893 - set the action_space to NOTHING so test_reward.py passes and removed unnecessary test print statements
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SunilSamra
@@ -236,7 +236,6 @@ class Primaite(Env):
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# [0, num services] - resolves to service ID (0 = nothing, resolves to service) # noqa
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self.action_dict = self.create_node_action_dict()
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self.action_space = spaces.Discrete(len(self.action_dict))
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print(self.action_space, "NODE action space")
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elif self.action_type == ActionType.ACL:
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_LOGGER.info("Action space type ACL selected")
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# Terms (for ACL action space):
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@@ -248,12 +247,10 @@ class Primaite(Env):
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# [0, num ports] - Port (0 = any, then 1 -> x resolving to port)
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self.action_dict = self.create_acl_action_dict()
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self.action_space = spaces.Discrete(len(self.action_dict))
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print(self.action_space, "ACL action space")
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elif self.action_type == ActionType.ANY:
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_LOGGER.info("Action space type ANY selected - Node + ACL")
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self.action_dict = self.create_node_and_acl_action_dict()
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self.action_space = spaces.Discrete(len(self.action_dict))
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print(self.action_space, "ANY action space")
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else:
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_LOGGER.info("Invalid action type selected")
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# Set up a csv to store the results of the training
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@@ -455,7 +452,6 @@ class Primaite(Env):
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Args:
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_action: The action space from the agent
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"""
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# print("intepret action")
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# At the moment, actions are only affecting nodes
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if self.action_type == ActionType.NODE:
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self.apply_actions_to_nodes(_action)
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@@ -470,7 +466,6 @@ class Primaite(Env):
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): # Node actions in multdiscrete (array) from have len 4
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self.apply_actions_to_nodes(_action)
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else:
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print("invalid action type found")
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logging.error("Invalid action type found")
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def apply_actions_to_nodes(self, _action):
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@@ -1091,7 +1086,6 @@ class Primaite(Env):
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item: A config data item representing action info
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"""
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self.action_type = ActionType[action_info["type"]]
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print("action type selected: ", self.action_type)
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def get_steps_info(self, steps_info):
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"""
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@@ -1196,7 +1190,6 @@ class Primaite(Env):
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"""
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# reserve 0 action to be a nothing action
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actions = {0: [1, 0, 0, 0]}
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# print("node dict function call", self.num_nodes + 1)
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action_key = 1
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for node in range(1, self.num_nodes + 1):
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# 4 node properties (NONE, OPERATING, OS, SERVICE)
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@@ -1204,14 +1197,11 @@ class Primaite(Env):
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# Node Actions either:
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# (NONE, ON, OFF, RESET) - operating state OR (NONE, PATCH) - OS/service state
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# Use MAX to ensure we get them all
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# print(self.num_services, "num services")
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for node_action in range(4):
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for service_state in range(self.num_services):
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action = [node, node_property, node_action, service_state]
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# check to see if its a nothing aciton (has no effect)
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# print("action node",action)
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# check to see if it's a nothing action (has no effect)
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if is_valid_node_action(action):
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print("true")
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actions[action_key] = action
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action_key += 1
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@@ -1223,7 +1213,6 @@ class Primaite(Env):
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actions = {0: [0, 0, 0, 0, 0, 0]}
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action_key = 1
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# print("node count",self.num_nodes + 1)
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# 3 possible action decisions, 0=NOTHING, 1=CREATE, 2=DELETE
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for action_decision in range(3):
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# 2 possible action permissions 0 = DENY, 1 = CREATE
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@@ -1241,13 +1230,10 @@ class Primaite(Env):
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protocol,
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port,
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]
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# print("action acl", action)
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# Check to see if its an action we want to include as possible i.e. not a nothing action
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if is_valid_acl_action_extra(action):
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print("true")
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actions[action_key] = action
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action_key += 1
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# print("false")
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return actions
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@@ -1261,8 +1247,6 @@ class Primaite(Env):
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node_action_dict = self.create_node_action_dict()
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acl_action_dict = self.create_acl_action_dict()
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print(len(node_action_dict), len(acl_action_dict))
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# Change node keys to not overlap with acl keys
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# Only 1 nothing action (key 0) is required, remove the other
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new_node_action_dict = {
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@@ -1273,6 +1257,4 @@ class Primaite(Env):
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# Combine the Node dict and ACL dict
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combined_action_dict = {**acl_action_dict, **new_node_action_dict}
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print("combined_action_dict entry", combined_action_dict.items())
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# print(len(list(combined_action_dict.values())))
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return combined_action_dict
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@@ -184,8 +184,8 @@ def run_generic(env, config_values):
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# Send the observation space to the agent to get an action
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# TEMP - random action for now
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# action = env.blue_agent_action(obs)
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action = env.action_space.sample()
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# action = env.action_space.sample()
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action = 0
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# Run the simulation step on the live environment
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obs, reward, done, info = env.step(action)
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@@ -222,7 +222,6 @@ def run_generic_set_actions(env, config_values):
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# Sets Node 1 Hardware State to OFF
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# Does not resolve any service
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action = 16
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print(action, "ran")
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# Run the simulation step on the live environment
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obs, reward, done, info = env.step(action)
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