some fix

python/dgl/data/tree.py

@@ -79,22 +79,3 @@ class SST(object):
     @property 
     def num_vocabs(self):
         return len(self.vocab)
-
-    @staticmethod
-    def batcher(batch):
-        nid_with_word = []
-        wordid = []
-        label = []
-        gnid = 0
-        for tree in batch:
-            for nid in range(tree.number_of_nodes()):
-                if tree.nodes[nid]['x'] != SST.PAD_WORD:
-                    nid_with_word.append(gnid)
-                    wordid.append(tree.nodes[nid]['x'])
-                label.append(tree.nodes[nid]['y'])
-                gnid += 1
-        batch_trees = dgl.batch(batch)
-        return SSTBatch(graph=batch_trees,
-                        nid_with_word=F.tensor(nid_with_word, dtype=F.int64),
-                        wordid=F.tensor(wordid, dtype=F.int64),
-                        label=F.tensor(label, dtype=F.int64))

python/dgl/graph.py

@@ -826,7 +826,7 @@ class DGLGraph(object):
     def _batch_send(self, u, v, message_func):
         if is_all(u) and is_all(v):
             u, v, _ = self._graph.edges()
-            self._msg_graph.add_edges(u, v)
+            self._msg_graph.add_edges(u, v) # TODO(minjie): can be optimized
             # call UDF
             src_reprs = self.get_n_repr(u)
             edge_reprs = self.get_e_repr()
@@ -1128,30 +1128,28 @@ class DGLGraph(object):
         self.apply_nodes(ALL, apply_node_func)
 
     def propagate(self,
-                  iterator='bfs',
+                  traverser='topo',
                   message_func="default",
                   reduce_func="default",
                   apply_node_func="default",
                   **kwargs):
-        """Propagate messages and update nodes using iterator.
+        """Propagate messages and update nodes using graph traversal.
 
         A convenient function for passing messages and updating
-        nodes according to the iterator. The iterator can be
-        any of the pre-defined iterators ('bfs', 'dfs', 'pre-order',
-        'mid-order', 'post-order'). The computation will be unrolled
-        in the backend efficiently. User can also provide custom
-        iterator that generates the edges and nodes.
+        nodes according to the traverser. The traverser can be
+        any of the pre-defined traverser (e.g. 'topo'). User can also provide custom
+        traverser that generates the edges and nodes.
 
         Parameters
         ----------
+        traverser : str or generator of edges.
+          The traverser of the graph.
         message_func : str or callable
           The message function.
         reduce_func : str or callable
           The reduce function.
         apply_node_func : str or callable
           The update function.
-        iterator : str or generator of steps.
-          The iterator of the graph.
         kwargs : keyword arguments, optional
             Arguments for pre-defined iterators.
         """

python/setup.py

@@ -17,7 +17,6 @@ setuptools.setup(
         'numpy>=1.14.0',
         'scipy>=1.1.0',
         'networkx>=2.1',
-        'python-igraph>=0.7.0',
     ],
     data_files=[('', ['VERSION'])],
-    url='https://github.com/jermainewang/dgl-1')
+    url='https://github.com/jermainewang/dgl')