#915 - Created app dirs and set as constants in the top-level init.
- renamed _config_values_main to training_config.py and renamed the ConfigValuesMain class to TrainingConfig. Moved training_config.py to src/primaite/config/training_config.py - Renamed all training config yaml file keys to make creating an instance of TrainingConfig easier. Moved action_type and num_steps over to the training config. - Decoupled the training config and lay down config. - Refactored main.py so that it can be ran from CLI and can take a training config path and a lay down config path. - refactored all outputs so that they save to the session dir. - Added some necessary setup scripts that handle creating app dirs, fronting example config files to the user, fronting demo notebooks to the user, performing clean-up in between installations etc. - Added functions that attempt to retrieve the file path of users example config files that have been fronted by the primaite setup. - Added logging config and a getLogger function in the top-level init. - Refactored all logs entries logged to use a logger using the primaite logging config. - Added basic typer CLI for doing things like setup, viewing logs, viewing primaite version, running a basic session. - Updated test to use new features and config structures. - Began updating docs. More to do here.
This commit is contained in:
Chris McCarthy
@@ -6,7 +6,8 @@ import csv
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import logging
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import os.path
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from datetime import datetime
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from typing import Dict, Tuple
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from pathlib import Path
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from typing import Dict, Tuple, Union
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import networkx as nx
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import numpy as np
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@@ -28,6 +29,8 @@ from primaite.common.enums import (
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SoftwareState,
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)
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from primaite.common.service import Service
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from primaite.config import training_config
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from primaite.config.training_config import TrainingConfig
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from primaite.environment.reward import calculate_reward_function
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from primaite.links.link import Link
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from primaite.nodes.active_node import ActiveNode
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@@ -56,26 +59,36 @@ class Primaite(Env):
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OBSERVATION_SPACE_HIGH_VALUE = 1000000 # Highest value within an observation space
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def __init__(self, _config_values, _transaction_list):
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def __init__(
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self,
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training_config_path: Union[str, Path],
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lay_down_config_path: Union[str, Path],
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transaction_list,
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session_path: Path,
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timestamp_str: str,
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):
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"""
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Init.
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The Primaite constructor.
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Args:
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_episode_steps: The number of steps for the episode
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_config_filename: The name of config file
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_transaction_list: The list of transactions to populate
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_agent_identifier: Identifier for the agent
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:param training_config_path: The training config filepath.
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:param lay_down_config_path: The lay down config filepath.
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:param transaction_list: The list of transactions to populate.
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:param session_path: The directory path the session is writing to.
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:param timestamp_str: The session timestamp in the format:
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<yyyy-mm-dd>_<hh-mm-ss>.
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"""
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super(Primaite, self).__init__()
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self._training_config_path = training_config_path
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self._lay_down_config_path = lay_down_config_path
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# Take a copy of the config values
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self.config_values = _config_values
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self.config_values: TrainingConfig = training_config.load(training_config_path)
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# Number of steps in an episode
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self.episode_steps = 0
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self.episode_steps = self.config_values.num_steps
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super(Primaite, self).__init__()
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# Transaction list
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self.transaction_list = _transaction_list
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self.transaction_list = transaction_list
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# The agent in use
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self.agent_identifier = self.config_values.agent_identifier
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@@ -153,13 +166,10 @@ class Primaite(Env):
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self.observation_type = ObservationType.BOX
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# Open the config file and build the environment laydown
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try:
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self.config_file = open(self.config_values.config_filename_use_case, "r")
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self.config_data = yaml.safe_load(self.config_file)
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self.load_config()
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except Exception:
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_LOGGER.error("Could not load the environment configuration")
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_LOGGER.error("Exception occured", exc_info=True)
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with open(self._lay_down_config_path, "r") as file:
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# Open the config file and build the environment laydown
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self.config_data = yaml.safe_load(file)
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self.load_lay_down_config()
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# Store the node objects as node attributes
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# (This is so we can access them as objects)
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@@ -179,12 +189,8 @@ class Primaite(Env):
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now = datetime.now() # current date and time
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time = now.strftime("%Y%m%d_%H%M%S")
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path = "outputs/diagrams"
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is_dir = os.path.isdir(path)
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if not is_dir:
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os.makedirs(path)
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filename = "outputs/diagrams/network_" + time + ".png"
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plt.savefig(filename, format="PNG")
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file_path = session_path / f"network_{timestamp_str}.png"
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plt.savefig(file_path, format="PNG")
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plt.clf()
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except Exception:
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_LOGGER.error("Could not save network diagram")
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@@ -236,13 +242,9 @@ class Primaite(Env):
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time = now.strftime("%Y%m%d_%H%M%S")
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header = ["Episode", "Average Reward"]
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# Check whether the output/rerults folder exists (doesn't exist by default install)
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path = "outputs/results/"
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is_dir = os.path.isdir(path)
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if not is_dir:
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os.makedirs(path)
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filename = "outputs/results/average_reward_per_episode_" + time + ".csv"
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self.csv_file = open(filename, "w", encoding="UTF8", newline="")
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file_name = f"average_reward_per_episode_{timestamp_str}.csv"
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file_path = session_path / file_name
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self.csv_file = open(file_path, "w", encoding="UTF8", newline="")
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self.csv_writer = csv.writer(self.csv_file)
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self.csv_writer.writerow(header)
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except Exception:
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@@ -404,7 +406,6 @@ class Primaite(Env):
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def __close__(self):
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"""Override close function."""
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self.csv_file.close()
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self.config_file.close()
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def init_acl(self):
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"""Initialise the Access Control List."""
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@@ -888,7 +889,7 @@ class Primaite(Env):
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elif self.observation_type == ObservationType.MULTIDISCRETE:
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self._update_env_obs_multidiscrete()
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def load_config(self):
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def load_lay_down_config(self):
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"""Loads config data in order to build the environment configuration."""
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for item in self.config_data:
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if item["itemType"] == "NODE":
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@@ -918,15 +919,9 @@ class Primaite(Env):
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elif item["itemType"] == "PORTS":
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# Create the list of ports
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self.create_ports_list(item)
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elif item["itemType"] == "ACTIONS":
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# Get the action information
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self.get_action_info(item)
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elif item["itemType"] == "OBSERVATIONS":
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# Get the observation information
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self.get_observation_info(item)
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elif item["itemType"] == "STEPS":
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# Get the steps information
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self.get_steps_info(item)
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else:
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# Do nothing (bad formatting)
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pass
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@@ -1247,15 +1242,6 @@ class Primaite(Env):
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# Set the number of ports
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self.num_ports = len(self.ports_list)
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def get_action_info(self, action_info):
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"""
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Extracts action_info.
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Args:
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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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def get_observation_info(self, observation_info):
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"""Extracts observation_info.
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@@ -1264,16 +1250,6 @@ class Primaite(Env):
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"""
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self.observation_type = ObservationType[observation_info["type"]]
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def get_steps_info(self, steps_info):
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"""
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Extracts steps_info.
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Args:
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item: A config data item representing steps info
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"""
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self.episode_steps = int(steps_info["steps"])
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_LOGGER.info("Training episodes have " + str(self.episode_steps) + " steps")
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def reset_environment(self):
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"""
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# Resets environment.
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