diff --git a/src/ATen/native/xpu/PinnedMemoryAllocator.cpp b/src/ATen/native/xpu/PinnedMemoryAllocator.cpp
deleted file mode 100644
index 8d04d93e1..000000000
--- a/src/ATen/native/xpu/PinnedMemoryAllocator.cpp
+++ /dev/null
@@ -1,39 +0,0 @@
-#include <ATen/ATen.h>
-#include <ATen/CPUFunctions.h>
-#include <ATen/xpu/PinnedMemoryAllocator.h>
-#include <ATen/xpu/XPUNativeFunctions.h>
-
-namespace at {
-
-// Note: The user must call is_pinned(device='xpu') to explicitly call here.
-bool XPUNativeFunctions::is_pinned(
-    const Tensor& self,
-    c10::optional<Device> device) {
-  TORCH_INTERNAL_ASSERT_DEBUG_ONLY(
-      !device.has_value() || device->type() == c10::DeviceType::XPU);
-
-  return at::detail::getXPUHooks().isPinnedPtr(self.storage().data());
-}
-
-// Note: The user must call tensor.pin_memory(device='xpu') to explicitly call
-// here.
-Tensor XPUNativeFunctions::_pin_memory(
-    const Tensor& self,
-    c10::optional<Device> device) {
-  TORCH_INTERNAL_ASSERT_DEBUG_ONLY(
-      !device.has_value() || device->type() == c10::DeviceType::XPU);
-
-  auto* allocator = at::xpu::getPinnedMemoryAllocator();
-  auto storage = c10::Storage(
-      c10::Storage::use_byte_size_t(),
-      at::detail::computeStorageNbytes(
-          self.sizes(), self.strides(), self.dtype().itemsize()),
-      allocator,
-      /*resizable=*/false);
-  auto tensor = at::cpu::empty({0}, self.options())
-                    .set_(storage, 0, self.sizes(), self.strides());
-  tensor.copy_(self);
-  return tensor;
-}
-
-} // namespace at
diff --git a/test/xpu/test_torch_xpu.py b/test/xpu/test_torch_xpu.py
index afb4b28a8..b82a8ec67 100644
--- a/test/xpu/test_torch_xpu.py
+++ b/test/xpu/test_torch_xpu.py
@@ -8572,31 +8572,17 @@ def test_new(self) -> None:
         # TypeError would be better
         self.assertRaises(RuntimeError, lambda: x.new(z.storage()))
 
-    @unittest.skipIf(PYTORCH_CUDA_MEMCHECK, "is_pinned uses failure to detect pointer property")
     def test_pin_memory(self):
         x = torch.randn(3, 5)
         self.assertFalse(x.is_pinned())
-        if not torch.cuda.is_available() or not torch.xpu.is_available():
-            self.assertRaises(RuntimeError, lambda: x.pin_memory())
-        else:
-            if torch.xpu.is_available():
-                device = 'xpu'
-                self.assertFalse(x.is_pinned(device))
-                pinned = x.pin_memory(device)
-                self.assertTrue(pinned.is_pinned(device))
-                self.assertEqual(pinned, x)
-                self.assertNotEqual(pinned.data_ptr(), x.data_ptr())
-                # test that pin_memory on already pinned tensor has no effect
-                self.assertIs(pinned, pinned.pin_memory(device))
-                self.assertEqual(pinned.data_ptr(), pinned.pin_memory(device).data_ptr())
-            else:
-                pinned = x.pin_memory()
-                self.assertTrue(pinned.is_pinned())
-                self.assertEqual(pinned, x)
-                self.assertNotEqual(pinned.data_ptr(), x.data_ptr())
-                # test that pin_memory on already pinned tensor has no effect
-                self.assertIs(pinned, pinned.pin_memory())
-                self.assertEqual(pinned.data_ptr(), pinned.pin_memory().data_ptr())
+        if torch.cuda.is_available() or torch.xpu.is_available():
+            pinned = x.pin_memory()
+            self.assertTrue(pinned.is_pinned())
+            self.assertEqual(pinned, x)
+            self.assertNotEqual(pinned.data_ptr(), x.data_ptr())
+            # test that pin_memory on already pinned tensor has no effect
+            self.assertIs(pinned, pinned.pin_memory())
+            self.assertEqual(pinned.data_ptr(), pinned.pin_memory().data_ptr())
 
 
 
diff --git a/yaml/xpu_functions.yaml b/yaml/xpu_functions.yaml
index 54c5c31ff..cd6f80b84 100644
--- a/yaml/xpu_functions.yaml
+++ b/yaml/xpu_functions.yaml
@@ -539,8 +539,6 @@ supported:
   - sgn.out
   - sgn_
   - _cdist_forward
-  - _pin_memory
-  - is_pinned
   - is_set_to
   - bucketize.Tensor
   - bucketize.Tensor_out