fixes

torch_sparse/cat.py

@@ -38,8 +38,7 @@ def cat(tensors, dim):
             value=torch.cat(values, dim=0) if has_value else None,
             sparse_size=sparse_size,
             rowcount=torch.cat(rowcounts) if has_rowcount else None,
-            rowptr=torch.cat(rowptrs) if has_rowptr else None,
-            is_sorted=True)
+            rowptr=torch.cat(rowptrs) if has_rowptr else None, is_sorted=True)
 
     if dim == 1:
         raise NotImplementedError

torch_sparse/reduce.py

@@ -61,8 +61,8 @@ def __reduce__(src, dim=None, reduce='add', deterministic=False):
     deterministic = src.storage._csr2csc is not None or deterministic
 
     if sparse_dims[0] == 0 and deterministic and src.has_value():
-        csr2csc, colptr = src.storage.csr2csc, src.storage.colptr
-        out = segment_csr(value[csr2csc], colptr)
+        csr2csc = src.storage.csr2csc
+        out = segment_csr(value[csr2csc], src.storage.colptr)
         out = out[0] if len(dense_dims) > 0 and isinstance(out, tuple) else out
         return out
 

torch_sparse/tensor.py

@@ -81,7 +81,7 @@ class SparseTensor(object):
         return self.storage.rowptr, self.storage.col, self.storage.value
 
     def csc(self):
-        perm = self.storage.csr2csc
+        perm = self.storage.csr2csc  # Compute `csr2csc` first.
         return (self.storage.colptr, self.storage.row[perm],
                 self.storage.value[perm] if self.has_value() else None)