small fix on a3c

examples/A3C-Gym/train-atari.py

@@ -263,11 +263,11 @@ if __name__ == '__main__':
         nr_gpu = get_nr_gpu()
         if nr_gpu > 0:
             if nr_gpu > 1:
-                predict_tower = range(nr_gpu)[-nr_gpu // 2:]
+                predict_tower = list(range(nr_gpu))[-nr_gpu // 2:]
             else:
                 predict_tower = [0]
             PREDICTOR_THREAD = len(predict_tower) * PREDICTOR_THREAD_PER_GPU
-            train_tower = range(nr_gpu)[:-nr_gpu // 2] or [0]
+            train_tower = list(range(nr_gpu))[:-nr_gpu // 2] or [0]
             logger.info("[BA3C] Train on gpu {} and infer on gpu {}".format(
                 ','.join(map(str, train_tower)), ','.join(map(str, predict_tower))))
             trainer = AsyncMultiGPUTrainer

tensorpack/dataflow/common.py

@@ -221,7 +221,8 @@ class MapData(ProxyDataFlow):
                 Note that if you use the filter feature, ``ds.size()`` will be incorrect.
 
         Note:
-            Be careful if func modifies datapoints.
+            Please make sure func doesn't modify the components
+            unless you're certain it's safe.
         """
         super(MapData, self).__init__(ds)
         self.func = func
@@ -245,8 +246,9 @@ class MapDataComponent(MapData):
             index (int): index of the component.
 
         Note:
-            This proxy itself doesn't modify the datapoints. But be careful because func
-            may modify the components.
+            This proxy itself doesn't modify the datapoints.
+            But please make sure func doesn't modify the components
+            unless you're certain it's safe.
         """
         def f(dp):
             r = func(dp[index])

tensorpack/train/predict.py

@@ -24,7 +24,7 @@ class PredictorFactory(object):
         def fn(_):
             self.model.build_graph(self.model.get_reused_placehdrs())
         self._tower_builder = PredictorTowerBuilder(fn)
-        assert isinstance(self.towers, list)
+        assert isinstance(self.towers, list), self.towers
 
     def get_predictor(self, input_names, output_names, tower):
         """