Fix error in the way learners check for the presence of a summary writer

The way they were checking causes an exception if the summary writer is None

Author: Islam Elnabarawy

rl/neural_q_learner.py

@@ -193,7 +193,7 @@ def updateModel(self):
         next_state_mask[k] = 1
 
     # whether to calculate summaries
-    calculate_summaries = self.train_iteration % self.summary_every == 0 and self.summary_writer is not None
+    calculate_summaries = self.summary_writer is not None and self.train_iteration % self.summary_every == 0
 
     # perform one update of training
     cost, _, summary_str = self.session.run([

rl/pg_actor_critic.py

@@ -190,7 +190,7 @@ def updateModel(self):
       discounted_rewards[t] = r
 
     # whether to calculate summaries
-    calculate_summaries = self.train_iteration % self.summary_every == 0 and self.summary_writer is not None
+    calculate_summaries = self.summary_writer is not None and self.train_iteration % self.summary_every == 0
 
     # update policy network with the rollout in batches
     for t in range(N-1):

rl/pg_ddpg.py

@@ -205,7 +205,7 @@ def updateModel(self):
         next_state_mask[k] = 1
 
     # whether to calculate summaries
-    calculate_summaries = self.train_iteration % self.summary_every == 0 and self.summary_writer is not None
+    calculate_summaries = self.summary_writer is not None and self.train_iteration % self.summary_every == 0
 
     # compute a = u(s)
     policy_outs = self.session.run(self.policy_outputs, {

rl/pg_reinforce.py

@@ -174,7 +174,7 @@ def updateModel(self):
     discounted_rewards /= np.std(self.all_rewards)
 
     # whether to calculate summaries
-    calculate_summaries = self.train_iteration % self.summary_every == 0 and self.summary_writer is not None
+    calculate_summaries = self.summary_writer is not None and self.train_iteration % self.summary_every == 0
 
     # update policy network with the rollout in batches
     for t in range(N-1):