Enabling-more-agents-for-Batch-RL-and-cleanup (#258)

allowing for the last training batch drawn to be smaller than batch_size + adding support for more agents in BatchRL by adding softmax with temperature to the corresponding heads + adding a CartPole_QR_DQN preset with a golden test + cleanups

rl_coach/agents/nec_agent.py

@@ -133,7 +133,7 @@ class NECAgent(ValueOptimizationAgent):
         TD_targets = self.networks['main'].online_network.predict(batch.states(network_keys))
         bootstrapped_return_from_old_policy = batch.n_step_discounted_rewards()
         #  only update the action that we have actually done in this transition
-        for i in range(self.ap.network_wrappers['main'].batch_size):
+        for i in range(batch.size):
             TD_targets[i, batch.actions()[i]] = bootstrapped_return_from_old_policy[i]
 
         # set the gradients to fetch for the DND update