breakout img

examples/Atari2600/README.md

+![breakout](breakout.jpg)
+
 Reproduce the following reinforcement learning methods:
 
 + Nature-DQN in:

tensorpack/predict/base.py

@@ -87,17 +87,17 @@ class OfflinePredictor(OnlinePredictor):
                     sess, input_vars, output_vars, config.return_input)
 
 
-class AsyncOnlinePredictor(PredictorBase):
-    def __init__(self, sess, enqueue_op, output_vars, return_input=False):
-        """
-        :param enqueue_op: an op to feed inputs with.
-        :param output_vars: a list of directly-runnable (no extra feeding requirements)
-            vars producing the outputs.
-        """
-        self.session = sess
-        self.enqop = enqueue_op
-        self.output_vars = output_vars
-        self.return_input = return_input
-
-    def put_task(self, dp, callback):
-        pass
+#class AsyncOnlinePredictor(PredictorBase):
+    #def __init__(self, sess, enqueue_op, output_vars, return_input=False):
+        #"""
+        #:param enqueue_op: an op to feed inputs with.
+        #:param output_vars: a list of directly-runnable (no extra feeding requirements)
+            #vars producing the outputs.
+        #"""
+        #self.session = sess
+        #self.enqop = enqueue_op
+        #self.output_vars = output_vars
+        #self.return_input = return_input
+
+    #def put_task(self, dp, callback):
+        #pass

tensorpack/train/base.py

@@ -107,7 +107,7 @@ class Trainer(object):
         get_global_step_var()   # ensure there is such var, before finalizing the graph
         logger.info("Setup callbacks ...")
         callbacks = self.config.callbacks
-        callbacks.setup_graph(self)
+        callbacks.setup_graph(self) # TODO use weakref instead?
         logger.info("Initializing graph variables ...")
         self.sess.run(tf.initialize_all_variables())
         self.config.session_init.init(self.sess)