Still use gpu as default ps device

tensorpack/train/multigpu.py

@@ -151,19 +151,16 @@ class SyncMultiGPUTrainerParameterServer(MultiGPUTrainerBase):
     See https://www.tensorflow.org/performance/benchmarks for details.
     """
 
-    def __init__(self, config, ps_device=None, gpu_prefetch=True):
+    def __init__(self, config, ps_device='gpu', gpu_prefetch=True):
         """
         Args:
             config(TrainConfig): Must contain 'model' and either one of 'data' or 'dataflow'.
-            ps_device: either 'gpu' or 'cpu', where variables are stored. Setting to 'cpu' might help if #gpu>=4
-                Defaults to 'cpu' when #gpu >= 4.
+            ps_device: either 'gpu' or 'cpu', where variables are stored.  Setting to 'cpu' might help when #gpu>=4
             gpu_prefetch(bool): whether to prefetch the data to each GPU. Usually improve performance.
         """
         apply_prefetch_policy(config, gpu_prefetch)
         self._input_source = config.data
 
-        if ps_device is None:
-            ps_device = 'cpu' if config.nr_tower >= 4 else 'gpu'
         assert ps_device in ['gpu', 'cpu'], ps_device
         self._ps_device = ps_device
         super(SyncMultiGPUTrainerParameterServer, self).__init__(config)