Just for unittest

python/paddle/v2/fluid/executor.py

@@ -17,7 +17,7 @@ def __init__(self, places):
             act_places.append(p)
 
         self.executor = core.Executor(act_places)
-        self.places = act_places
+        self.places = places
 
     def aslodtensor(self, data):
         def accumulate(data):
@@ -38,8 +38,7 @@ def parselod(data):
         if not isinstance(data, list):
             # pure tensor case
             tensor = core.LoDTensor()
-            numpy_data = np.array(data).reshape([len(data), 1])
-            tensor.set(numpy_data, self.places[0])
+            tensor.set(data, self.places[0])
             return tensor
         else:
             # lodtensor case
@@ -121,8 +120,10 @@ def run(self,
                 inputs={'X': [feed_var]},
                 outputs={'Out': [out]},
                 attrs={'col': i})
-            # core.set_feed_variable(scope, self.aslodtensor(feed[name]), feed_var.name, i)
-            core.set_feed_variable(scope, feed[name], feed_var.name, i)
+            cur_feed = feed[name]
+            if not isinstance(cur_feed, core.LoDTensor):
+                cur_feed = self.aslodtensor(cur_feed)
+            core.set_feed_variable(scope, cur_feed, feed_var.name, i)
 
         fetch_var = global_block.create_var(
             name=fetch_var_name,

python/paddle/v2/fluid/tests/test_executor_and_mul.py

@@ -41,15 +41,15 @@ class TestExecutor2(unittest.TestCase):
     def test_asnumpy(self):
         seq = data(name='seq', shape=[784], data_type='float32')
         out = sequence_pool(seq, "sum")
-        x = np.ones(shape=(3, 5)).astype('float32')
+        x = numpy.ones(shape=(3, 5)).astype('float32')
         lod = [[0, 2, 3]]
         tensor = core.LoDTensor()
         place = core.CPUPlace()
         tensor.set(x, place)
         tensor.set_lod(lod)
         exe = Executor(place)
-        outs = exe.run(g_main_program, feed={"seq": tensor}, fetch_list=out)
-        self.assertTrue(np.allclose(outs[0], sequence_sum(lod, x)))
+        outs = exe.run(g_main_program, feed={"seq": tensor}, fetch_list=[out])
+        self.assertTrue(numpy.allclose(outs[0], sequence_sum(lod, x)))
 
 
 if __name__ == '__main__':