remove action spec attribute from policy

ml-agents/mlagents/trainers/policy/policy.py

         condition_sigma_on_obs: bool = True,
     ):
         self.behavior_spec = behavior_spec
-        self.action_spec = behavior_spec.action_spec
         self.trainer_settings = trainer_settings
         self.network_settings: NetworkSettings = trainer_settings.network_settings
         self.seed = seed

ml-agents/mlagents/trainers/policy/tf_policy.py

             reparameterize,
             condition_sigma_on_obs,
         )
-        if self.action_spec.continuous_size > 0 and self.action_spec.discrete_size > 0:
+        if self.behavior_spec.action_spec.continuous_size > 0 and self.behavior_spec.action_spec.discrete_size > 0:
             raise UnityPolicyException(
                 "TensorFlow does not support mixed action spaces. Please run with the Torch framework."
             )

ml-agents/mlagents/trainers/policy/torch_policy.py

     ) -> Tuple[SplitObservations, np.ndarray]:
         vec_vis_obs = SplitObservations.from_observations(decision_requests.obs)
         mask = None
-        if self.action_spec.discrete_size > 0:
+        if self.behavior_spec.action_spec.discrete_size > 0:
             mask = torch.ones([len(decision_requests), np.sum(self.act_size)])
             if decision_requests.action_mask is not None:
                 mask = torch.as_tensor(

ml-agents/mlagents/trainers/torch/components/bc/module.py

         expert_actions: torch.Tensor,
     ) -> torch.Tensor:
         bc_loss = 0
-        if self.policy.action_spec.continuous_size > 0:
+        if self.policy.behavior_spec.action_spec.continuous_size > 0:
-        if self.policy.action_spec.discrete_size > 0:
+        if self.policy.behavior_spec.action_spec.discrete_size > 0:
-                self.policy.action_spec.discrete_branches,
+                self.policy.behavior_spec.action_spec.discrete_branches,
             )
 
             log_prob_branches = ModelUtils.break_into_branches(
         vec_obs = [ModelUtils.list_to_tensor(mini_batch_demo["vector_obs"])]
         act_masks = None
         expert_actions = AgentAction.from_dict(mini_batch_demo)
-        if self.policy.action_spec.discrete_size > 0:
+        if self.policy.behavior_spec.action_spec.discrete_size > 0:
             act_masks = ModelUtils.list_to_tensor(
                 np.ones(
                     (