fix DQN learning bug (#632)

* Update run.py

* Update utils.py

* Update utils.py

baselines/deepq/utils.py

@@ -1,8 +1,6 @@
 from baselines.common.input import observation_input
 from baselines.common.tf_util import adjust_shape
 
-import tensorflow as tf
-
 # ================================================================
 # Placeholders
 # ================================================================
@@ -40,29 +38,6 @@ class PlaceholderTfInput(TfInput):
         return {self._placeholder: adjust_shape(self._placeholder, data)}
 
 
-class Uint8Input(PlaceholderTfInput):
-    def __init__(self, shape, name=None):
-        """Takes input in uint8 format which is cast to float32 and divided by 255
-        before passing it to the model.
-
-        On GPU this ensures lower data transfer times.
-
-        Parameters
-        ----------
-        shape: [int]
-            shape of the tensor.
-        name: str
-            name of the underlying placeholder
-        """
-
-        super().__init__(tf.placeholder(tf.uint8, [None] + list(shape), name=name))
-        self._shape = shape
-        self._output = tf.cast(super().get(), tf.float32) / 255.0
-
-    def get(self):
-        return self._output
-
-
 class ObservationInput(PlaceholderTfInput):
     def __init__(self, observation_space, name=None):
         """Creates an input placeholder tailored to a specific observation space

baselines/run.py

@@ -99,7 +99,7 @@ def build_env(args):
             env = atari_wrappers.make_atari(env_id)
             env.seed(seed)
             env = bench.Monitor(env, logger.get_dir())
-            env = atari_wrappers.wrap_deepmind(env, frame_stack=True, scale=True)
+            env = atari_wrappers.wrap_deepmind(env, frame_stack=True)
         elif alg == 'trpo_mpi':
             env = atari_wrappers.make_atari(env_id)
             env.seed(seed)