273876873e
- 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.
114 lines
3.9 KiB
Python
114 lines
3.9 KiB
Python
# Crown Copyright (C) Dstl 2022. DEFCON 703. Shared in confidence.
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"""Writes the Transaction log list out to file for evaluation to utilse."""
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import csv
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from pathlib import Path
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from primaite import getLogger
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_LOGGER = getLogger(__name__)
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def turn_action_space_to_array(_action_space):
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"""
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Turns action space into a string array so it can be saved to csv.
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Args:
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_action_space: The action space.
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"""
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return_array = []
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for x in range(len(_action_space)):
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return_array.append(str(_action_space[x]))
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return return_array
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def turn_obs_space_to_array(_obs_space, _obs_assets, _obs_features):
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"""
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Turns observation space into a string array so it can be saved to csv.
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Args:
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_obs_space: The observation space
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_obs_assets: The number of assets (i.e. nodes or links) in the observation space
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_obs_features: The number of features associated with the asset
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"""
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return_array = []
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for x in range(_obs_assets):
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for y in range(_obs_features):
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return_array.append(str(_obs_space[x][y]))
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return return_array
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def write_transaction_to_file(transaction_list, session_path: Path, timestamp_str: str):
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"""
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Writes transaction logs to file to support training evaluation.
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:param transaction_list: The list of transactions from all steps and all
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episodes.
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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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# Get the first transaction and use it to determine the makeup of the
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# observation space and action space
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# Label the obs space fields in csv as "OSI_1_1", "OSN_1_1" and action
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# space as "AS_1"
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# This will be tied into the PrimAITE Use Case so that they make sense
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template_transation = transaction_list[0]
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action_length = template_transation.action_space.size
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obs_shape = template_transation.obs_space_post.shape
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obs_assets = template_transation.obs_space_post.shape[0]
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if len(obs_shape) == 1:
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# bit of a workaround but I think the way transactions are written will change soon
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obs_features = 1
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else:
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obs_features = template_transation.obs_space_post.shape[1]
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# Create the action space headers array
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action_header = []
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for x in range(action_length):
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action_header.append("AS_" + str(x))
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# Create the observation space headers array
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obs_header_initial = []
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obs_header_new = []
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for x in range(obs_assets):
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for y in range(obs_features):
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obs_header_initial.append("OSI_" + str(x) + "_" + str(y))
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obs_header_new.append("OSN_" + str(x) + "_" + str(y))
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# Open up a csv file
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header = ["Timestamp", "Episode", "Step", "Reward"]
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header = header + action_header + obs_header_initial + obs_header_new
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try:
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filename = session_path / f"all_transactions_{timestamp_str}.csv"
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csv_file = open(filename, "w", encoding="UTF8", newline="")
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csv_writer = csv.writer(csv_file)
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csv_writer.writerow(header)
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for transaction in transaction_list:
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csv_data = [
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str(transaction.timestamp),
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str(transaction.episode_number),
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str(transaction.step_number),
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str(transaction.reward),
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]
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csv_data = (
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csv_data
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+ turn_action_space_to_array(transaction.action_space)
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+ turn_obs_space_to_array(
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transaction.obs_space_pre, obs_assets, obs_features
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)
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+ turn_obs_space_to_array(
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transaction.obs_space_post, obs_assets, obs_features
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)
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)
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csv_writer.writerow(csv_data)
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csv_file.close()
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except Exception:
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_LOGGER.error("Could not save the transaction file", exc_info=True)
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