New benchmarking configurations

Fixed GPU disabling.

environment_wrapper.py

@@ -31,10 +31,6 @@ class Config:
 
 
     def conf_to_name(self):
-        # 0. Allow GPU usage or force tensorflow to use the CPU.
-        if self.force_cpu:
-            os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
-            os.environ["CUDA_VISIBLE_DEVICES"] = ""
         self.name = self.env_type + '_' + self.name
         for layer in self.net_layout:
             self.name += '_' + str(layer) + '_'

networks.py

+import os
 from keras import Sequential
 from keras.models import load_model
 from keras.layers import Dense
@@ -10,6 +11,9 @@ class QNet:
     learn_rate = 0.0005
 
     def __init__(self, conf):
+        if conf.force_cpu:
+            os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
+            os.environ["CUDA_VISIBLE_DEVICES"] = ""
         self.net = None    
         self.net = Sequential()
         self.compile_net(conf)

run_scripts/benchmarks.py

@@ -23,9 +23,9 @@ smallNet.net_layout = [128, 32]
 smallNet.conf_to_name()
 
 smallNetSlow = copy.deepcopy(c)
-smallNetSlow.name = 'SmallNetSlow'
+smallNetSlow.name = 'SmallNet'
 smallNetSlow.net_layout = [128, 32]
-smallNetSlow.learn_rate = 0.0005
+smallNetSlow.eps_decay = 0.9996
 smallNetSlow.conf_to_name()
 
 smallNetDeep = copy.deepcopy(c)
@@ -92,6 +92,12 @@ verryLittleNetDeep.name = 'VerryLittleNetDeep'
 verryLittleNetDeep.net_layout = [64, 32, 32]
 verryLittleNetDeep.conf_to_name()
 
+ThisHasToBeTooBig = copy.deepcopy(c)
+ThisHasToBeTooBig.name = 'ThisHasToBeTooBig'
+ThisHasToBeTooBig.force_cpu = False
+ThisHasToBeTooBig.net_layout = [4096, 2048]
+ThisHasToBeTooBig.conf_to_name()
+
 lun = copy.deepcopy(c)
 lun.run_episodes = 500
 lun.name = 'NormalLunarDoubleNotSoMoreLearn'
@@ -114,6 +120,8 @@ configuration = smallNetSlow
 # configuration = deepNetSlowLearn
 # configuration = smallNetDeepSlowLearn
 # configuration = lun
+configuration = ThisHasToBeTooBig
+
 print(configuration.name)
 configuration.agent = QAgent(configuration)
 main.run(configuration)