use csr only for readonly graph.

python/dgl/graph_index.py

@@ -551,37 +551,37 @@ def adjacency_matrix(self, transpose, ctx):
         if not isinstance(transpose, bool):
             raise DGLError('Expect bool value for "transpose" arg,'
                            ' but got %s.' % (type(transpose)))
-        fmt = F.get_preferred_sparse_format()
-        rst = _CAPI_DGLGraphGetAdj(self._handle, transpose, fmt)
-        if fmt == "csr":
+        if self.is_readonly():
+            fmt = F.get_preferred_sparse_format()
+            rst = _CAPI_DGLGraphGetAdj(self._handle, transpose, fmt)
             indptr = F.copy_to(utils.toindex(rst(0)).tousertensor(), ctx)
             indices = F.copy_to(utils.toindex(rst(1)).tousertensor(), ctx)
             shuffle = utils.toindex(rst(2))
             dat = F.ones(indices.shape, dtype=F.float32, ctx=ctx)
             return F.sparse_matrix(dat, ('csr', indices, indptr),
                                    (self.number_of_nodes(), self.number_of_nodes()))[0], shuffle
-        elif fmt == "coo":
-            #src, dst, _ = self.edges(False)
-            #src = src.tousertensor(ctx)  # the index of the ctx will be cached
-            #dst = dst.tousertensor(ctx)  # the index of the ctx will be cached
-            #src = F.unsqueeze(src, dim=0)
-            #dst = F.unsqueeze(dst, dim=0)
-            #if transpose:
-            #    idx = F.cat([src, dst], dim=0)
-            #else:
-            #    idx = F.cat([dst, src], dim=0)
-            #print(idx.shape)
+        else:
+            src, dst, _ = self.edges(False)
+            src = src.tousertensor(ctx)  # the index of the ctx will be cached
+            dst = dst.tousertensor(ctx)  # the index of the ctx will be cached
+            src = F.unsqueeze(src, dim=0)
+            dst = F.unsqueeze(dst, dim=0)
+            if transpose:
+                idx = F.cat([src, dst], dim=0)
+            else:
+                idx = F.cat([dst, src], dim=0)
+
             ## FIXME(minjie): data type
-            idx = F.copy_to(utils.toindex(rst(0)).tousertensor(), ctx)
+            #idx = F.copy_to(utils.toindex(rst(0)).tousertensor(), ctx)
             m = self.number_of_edges()
-            idx = F.reshape(idx, (2, m))
+            #idx = F.reshape(idx, (2, m))
             dat = F.ones((m,), dtype=F.float32, ctx=ctx)
             n = self.number_of_nodes()
             adj, shuffle_idx = F.sparse_matrix(dat, ('coo', idx), (n, n))
             shuffle_idx = utils.toindex(shuffle_idx) if shuffle_idx is not None else None
             return adj, shuffle_idx
-        else:
-            raise Exception("unknown format")
+        #else:
+        #    raise Exception("unknown format")
 
     @utils.cached_member(cache='_cache', prefix='inc')
     def incidence_matrix(self, typestr, ctx):