deprecate TrainConfig(predict_tower). The device should be passed directly to InferenceRunner

CHANGES.md

@@ -8,6 +8,8 @@ so you won't need to look at here very often.
 Here are a list of things that were changed, starting from an early version.
 TensorFlow itself also changed APIs before 1.0 and those are not listed here.
 
++ [2017/10/18]
+	`TrainConfig(predict_tower)` was deprecated. You can set the inference device directly when creating the `InferenceRunner` callback.
 + [2017/10/12](https://github.com/ppwwyyxx/tensorpack/commit/7e963996f615b85f7459455596b4ee9bbd0bce8e).
 	`tensorpack.RL` was deprecated. The RL examples are written with OpenAI gym interface instead.
 + [2017/10/10](https://github.com/ppwwyyxx/tensorpack/commit/7d40e049691d92018f50dc7d45bba5e8b140becc).

tensorpack/callbacks/inference_runner.py

@@ -101,7 +101,7 @@ class InferenceRunner(InferenceRunnerBase):
     A callback that runs a list of :class:`Inferencer` on some :class:`InputSource`.
     """
 
-    def __init__(self, input, infs, tower_name='InferenceTower', extra_hooks=None):
+    def __init__(self, input, infs, tower_name='InferenceTower', device=0, extra_hooks=None):
         """
         Args:
             input (InputSource or DataFlow): The :class:`InputSource` to run
@@ -109,11 +109,13 @@ class InferenceRunner(InferenceRunnerBase):
             infs (list): a list of :class:`Inferencer` instances.
             tower_name (str): the name scope of the tower to build. Need to set a
                 different one if multiple InferenceRunner are used.
+            gpu (int): the device to use
         """
         if isinstance(input, DataFlow):
             input = FeedInput(input, infinite=False)
         assert isinstance(input, InputSource), input
         self._tower_name = tower_name
+        self._device = device
         super(InferenceRunner, self).__init__(
             input, infs, extra_hooks=extra_hooks)
 
@@ -127,8 +129,11 @@ class InferenceRunner(InferenceRunnerBase):
             # old Trainer API
             assert self.trainer.model is not None
             # Use predict_tower in train config. either gpuid or -1
-            tower_id = self.trainer._config.predict_tower[0]
-            device = '/gpu:{}'.format(tower_id) if tower_id >= 0 else '/cpu:0'
+            if self.trainer._config.predict_tower is not None:
+                device = self.trainer._config.predict_tower[0]
+            else:
+                device = self._device
+            device = '/gpu:{}'.format(device) if device >= 0 else '/cpu:0'
 
             input_callbacks = self._input_source.setup(self.trainer.model.get_inputs_desc())
 

tensorpack/train/config.py

@@ -13,6 +13,7 @@ from ..tfutils import (JustCurrentSession,
                        get_default_sess_config, SessionInit)
 from ..tfutils.sesscreate import NewSessionCreator
 from ..input_source import InputSource
+from ..utils.develop import log_deprecated
 
 __all__ = ['TrainConfig']
 
@@ -128,8 +129,9 @@ class TrainConfig(object):
             self.tower = tower
 
         predict_tower = kwargs.pop('predict_tower', None)
-        if predict_tower is None:
-            predict_tower = [0]
+        if predict_tower is not None:
+            log_deprecated("TrainConfig(predict_tower=)",
+                           "InferenceRunner now accepts a 'device' argument.", "2017-12-31")
         self.predict_tower = predict_tower
         if isinstance(self.predict_tower, int):
             self.predict_tower = [self.predict_tower]