shared baseline and v

ml-agents/mlagents/trainers/optimizer/torch_optimizer.py

             team_act=team_actions,
         )
 
-        value_estimates, mem = self.policy.actor_critic.target_critic_value(
+        value_estimates, mem = self.policy.actor_critic.critic_value(
             current_obs,
             memory,
             sequence_length=batch.num_experiences,
-        boot_value_estimates, mem = self.policy.actor_critic.target_critic_value(
+        boot_value_estimates, mem = self.policy.actor_critic.critic_value(
             next_obs,
             memory,
             sequence_length=batch.num_experiences,

ml-agents/mlagents/trainers/torch/networks.py

             team_obs=team_obs,
             team_act=team_act,
         )
-        value_outputs, _ = self.target_critic_value(inputs, memories=critic_mem, sequence_length=sequence_length, team_obs=team_obs)
+        value_outputs, _ = self.critic_value(inputs, memories=critic_mem, sequence_length=sequence_length, team_obs=team_obs)
 
         return log_probs, entropies, q_outputs, baseline_outputs, value_outputs