_NoOp"]}

    func.return %1 : tensor<100x50xf32>
  }

  func.func @Init() attributes {tf_saved_model.exported_names = ["Init"], tf_saved_model.initializer_type = "restore_op"} {
    func.return
  }

  // CHECK-LABEL: func @Init
  // CHECK-SAME: tf_saved_model.exported_names = ["Init"]
  // CHECK-SAME: tf_saved_model.initializer_type = "restore_op"
  // CHECK: %[[VAR:.*]] = "tf.VarHandleOp"()

  func.func @main() attributes {tf.entry_function = {inputs = "", outputs = ""}, tf_saved_model.exported_names = ["main"]} {
    tf_executor.graph {
      tf_executor.fetch
    }
    return
  }
// Sanity check: The main function's signature & attributes have not changed.
// CHECK: func.func @main()
// CHECK-SAME: tf_saved_model.exported_names = ["main"]

// CHECK: tf_executor.graph

  "tf_saved_model.global_tensor"() {
    tf_saved_model.exported_names = ["some_const"],
    sym_name = "some_constant",
    type = tensor<1x64xf32>,
    value = dense<42.0> : tensor<1x64xf32>
  } : () -> ()

  // Representation for variables: mutable global tensor.
  // CHECK: tf_saved_model.global_tensor
  "tf_saved_model.global_tensor"() {
    is_mutable,
    tf_saved_model.exported_names = ["some_var", "some.other.name"],

// CHECK-SAME: tf_saved_model.exported_names = ["add"]

// CHECK: func @sub(
// CHECK-SAME: {tf_saved_model.index_path = ["input2"]}
// CHECK-SAME: {tf_saved_model.index_path = ["input1"]}
// CHECK-SAME: {tf_saved_model.index_path = ["result"]}
// CHECK-SAME: tf.entry_function = {inputs = "input2:0,input1:0", outputs = "result:0"}
// CHECK-SAME: tf_saved_model.exported_names = ["sub"]

  SmallVector<StringRef, 2> ret;
  auto exported_names =
      op->getAttrOfType<ArrayAttr>(kTfSavedModelExportedNamesAttr);
  if (exported_names) {
    for (auto name : exported_names) {
      ret.push_back(mlir::cast<StringAttr>(name).getValue());
    }
  }
  return ret;
}

bool IsExported(Operation *op) {
  auto exported_names =
      op->getAttrOfType<ArrayAttr>(kTfSavedModelExportedNamesAttr);

  "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", tf_saved_model.exported_names = ["v"], type = tensor<f32>, value = dense<42.> : tensor<f32> } : () -> ()

  func.func @f(%arg0: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @v}) -> (tensor<f32> {tf_saved_model.index_path = []})
  attributes {tf_saved_model.exported_names = ["f"]} {

  # Check index paths for results.
  #
  # CHECK:      func {{@[a-zA-Z_0-9]+}}() -> (
  # CHECK-SAME:   tensor<1xf32> {tf_saved_model.index_path = []})
  # CHECK-SAME: attributes {{.*}} tf_saved_model.exported_names = ["f0000_single_return"]
  @tf.function(input_signature=[])
  def f0000_single_return(self):
    return tf.constant(1.0, shape=[1])

  # Check index paths for results with multiple return values.