y = constant_op.constant([2], name='y_const')
  math_ops.add(x, y, name='x_y_sum')


def tfadd_with_ckpt(out_dir):
  x = array_ops.placeholder(dtypes.int32, name='x_hold')
  y = variable_v1.VariableV1(constant_op.constant([0]), name='y_saved')
  math_ops.add(x, y, name='x_y_sum')

  init_op = variables.global_variables_initializer()
  saver = saver_lib.Saver(write_version=saver_pb2.SaverDef.V1)

  // CHECK-DAG: ml_program.global public @vars.Variable_1([]) : tensor<!tf_type.string>
  func.func @lowers_string_ops(%arg0: tensor<128xi32>, %arg1: tensor<128xi32>, %arg2: tensor<128x1xi32>, %arg3: tensor<128x90xi32>, %arg4: tensor<128x90xi32>, %arg5: tensor<128x90xi32>, %arg6: tensor<128x90x64xf32>, %arg7: tensor<128x90x64xf32>) -> tensor<!tf_type.string> {
    // CHECK: %[[v0:.*]] = ml_program.global_load @vars.Variable_1 : tensor<!tf_type.string>

  attributes {tf._input_shapes = [#tf_type.shape<1x3>, #tf_type.shape<*>], tf.signature.is_stateful} {
  // CHECK-DAG: [[handle1:%.*]] = "tf.VarHandleOp"() <{{{.*}}, shared_name = "variable1"}>
  // CHECK-DAG: [[handle2:%.*]] = "tf.VarHandleOp"() <{{{.*}}, shared_name = "variable2"}>
  // CHECK: "tf.ReadVariableOp"([[handle1]])
  // CHECK: "tf.ReadVariableOp"([[handle2]])