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>

  // expected-remark@below {{Result #1, ID 2 : 1, 2, 3, 5}}
  // expected-remark@below {{Result #2, ID 3 : 0, 1, 2, 3, 5}}
  %if:3 = "tf.If"(%read0, %arg1, %vh0) {
            then_branch = @if_then, else_branch = @if_else, is_stateless = true
          } : (tensor<32xf32>, !tf_res, !tf_res) -> (!tf_res, !tf_res, !tf_res)
  func.return
}

// expected-remark@below {{Region #0, Arg #0, ID 2 : 0, 1, 2}}

^bb0(%arg0: tensor<i1>, %arg1: tensor<*xf32>):
  // expected-error @+1 {{'tf.If' op 'else_branch' result type tensor<3xf32> is incompatible with result type tensor<2xf32> at index 0}}
  %1 = "tf.If"(%arg0, %arg1) {
    then_branch = @testIfThen,
    else_branch = @testIfElse,
    is_stateless = false
  } : (tensor<i1>, tensor<*xf32>) -> tensor<2xf32>

  func.return %1 : tensor<2xf32>

    %1 = "tf.Greater"(%0, %cst_0) {device = ""} : (tensor<f32>, tensor<f32>) -> tensor<i1>