diff --git a/torch_xla/csrc/aten_xla_type.cpp b/torch_xla/csrc/aten_xla_type.cpp
index 5d378d9fa1ef..fcb4285c76af 100644
--- a/torch_xla/csrc/aten_xla_type.cpp
+++ b/torch_xla/csrc/aten_xla_type.cpp
@@ -53,6 +53,8 @@ namespace {
 at::Tensor to_meta(const at::Tensor& tensor) {
   // undefined tensors can't be converted to the meta device, since they don't
   // have sizes/strides
+  std::cout << "WONJOO: at aten_xla_type.cpp, to_meta1" << std::endl;
+  std::cout << "WONJOO: at aten_xla_type.cpp, to_meta2, tensor_is_functional=" << at::functionalization::impl::isFunctionalTensor(tensor) << std::endl;
   if (!tensor.defined()) return tensor;
   auto out = at::native::empty_strided_meta_symint(
       tensor.sym_sizes(), tensor.sym_strides(),
@@ -458,6 +460,7 @@ at::Tensor& XLANativeFunctions::_amp_update_scale_(at::Tensor& current_scale,
 at::Tensor XLANativeFunctions::_copy_from(const at::Tensor& self,
                                           const at::Tensor& dst,
                                           bool non_blocking) {
+  std::cout << "WONJOO: at aten_xla_type.cpp, _copy_from" << std::endl;
   TORCH_LAZY_FN_COUNTER("xla::");
   auto dst_tensor = bridge::TryGetXlaTensor(dst);
   auto self_tensor = bridge::TryGetXlaTensor(self);
@@ -652,6 +655,7 @@ at::Tensor XLANativeFunctions::argmin(const at::Tensor& self,
 at::Tensor XLANativeFunctions::as_strided_copy(
     const at::Tensor& self, at::IntArrayRef size, at::IntArrayRef stride,
     c10::optional<int64_t> storage_offset) {
+  std::cout << "WONJOO: at aten_xla_type.cpp, as_strided_copy1" << std::endl;
   TORCH_LAZY_FN_COUNTER("xla::");
   XLATensorPtr self_tensor = bridge::GetXlaTensor(self);
   auto xsize = XlaHelpers::I64List(size);
@@ -671,6 +675,7 @@ at::Tensor XLANativeFunctions::as_strided_scatter(
     const at::Tensor& base, const at::Tensor& mutated_view,
     at::IntArrayRef size, at::IntArrayRef stride,
     c10::optional<int64_t> storage_offset) {
+  std::cout << "WONJOO: at aten_xla_type.cpp, as_strided_scatter1" << std::endl;
   TORCH_LAZY_FN_COUNTER("xla::");
   auto base_ = bridge::GetXlaTensor(base);
   auto xsize = XlaHelpers::I64List(size);
@@ -1148,6 +1153,7 @@ at::Tensor XLANativeFunctions::empty_symint(
     c10::optional<at::Layout> layout, c10::optional<at::Device> device,
     c10::optional<bool> pin_memory,
     c10::optional<at::MemoryFormat> /* memory_format */) {
+  std::cout << "WONJOO: at XLANativeFunctions::empty_symint" << std::endl;
   TORCH_LAZY_FN_COUNTER("xla::");
   auto size = c10::asIntArrayRefSlow(sym_size);
   // PT empty*() are optimizations to avoid initializing the data when it is
@@ -1381,6 +1387,8 @@ at::Tensor& XLANativeFunctions::index_fill_(at::Tensor& self, int64_t dim,
 at::Tensor& XLANativeFunctions::index_put_(
     at::Tensor& self, const c10::List<c10::optional<at::Tensor>>& indices,
     const at::Tensor& values, bool accumulate) {
+  std::cout << "WONJOO: at aten_xla_type.cpp, input_put_1" << std::endl;
+  std::cout << "WONJOO: at aten_xla_type.cpp, input_put_2, self.is_functional=" << at::functionalization::impl::isFunctionalTensor(self) << std::endl;
   TORCH_LAZY_FN_COUNTER("xla::");
   XLA_CHECK(self.scalar_type() == values.scalar_type());
   CanonicalIndexInfo canonical_index_info =
@@ -1399,6 +1407,7 @@ at::Tensor& XLANativeFunctions::index_put_(
       canonical_index_info.start_dim,
       bridge::GetOrCreateXlaTensor(values, *device), accumulate,
       canonical_index_info.result_permutation);
+std::cout << "WONJOO: at aten_xla_type.cpp, input_put_3, self.is_functional=" << at::functionalization::impl::isFunctionalTensor(self) << std::endl;
   return self;
 }
 
@@ -1468,17 +1477,18 @@ at::Tensor XLANativeFunctions::lerp(const at::Tensor& self,
       bridge::GetXlaTensor(self), bridge::GetXlaTensor(end), weight));
 }
 
-at::Tensor XLANativeFunctions::lift_fresh(const at::Tensor& self) {
-  std::cout << "WONJOO: at aten_xla_type.cpp, lift_fresh" << std::endl;
-  return at::functionalization::impl::to_functional_tensor(self);
-  // return at::functionalization::functionalize_aten_op<ATEN_OP(
-  //     lift_fresh)>::call(self);
+at::Tensor XLANativeFunctions::lift(const at::Tensor& tensor) {
+  std::cout << "WONJOO: at XLANativeFunctions::lift" << std::endl;
+  TORCH_INTERNAL_ASSERT(
+      !at::functionalization::impl::isFunctionalTensor(tensor));
+  return at::functionalization::impl::to_functional_tensor(tensor);
 }
 
-at::Tensor XLANativeFunctions::lift_fresh_copy(const at::Tensor& self) {
-  std::cout << "WONJOO: at aten_xla_type.cpp, lift_fresh_copy" << std::endl;
-  return at::functionalization::functionalize_aten_op<ATEN_OP(
-      lift_fresh_copy)>::call(self);
+at::Tensor XLANativeFunctions::lift_fresh(const at::Tensor& tensor) {
+  std::cout << "WONJOO: at XLANativeFunctions::lift_fresh" << std::endl;
+  TORCH_INTERNAL_ASSERT(
+      !at::functionalization::impl::isFunctionalTensor(tensor));
+  return at::functionalization::impl::to_functional_tensor(tensor);
 }
 
 at::Tensor XLANativeFunctions::linspace(const at::Scalar& start,
@@ -3114,6 +3124,7 @@ at::Tensor XLANativeFunctions::block_diag(at::TensorList tensors) {
   return at::functionalization::functionalize_aten_op<ATEN_OP(
       block_diag)>::call(tensors);
 }
+
 at::Tensor XLANativeFunctions::new_empty_strided_symint(
     const at::Tensor& self, at::SymIntArrayRef size, at::SymIntArrayRef stride,
     c10::optional<at::ScalarType> dtype, c10::optional<at::Layout> layout,
diff --git a/xla_native_functions.yaml b/xla_native_functions.yaml
index 9bb0d70e2d9f..d93cba4eb9c9 100644
--- a/xla_native_functions.yaml
+++ b/xla_native_functions.yaml
@@ -197,8 +197,8 @@ supported:
   - leaky_relu_backward
   - lerp.Scalar
   - lerp.Tensor
+  - lift
   - lift_fresh
-  - lift_fresh_copy
   - linspace
   - log
   - log1p