Timestep based test scheme

agent/BaseAgent.py

@@ -5,10 +5,11 @@
 #######################################################################
 
 import torch
+import numpy as np
 
 class BaseAgent:
     def __init__(self):
-        pass
+        self.testing = False
 
     def close(self):
         if hasattr(self.task, 'close'):
@@ -19,4 +20,22 @@ class BaseAgent:
 
     def load(self, filename):
         state_dict = torch.load(filename, map_location=lambda storage, loc: storage)
-        self.network.load_state_dict(state_dict)
+        self.network.load_state_dict(state_dict)
+
+    def deterministic_test(self):
+        if self.testing:
+            return
+        if not self.config.test_interval:
+            return
+        if self.total_steps % self.config.test_interval:
+            return
+        if not hasattr(self, 'episode'):
+            return
+        rewards = []
+        self.testing = True
+        for _ in range(self.config.test_repetitions):
+            rewards.append(self.episode(deterministic=True))
+        self.testing = False
+        self.config.logger.info('%d deterministic episodes: %f(%f)' % (
+            self.config.test_repetitions, np.mean(rewards), np.std(rewards) / np.sqrt(len(rewards))
+        ))