chore: import upstream snapshot with attribution

tests/python/common/utils/test_pin_memory.py

@@ -0,0 +1,37 @@
+import backend as F
+
+import dgl
+import pytest
+
+
+@pytest.mark.skipif(
+    F._default_context_str == "cpu", reason="Need gpu for this test"
+)
+def test_pin_unpin():
+    t = F.arange(0, 100, dtype=F.int64, ctx=F.cpu())
+
+    assert not F.is_pinned(t)
+
+    if F.backend_name == "pytorch":
+        nd = dgl.utils.pin_memory_inplace(t)
+        assert F.is_pinned(t)
+        nd.unpin_memory_()
+        assert not F.is_pinned(t)
+        del nd
+
+        # tensor will be unpinned immediately if the returned ndarray is not saved
+        dgl.utils.pin_memory_inplace(t)
+        assert not F.is_pinned(t)
+
+        t_pin = t.pin_memory()
+        # cannot unpin a tensor that is pinned outside of DGL
+        with pytest.raises(dgl.DGLError):
+            F.to_dgl_nd(t_pin).unpin_memory_()
+    else:
+        with pytest.raises(dgl.DGLError):
+            # tensorflow and mxnet should throw an error
+            dgl.utils.pin_memory_inplace(t)
+
+
+if __name__ == "__main__":
+    test_pin_unpin()