Added to torch_sparse_csc_tensor (#319)

update

Author: rusty1s

torch_sparse/storage.py

@@ -282,9 +282,9 @@ def sparse_resize(self, sparse_sizes: Tuple[int, int]):
                 rowcount = torch.cat([rowcount, rowcount.new_zeros(diff_0)])
         elif diff_0 < 0:
             if rowptr is not None:
-                rowptr = rowptr[:-diff_0]
+                rowptr = rowptr[:diff_0]
             if rowcount is not None:
-                rowcount = rowcount[:-diff_0]
+                rowcount = rowcount[:diff_0]
 
         diff_1 = sparse_sizes[1] - old_sparse_sizes[1]
         colcount, colptr = self._colcount, self._colptr
@@ -295,9 +295,9 @@ def sparse_resize(self, sparse_sizes: Tuple[int, int]):
                 colcount = torch.cat([colcount, colcount.new_zeros(diff_1)])
         elif diff_1 < 0:
             if colptr is not None:
-                colptr = colptr[:-diff_1]
+                colptr = colptr[:diff_1]
             if colcount is not None:
-                colcount = colcount[:-diff_1]
+                colcount = colcount[:diff_1]
 
         return SparseStorage(
             row=self._row,

torch_sparse/tensor.py

@@ -510,6 +510,15 @@ def to_torch_sparse_csr_tensor(
 
         return torch.sparse_csr_tensor(rowptr, col, value, self.sizes())
 
+    def to_torch_sparse_csc_tensor(
+            self, dtype: Optional[int] = None) -> torch.Tensor:
+        colptr, row, value = self.csc()
+
+        if value is None:
+            value = torch.ones(self.nnz(), dtype=dtype, device=self.device())
+
+        return torch.sparse_csc_tensor(colptr, row, value, self.sizes())
+
 
 # Python Bindings #############################################################