# CHECK-SAME:   %arg0: tensor<1xf32> {tf._user_specified_name = "d", tf_saved_model.index_path = [0, "a"]},
  # CHECK-SAME:   %arg1: tensor<2xf32> {tf._user_specified_name = "d", tf_saved_model.index_path = [0, "b"]},
  # CHECK-SAME:   %arg2: tensor<3xf32> {tf._user_specified_name = "d", tf_saved_model.index_path = [0, "c"]},
  # CHECK-SAME:   %arg3: tensor<4xf32> {tf._user_specified_name = "d", tf_saved_model.index_path = [0, "x"]},

// CHECK-LABEL: module
module attributes {tf_saved_model.semantics} {
  "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<10xf32>, value = dense<[0.,1.,2.,3.,4.,5.,6.,7.,8.,9.]> : tensor<10xf32> } : () -> ()
  // CHECK-LABEL: @read_from_global
  func.func @read_from_global(%arg0: tensor<!tf_type.resource<tensor<10xf32>>> {tf_saved_model.bound_input = @v})
  attributes {tf_saved_model.exported_names = ["read_from_global"]} {

  func.func @f(%arg0: tensor<?xf32> {tf_saved_model.index_path = [0]}, %v: tensor<!tf_type.resource<tensor<?xf32>>> {tf_saved_model.bound_input = @v}, %v1: tensor<!tf_type.resource<tensor<?xf32>>> {tf_saved_model.bound_input = @v1}) -> (tensor<?xf32> {tf_saved_model.index_path = [0]}) attributes {tf_saved_model.exported_names = ["f"]} {
    %pred = arith.constant false

  // CHECK: "tf_saved_model.global_tensor"() <{
  // CHECK-NOT: is_mutable
  "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v2", 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-SAME: tf_saved_model.exported_names = ["serving_default"]
module attributes {tf.versions = {bad_consumers = [], min_consumer = 12 : i32, producer = 554 : i32}, tf_saved_model.semantics} {

  "tf_saved_model.global_tensor"() {is_mutable, sym_name = "y", type = tensor<3x1xi32>, value = dense<[[1], [2], [3]]> : tensor<3x1xi32>} : () -> ()
  "tf_saved_model.asset"() {sym_name = "z", filename = "file"} : () -> ()
  func.func @serving_default(
      %arg0: tensor<1x3xi32> {tf_saved_model.index_path = ["x"]},

  }
}

// -----

// Tests that no call_once op is added.

module attributes {tf_saved_model.semantics} {
  func.func @no_call_once(%arg0: tensor<i64> {tf_saved_model.index_path = ["x"]}) -> (tensor<i64> {tf_saved_model.index_path = ["r"]})
  attributes {tf.entry_function = {control_outputs = "", inputs = "input:0", outputs = "output:0"}, tf_saved_model.exported_names = ["serving_default"]} {
    func.return %arg0 : tensor<i64>

  // CHECK: return
  func.func @f(%a: i32         {tf_saved_model.index_path = [0]},
               %b: f32         {tf_saved_model.index_path = [0]},
               %c: tensor<i32> {tf_saved_model.index_path = [0]})
               ->( tensor<i8>  {tf_saved_model.index_path = [0]},
                   tensor<i16> {tf_saved_model.index_path = [0]})
                    attributes {tf_saved_model.exported_names = ["a", "b", "c"]} {

// -----

// Tests the case when there's a tf_saved_model.session_initializer and an empty init function.
module attributes {tf_saved_model.semantics} {

  "tf_saved_model.session_initializer"() {initializers = [@init]} : () -> ()
// CHECK: "tf_saved_model.session_initializer"()
// CHECK-SAME: initializers = [@init]

  constexpr absl::string_view kModuleCode = R"mlir(
    module attributes {tf_saved_model.semantics} {
      "tf_saved_model.session_initializer"() {initializers = [@init_func_restore_op]} : () -> ()

      func.func @init_func_restore_op() -> () attributes {tf_saved_model.exported_names = ["restore"], tf_saved_model.initializer_type = "restore_op"} {