%0 = tf_executor.graph {
    %output, %control = tf_executor.island {
      // CHECK: {{%.+}}, [[IF_CONTROL:%.+]] = tf_executor.island wraps "tf.If"
      %1 = "tf.If"(%arg0, %arg1) {device = "", else_branch = @stateful_composite_op_control_else, is_stateless = false, then_branch = @stateful_composite_op_control_then} : (tensor<i1>, tensor<*x!tf_type.resource<tensor<i32>>>) -> tensor<i32>

// CHECK:  [[SHAPE_1:%.*]] = "tf.Shape"([[INPUT]]) : (tensor<3x10xf32>) -> tensor<?xi32>
// CHECK:  [[RESULT:%.*]] = "tf.If"([[DIFF_RES]], [[INPUT]], [[SHAPE_1]], [[SIZE_DIFF]], [[SIZE]]) <{else_branch = @cond_false, is_stateless = true, then_branch = @cond_true}> : (tensor<i1>, tensor<3x10xf32>, tensor<?xi32>, tensor<i32>, tensor<i32>) -> tensor<?x10xf32>
// CHECK:  return [[RESULT]] : tensor<?x10xf32>
}

  // CHECK-NOT: tf.Stack
  %stack = "tf.StackV2"(%max_size) {elem_type = f32, stack_name = "s"} : (tensor<i32>) -> tensor<!tf_type.resource>
  %if_op = "tf.If"(%arg0, %stack) {then_branch = @if_then, else_branch = @if_else, is_stateless = false}
    : (tensor<i1>, tensor<!tf_type.resource>) -> tensor<!tf_type.resource>
  // CHECK: "tf.Slice"
  %pop = "tf.StackPopV2"(%if_op) : (tensor<!tf_type.resource>) -> tensor<f32>

      auto then_branch = if_op.then_function();
      auto else_branch = if_op.else_function();
      // Recursively handle the nested control flow.
      (void)HoistForControlFlow(&then_branch.front(), module, vars_initialized,
                                lifted_partitioned_call_callees);
      (void)HoistForControlFlow(&else_branch.front(), module, vars_initialized,

                                    /*operands=*/ArrayRef<Value>{});

  // Create empty else branch region.
  auto& else_branch = host_side_if.getElseBranch();
  else_branch.push_back(new Block);
  builder.setInsertionPointToEnd(&else_branch.front());
  builder.create<mlir::TF::YieldOp>(if_region.getLoc(),
                                    /*operands=*/ArrayRef<Value>{});
  return host_side_if;
}

      NodeBuilder(kFunctionalIfNodeName, "If", &root.graph()->flib_def())
          .Input(predicate.node())
          .Input(if_inputs)
          .Attr("then_branch", uncompilable_fn1_attr)
          .Attr("else_branch", uncompilable_fn2_attr)
          .Attr("Tout", {DT_INT32})
          .Finalize(root.graph(), &if_node));
  std::unique_ptr<Graph> graph(new Graph(OpRegistry::Global()));
  TF_ASSERT_OK(root.ToGraph(graph.get()));

      %outputs_65,...

  // CHECK:  "tf._TfrtGetResource"()
  %cond = "tf.Const"() {device = "/CPU:0", value = dense<true> : tensor<i1>} : () -> tensor<i1>
  // CHECK: tf.If
  %x = "tf.If"(%cond, %handle) {then_branch = @some_func, else_branch = @some_func, is_stateless = false} : (tensor<i1>, tensor<!tf_type.resource<tensor<i32>>>) -> tensor<i32>
  %r = "tf.AddV2"(%arg, %x) {device = "/CPU:0"} : (tensor<i32>, tensor<i32>) -> tensor<i32>
  func.return %r : tensor<i32>

  %0 = tf_executor.graph {
    %output, %control = tf_executor.island {
      // CHECK: {{%.+}}, [[IF_CONTROL:%.+]] = tf_executor.island wraps "tf.If"
      %1 = "tf.If"(%arg0, %arg1) {device = "", else_branch = @stateful_composite_op_control_else, is_stateless = false, then_branch = @stateful_composite_op_control_then} : (tensor<i1>, tensor<*x!tf_type.resource<tensor<i32>>>) -> tensor<i32>

  %3 = "tf.Less"(%2, %0) : (tensor<f32>, tensor<f32>) -> tensor<i1>
  %4 = "tf.If"(%3, %1, %2) {Tcond = i1, Tin = ["tfdtype$DT_RESOURCE", "tfdtype$DT_FLOAT"], Tout = ["tfdtype$DT_FLOAT"],
       else_branch = @cond_false, is_stateless = false,then_branch = @cond_true} :
       (tensor<i1>, tensor<!tf_type.resource<tensor<f32>>>, tensor<f32>) -> tensor<f32>
  %5 = "tf.Identity"(%4) : (tensor<f32>) -> tensor<f32>