cyyever
diff --git a/‎docs/source/torch.rst
Lines changed: 1 addition & 0 deletions b/‎docs/source/torch.rst
Lines changed: 1 addition & 0 deletions
diff --git a/‎test/test_torch.py
Lines changed: 43 additions & 2 deletions b/‎test/test_torch.py
Lines changed: 43 additions & 2 deletions
diff --git a/‎torch/_torch_docs.py
Lines changed: 1 addition & 1 deletion b/‎torch/_torch_docs.py
Lines changed: 1 addition & 1 deletion
@@ -58,6 +58,7 @@ Creation Ops
     as_tensor
     as_strided
     from_numpy
+    from_dlpack
     frombuffer
     zeros
     zeros_like
 
@@ -4604,11 +4604,44 @@ def test_dlpack_conversion_with_streams(self, device, dtype):
         stream.synchronize()
         self.assertEqual(z, x)
 
+    @skipMeta
+    @onlyNativeDeviceTypes
+    @dtypes(*get_all_dtypes(include_bool=False))
+    def test_from_dlpack(self, device, dtype):
+        x = make_tensor((5,), device, dtype)
+        y = torch.from_dlpack(x)
+        self.assertEqual(x, y)
+
+    @skipMeta
+    @onlyNativeDeviceTypes
+    @dtypes(*get_all_dtypes(include_bool=False))
+    def test_from_dlpack_noncontinguous(self, device, dtype):
+        x = make_tensor((25,), device, dtype).reshape(5, 5)
+
+        y1 = x[0]
+        y1_dl = torch.from_dlpack(y1)
+        self.assertEqual(y1, y1_dl)
+
+        y2 = x[:, 0]
+        y2_dl = torch.from_dlpack(y2)
+        self.assertEqual(y2, y2_dl)
+
+        y3 = x[1, :]
+        y3_dl = torch.from_dlpack(y3)
+        self.assertEqual(y3, y3_dl)
+
+        y4 = x[1]
+        y4_dl = torch.from_dlpack(y4)
+        self.assertEqual(y4, y4_dl)
+
+        y5 = x.t()
+        y5_dl = torch.from_dlpack(y5)
+        self.assertEqual(y5, y5_dl)
+
     @skipMeta
     @onlyCUDA
     @dtypes(*get_all_dtypes(include_bool=False))
     def test_dlpack_conversion_with_diff_streams(self, device, dtype):
-        from torch._C import _from_dlpack
         stream_a = torch.cuda.Stream()
         stream_b = torch.cuda.Stream()
         # DLPack protocol helps establish a correct stream order
@@ -4617,11 +4650,19 @@ def test_dlpack_conversion_with_diff_streams(self, device, dtype):
         # in the current stream to make sure that it was correctly populated.
         with torch.cuda.stream(stream_a):
             x = make_tensor((5,), device, dtype) + 1
-            z = _from_dlpack(x.__dlpack__(stream_b.cuda_stream))
+            z = torch.from_dlpack(x.__dlpack__(stream_b.cuda_stream))
             stream_a.synchronize()
         stream_b.synchronize()
         self.assertEqual(z, x)
 
+    @skipMeta
+    @onlyNativeDeviceTypes
+    @dtypes(*get_all_dtypes(include_bool=False))
+    def test_from_dlpack_dtype(self, device, dtype):
+        x = make_tensor((5,), device, dtype)
+        y = torch.from_dlpack(x)
+        assert x.dtype == y.dtype
+
     @skipMeta
     @onlyCUDA
     def test_dlpack_default_stream(self, device):
 
@@ -1041,7 +1041,7 @@ def merge_dicts(*dicts):
     :func:`torch.frombuffer` creates a tensor that always shares memory from objects that
            implement the buffer protocol.
 
-    :func:`torch.utils.dlpack.from_dlpack` creates a tensor that always shares memory from
+    :func:`torch.from_dlpack` creates a tensor that always shares memory from
            DLPack capsules.
 
 Args: