[Bugfix] fixes NLTK dependency (#125) and #126 (#131)

python/dgl/__init__.py

 from . import backend
-from . import data
+# One has to manually import dgl.data; fixes #125
+#from . import data
 from . import function
 from . import nn
 

python/dgl/utils.py

@@ -37,7 +37,10 @@ class Index(object):
                 self._list_data = np.array([int(data)]).astype(np.int64)
             except:
                 try:
-                    self._list_data = np.array(data).astype(np.int64)
+                    data = np.array(data).astype('int64')
+                    if data.ndim != 1:
+                        raise ValueError('Index data must be 1D int64 vector, but got: %s' % str(data))
+                    self._list_data = data
                 except:
                     raise ValueError('Error index data: %s' % str(data))
             self._user_tensor_data[F.cpu()] = F.zerocopy_from_numpy(self._list_data)

tests/pytorch/test_basics.py

@@ -191,11 +191,16 @@ def test_update_routines():
 
     # send_and_recv
     reduce_msg_shapes.clear()
-    u = th.tensor([0, 0, 0, 4, 5, 6])
-    v = th.tensor([1, 2, 3, 9, 9, 9])
+    u = [0, 0, 0, 4, 5, 6]
+    v = [1, 2, 3, 9, 9, 9]
     g.send_and_recv((u, v))
     assert(reduce_msg_shapes == {(1, 3, D), (3, 1, D)})
     reduce_msg_shapes.clear()
+    try:
+        g.send_and_recv([u, v])
+        assert False
+    except ValueError:
+        pass
 
     # pull
     v = th.tensor([1, 2, 3, 9])