// CHECK-LABEL: @if
func.func @if() {
  // CHECK-NOT: Optional
  %0 = builtin.unrealized_conversion_cast to tensor<5xi1>
  %1 = "tf.OptionalNone"() : () -> tensor<!tf_type.variant<tensor<f32>>>
  %2 = "tf.If"(%0, %1) <{else_branch = @false, is_stateless = false, then_branch = @true}>
      : (tensor<5xi1>, tensor<!tf_type.variant<tensor<f32>>>) -> (tensor<!tf_type.variant<tensor<f32>>>)
  return
}

// CHECK-NEXT: "tf.Asin"
// CHECK-NEXT: "tf.If"({{.+}}) <{else_branch = @tf.IfRegion_else, {{.+}} then_branch = @tf.IfRegion_then}

// CHECK: func private @tf.IfRegion_else
// CHECK-NEXT: "tf.Neg"
// CHECK: func private @tf.IfRegion_then
// CHECK-NEXT: "tf.Abs"

func.func @testNested(%arg0: tensor<i1>, %arg1: tensor<*xf32>) -> tensor<*xf32> {
  // CHECK: "tf.If"({{.+}}) <{else_branch = @tf.IfRegion1_else, {{.+}} then_branch = @tf.IfRegion1_then}

  dataset_if->setAttr("_lower_using_switch_merge", builder.getBoolAttr(true));
  // Empty else branch, if there is no more data, do nothing.
  auto& else_branch = dataset_if.getElseBranch();
  else_branch.push_back(new Block);
  builder.setInsertionPointToEnd(&else_branch.front());
  // Return only the state variables from the body arguments.
  SmallVector<Value, 4> else_returns;
  for (int i = 1; i < state_size + 1; i++) {

    bool* has_outside_compilation) {
  // Instantiate "then_branch" and "else_branch".
  NameAttrList then_branch, else_branch;
  TF_RETURN_IF_ERROR(GetNodeAttr(n->attrs(), "then_branch", &then_branch));
  TF_RETURN_IF_ERROR(GetNodeAttr(n->attrs(), "else_branch", &else_branch));

  // Extract outside compilation for then_branch and else_branch.
  bool then_branch_has_outside_compilation = false;

    %4 = "tf.If"(%3, %3, %arg0, %cst) {_tpu_replicate = "cluster", _xla_outside_compilation = "0", device = "", else_branch = @if_else_branch, is_stateless = false, then_branch = @if_then_branch} : (tensor<*xi1>, tensor<*xi1>, tensor<*xi64>, tensor<i64>) -> tensor<*xi1>
    func.return %4 : tensor<*xi1>
  }

  %16 = "tf.Const"() {value = dense<1> : tensor<1xi32>} : () -> tensor<1xi32>

// CHECK: return [[z]]
func.func @while_cond_if(%cond: tensor<i1>, %x: tensor<i1>, %y: tensor<i1>, %z: tensor<i32>) -> (tensor<i1>) {
  %r = "tf.If"(%cond, %x, %y, %z) {then_branch = @then, else_branch = @else, is_stateless = true} : (tensor<i1>, tensor<i1>, tensor<i1>, tensor<i32>) -> tensor<i1>
  return %r : tensor<i1>
}

// CHECK-LABEL: func @while_body_if

      if (type_from_body.has_value()) return type_from_body;
    } else if (auto if_op = llvm::dyn_cast<TF::IfOp>(use.getOwner())) {
      auto then_branch = if_op.then_function();
      auto else_branch = if_op.else_function();
      assert(then_branch && else_branch);
      auto type_from_then = GetElementTypeFromAccess(
          then_branch.getArgument(use.getOperandNumber() - 1), module,
          infer_from_op);

    tensors, whose types are the same as what else_branch returns.
else_branch: A function that takes 'inputs' and returns a list of
    tensors.  whose types are the same as what then_branch returns.
  }];

  let arguments = (ins
    TF_Tensor:$cond,
    Variadic<TF_Tensor>:$input,

    FlatSymbolRefAttr:$then_branch,
    FlatSymbolRefAttr:$else_branch,

  // CHECK: [[cond_res:%.*]]:2 = tfrt.cond [[cond]]
  // CHECK-SAME: @cond_true @cond_false(%arg0, %arg2) : (!tfrt.chain, !tfrt_fallback.tf_tensor)
  %2 = "tf.If"(%arg0, %arg1) {else_branch = @cond_false, then_branch = @cond_true, is_stateless = true} : (tensor<i1>, tensor<i32>) -> tensor<i32>
  // CHECK: [[out_ch:%.*]] = tfrt.merge.chains [[cond_res]]#0, %arg0 : !tfrt.chain, !tfrt.chain