#1522: added a check for existing links in laydown + test that checks if red agent instructions are random
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@@ -1265,6 +1265,12 @@ class Primaite(Env):
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# Bandwidth for all links
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bandwidths = [i.get_bandwidth() for i in list(self.links.values())]
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if len(bandwidths) < 1:
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msg = "Random red agent cannot be used on a network without any links"
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_LOGGER.error(msg)
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raise Exception(msg)
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servers = [node for node in node_list if node.node_type == NodeType.SERVER]
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for n, node in enumerate(nodes_to_be_compromised):
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@@ -1,5 +1,6 @@
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from datetime import time, datetime
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from datetime import datetime
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from primaite.config.lay_down_config import data_manipulation_config_path
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from primaite.environment.primaite_env import Primaite
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from tests import TEST_CONFIG_ROOT
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from tests.conftest import _get_temp_session_path
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@@ -24,9 +25,6 @@ def run_generic(env, config_values):
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if done:
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break
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# Introduce a delay between steps
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time.sleep(config_values.time_delay / 1000)
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# Reset the environment at the end of the episode
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env.reset()
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@@ -40,6 +38,8 @@ def test_random_red_agent_behaviour():
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When the initial state is OFF compared to reference state which is ON.
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"""
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list_of_node_instructions = []
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# RUN TWICE so we can make sure that red agent is randomised
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for i in range(2):
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"""Takes a config path and returns the created instance of Primaite."""
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@@ -49,7 +49,7 @@ def test_random_red_agent_behaviour():
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timestamp_str = session_timestamp.strftime("%Y-%m-%d_%H-%M-%S")
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env = Primaite(
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training_config_path=TEST_CONFIG_ROOT / "one_node_states_on_off_main_config.yaml",
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lay_down_config_path=TEST_CONFIG_ROOT / "one_node_states_on_off_lay_down_config.yaml",
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lay_down_config_path=data_manipulation_config_path(),
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transaction_list=[],
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session_path=session_path,
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timestamp_str=timestamp_str,
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@@ -57,18 +57,18 @@ def test_random_red_agent_behaviour():
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training_config = env.training_config
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training_config.num_steps = env.episode_steps
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# TOOD: This needs t be refactored to happen outside. Should be part of
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# a main Session class.
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if training_config.agent_identifier == "GENERIC":
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run_generic(env, training_config)
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all_red_actions = env.red_node_pol
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list_of_node_instructions.append(all_red_actions)
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run_generic(env, training_config)
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# add red pol instructions to list
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list_of_node_instructions.append(env.red_node_pol)
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# compare instructions to make sure that red instructions are truly random
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for index, instruction in enumerate(list_of_node_instructions):
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for key in list_of_node_instructions[index].keys():
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instruction: NodeInstructionRed = list_of_node_instructions[index][key]
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print(f"run {index}")
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print(f"{key} start step: {instruction.get_start_step()}")
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print(f"{key} end step: {instruction.get_end_step()}")
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print(f"{key} target node id: {instruction.get_target_node_id()}")
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print("")
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# assert not (list_of_node_instructions[0].__eq__(list_of_node_instructions[1]))
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print(list_of_node_instructions[0]["1"].get_start_step())
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print(list_of_node_instructions[0]["1"].get_end_step())
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print(list_of_node_instructions[0]["1"].get_target_node_id())
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print(list_of_node_instructions[1]["1"].get_start_step())
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print(list_of_node_instructions[1]["1"].get_end_step())
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print(list_of_node_instructions[1]["1"].get_target_node_id())
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assert list_of_node_instructions[0].__ne__(list_of_node_instructions[1])
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