VariableInfo::VariableInfo(
    int index, absl::string_view name, Var* var,
    const std::optional<ManagedStackTrace>& definition_stack_trace)
    : index_(index),
      name_(name),
      var_(var),
      definition_stack_trace_(definition_stack_trace) {}

VariableInfo::VariableInfo(VariableInfo&& other)
    : index_(other.index_),
      var_(other.var_),
      definition_stack_trace_(other.definition_stack_trace_),

    func.return %4 : tensor<100x50xf32>
  }
  // CHECK: "tf.VarHandleOp"
  // CHECK-SAME: shared_name = "var1"
  // CHECK-SAME: _is_initialized = true
  // CHECK: "tf.VarHandleOp"
  // CHECK-SAME: shared_name = "var2"
  // CHECK-SAME: _is_initialized = true
  // CHECK: "tf.VarHandleOp"

  // Create 2 resources and initialize them with dummy values.
  TF_CHECK_OK(device->resource_manager()->Create(
      container, "var1", new tensorflow::Var(tensorflow::DataType::DT_FLOAT)));
  TF_CHECK_OK(device->resource_manager()->Create(
      container, "var2", new tensorflow::Var(tensorflow::DataType::DT_FLOAT)));
}

Status FakeSession::Create(const tensorflow::GraphDef& graph) {

    %var_0 = "tf.VarHandleOp"() {shared_name = "var_0"} : () -> tensor<!tf_type.resource<tensor<2xf32>>>
    "tf.AssignVariableOp"(%var_0, %cst_0) : (tensor<!tf_type.resource<tensor<2xf32>>>, tensor<2xf32>) -> ()
    %cst_1 = "tf.Const"() {value = dense<2.000000e+00> : tensor<3xf32>} : () -> tensor<3xf32>
    %var_1 = "tf.VarHandleOp"() {shared_name = "var_1"} : () -> tensor<!tf_type.resource<tensor<3xf32>>>

    // CHECK: %[[VAR0:.*]] = "tf.VarHandleOp"()
    %0 = "tf.VarHandleOp"() {container = "", shared_name = "var0"} : () -> tensor<!tf_type.resource<tensor<!tf_type.string>>>

    // CHECK: "tf.AssignVariableOp"(%[[VAR0]], %[[ASSET0]])
    "tf.AssignVariableOp"(%0, %arg0) : (tensor<!tf_type.resource<tensor<!tf_type.string>>>, tensor<!tf_type.string>) -> ()

    // CHECK: %[[VAR1:.*]] = "tf.VarHandleOp"()

    %var_0 = "tf.VarHandleOp"() {shared_name = "var_0"} : () -> tensor<!tf_type.resource<tensor<2xf32>>>
    "tf.AssignVariableOp"(%var_0, %cst_0) : (tensor<!tf_type.resource<tensor<2xf32>>>, tensor<2xf32>) -> ()
    %add_0 = "tf.Identity"(%cst_0) : (tensor<2xf32>) -> tensor<2xf32>
    %var_1 = "tf.VarHandleOp"() {shared_name = "var_1"} : () -> tensor<!tf_type.resource<tensor<2xf32>>>

from tensorflow.compiler.mlir.tensorflow.tests.tf_saved_model import common_v1

# CHECK: "tf_saved_model.global_tensor"() <{is_mutable, sym_name = "[[VAR0:[a-zA-Z_0-9]+]]", type = tensor<5x3xf32>, value = {{.*}} : tensor<5x3xf32>}> : () -> ()
# CHECK: "tf_saved_model.global_tensor"() <{is_mutable, sym_name = "[[VAR1:[a-zA-Z_0-9]+]]", type = tensor<3x5xf32>, value = {{.*}} : tensor<3x5xf32>}> : () -> ()
# CHECK:      func {{@[a-zA-Z_0-9]+}}(

    tf_executor.graph {
      %out, %ctl = tf_executor.island wraps "tf.VarHandleOp"() {shared_name = "var_0"} : () -> tensor<!tf_type.resource<tensor<2xf32>>>
      %out_0, %ctl_0 = tf_executor.island wraps "tf.ReadVariableOp"(%out) : (tensor<!tf_type.resource<tensor<2xf32>>>) -> tensor<2xf32>
      %out_1, %ctl_1 = tf_executor.island wraps "tf.Const"() {value = dense<"var_0"> : tensor<1x!tf_type.string>} : () -> tensor<1x!tf_type.string>

module {
// CHECK-LABEL: @serving_default
  func.func @serving_default() -> (tensor<*xi32>) {
    // expected-remark@below {{device: "", container: "", shared_name: "var_0", is_potentially_written: false}}
    %0 = "tf.VarHandleOp"() {shared_name = "var_0"} : () -> tensor<!tf_type.resource<tensor<2xi32>>>
    %1 = "tf.BatchFunction"(%0) {
        f = @called_by_batch_func,
        operandSegmentSizes = array<i32: 1, 0>,

        doSystemUninstall();
        if (shutdownHook != null) {
            try {
                Runtime.getRuntime().removeShutdownHook(shutdownHook);
            } catch (IllegalStateException var3) {
                // ignore
            }
        }
    }

    private static void doSystemUninstall() {
        try {
            AnsiConsole.systemUninstall();
        } finally {