add actions to enable/disable ports in routers/firewalls, improve notebook for training PPO agents

src/primaite/game/agent/actions.py

@@ -569,6 +569,53 @@ class NetworkNICDisableAction(NetworkNICAbstractAction):
         self.verb: str = "disable"
 
 
+class NetworkPortAbstractAction(AbstractAction):
+    """
+    Abstract base class for Port actions.
+
+    Any action which applies to a Router/Firewall and uses node_id and port_id as its only two parameters
+    can inherit from this base class.
+    """
+
+    def __init__(self, manager: "ActionManager", num_nodes: int, max_nics_per_node: int, **kwargs) -> None:
+        """Init method for NetworkNICAbstractAction.
+
+        :param manager: Reference to the ActionManager which created this action.
+        :type manager: ActionManager
+        :param num_nodes: Number of nodes in the simulation.
+        :type num_nodes: int
+        :param max_nics_per_node: Maximum number of NICs per node.
+        :type max_nics_per_node: int
+        """
+        super().__init__(manager=manager)
+        self.shape: Dict[str, int] = {"node_id": num_nodes, "port_id": max_nics_per_node}
+        self.verb: str  # define but don't initialise: defends against children classes not defining this
+
+    def form_request(self, node_id: int, port_id: int) -> List[str]:
+        """Return the action formatted as a request which can be ingested by the PrimAITE simulation."""
+        node_name = self.manager.get_node_name_by_idx(node_idx=node_id)
+        port_num = self.manager.get_nic_num_by_idx(node_idx=node_id, nic_idx=port_id)
+        if node_name is None or port_num is None:
+            return ["do_nothing"]
+        return ["network", "node", node_name, "network_interface", port_num, self.verb]
+
+
+class NetworkPortEnableAction(NetworkPortAbstractAction):
+    """Action which enables a PORT."""
+
+    def __init__(self, manager: "ActionManager", num_nodes: int, max_nics_per_node: int, **kwargs) -> None:
+        super().__init__(manager=manager, num_nodes=num_nodes, max_nics_per_node=max_nics_per_node, **kwargs)
+        self.verb: str = "enable"
+
+
+class NetworkPortDisableAction(NetworkPortAbstractAction):
+    """Action which disables a NIC."""
+
+    def __init__(self, manager: "ActionManager", num_nodes: int, max_nics_per_node: int, **kwargs) -> None:
+        super().__init__(manager=manager, num_nodes=num_nodes, max_nics_per_node=max_nics_per_node, **kwargs)
+        self.verb: str = "disable"
+
+
 class ActionManager:
     """Class which manages the action space for an agent."""
 
@@ -602,6 +649,8 @@ class ActionManager:
         "NETWORK_ACL_REMOVERULE": NetworkACLRemoveRuleAction,
         "NETWORK_NIC_ENABLE": NetworkNICEnableAction,
         "NETWORK_NIC_DISABLE": NetworkNICDisableAction,
+        "NETWORK_PORT_ENABLE": NetworkPortEnableAction,
+        "NETWORK_PORT_DISABLE": NetworkPortDisableAction,
     }
     """Dictionary which maps action type strings to the corresponding action class."""
 

src/primaite/notebooks/Training-an-SB3-Agent.ipynb

@@ -45,7 +45,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from stable_baselines3 import PPO"
+    "from stable_baselines3 import PPO\n",
+    "\n",
+    "EPISODE_LEN = 128\n",
+    "NO_STEPS = EPISODE_LEN * 10\n",
+    "BATCH_SIZE = EPISODE_LEN * 10\n",
+    "TOTAL_TIMESTEPS = 5e3 * EPISODE_LEN\n",
+    "LEARNING_RATE = 3e-4"
    ]
   },
   {
@@ -54,7 +60,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "model = PPO('MlpPolicy', gym)\n"
+    "model = PPO('MlpPolicy', gym, learning_rate=LEARNING_RATE,  n_steps=NO_STEPS, batch_size=BATCH_SIZE, verbose=0, tensorboard_log=\"./PPO_UC2/\")\n"
    ]
   },
   {
@@ -63,7 +69,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "model.learn(total_timesteps=10)\n"
+    "model.learn(total_timesteps=TOTAL_TIMESTEPS)\n"
    ]
   },
   {
@@ -72,7 +78,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "model.save(\"deleteme\")"
+    "model.save(\"PrimAITE-v3.0.0b7-PPO\")"
    ]
   },
   {
@@ -80,7 +86,21 @@
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "eval_model = PPO(\"MlpPolicy\", gym)\n",
+    "eval_model = PPO.load(\"PrimAITE-v3.0.0b7-PPO\", gym)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from stable_baselines3.common.evaluation import evaluate_policy\n",
+    "\n",
+    "evaluate_policy(eval_model, gym, n_eval_episodes=10)"
+   ]
   }
  ],
  "metadata": {
@@ -99,7 +119,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,