Source code for csle_common.dao.jobs.training_job_config

from typing import Dict, Any, List
from csle_common.dao.training.experiment_config import ExperimentConfig
from csle_common.dao.training.experiment_result import ExperimentResult
from csle_common.dao.simulation_config.simulation_trace import SimulationTrace
from csle_base.json_serializable import JSONSerializable


[docs]class TrainingJobConfig(JSONSerializable): """ DTO representing the configuration of a training job """ def __init__(self, simulation_env_name: str, experiment_config: ExperimentConfig, progress_percentage: float, pid: int, experiment_result: ExperimentResult, emulation_env_name: str, simulation_traces: List[SimulationTrace], num_cached_traces: int, log_file_path: str, descr: str, physical_host_ip: str) -> None: """ Initializes the DTO :param simulation_env_name: the simulation environment name :param simulation_env_name: the emulation environment name :param experiment_config: the experiment configuration :param progress_percentage:the progress of the job in percentage :param pid: the pid of the process :param experiment_result: the result of the job :param emulation_env_config: the configuration of the emulation environment :param simulation_env_config: the configuration of the simulation environment :param simulation_traces: the list of simulation traces :param num_cached_traces: number of cached simulation traces :param descr: description of the job :param physical_host_ip: the IP of the physical host where the job is running """ self.simulation_env_name = simulation_env_name self.emulation_env_name = emulation_env_name self.experiment_config = experiment_config self.experiment_result = experiment_result self.progress_percentage = round(progress_percentage, 3) self.pid = pid self.id = -1 self.running = False self.simulation_traces = simulation_traces self.num_cached_traces = num_cached_traces self.log_file_path = log_file_path self.descr = descr self.physical_host_ip = physical_host_ip
[docs] def to_dict(self) -> Dict[str, Any]: """ Converts the object to a dict representation :return: a dict representation of the object """ d: Dict[str, Any] = {} d["simulation_env_name"] = self.simulation_env_name d["emulation_env_name"] = self.emulation_env_name d["experiment_config"] = self.experiment_config.to_dict() d["progress_percentage"] = round(self.progress_percentage, 2) d["pid"] = self.pid d["id"] = self.id d["experiment_result"] = self.experiment_result.to_dict() d["running"] = self.running d["simulation_traces"] = list(map(lambda x: x.to_dict(), self.simulation_traces)) d["num_cached_traces"] = self.num_cached_traces d["log_file_path"] = self.log_file_path d["descr"] = self.descr d["physical_host_ip"] = self.physical_host_ip return d
[docs] @staticmethod def from_dict(d: Dict[str, Any]) -> "TrainingJobConfig": """ Converts a dict representation of the object to an instance :param d: the dict to convert :return: the created instance """ obj = TrainingJobConfig( simulation_env_name=d["simulation_env_name"], experiment_config=ExperimentConfig.from_dict(d["experiment_config"]), progress_percentage=d["progress_percentage"], pid=d["pid"], experiment_result=ExperimentResult.from_dict(d["experiment_result"]), emulation_env_name=d["emulation_env_name"], simulation_traces=list(map(lambda x: SimulationTrace.from_dict(x), d["simulation_traces"])), num_cached_traces=d["num_cached_traces"], log_file_path=d["log_file_path"], descr=d["descr"], physical_host_ip=d["physical_host_ip"]) obj.id = d["id"] obj.running = d["running"] return obj
def __str__(self) -> str: """ :return: a string representation of the object """ return f"simulation_env_name: {self.simulation_env_name}, experiment_config: {self.experiment_config}, " \ f"progress_percentage: {self.progress_percentage}, pid: {self.pid}," \ f"id: {self.id}, experiment_result: {self.experiment_result}, running: {self.running}, " \ f"emulation_env_name: {self.emulation_env_name}, " \ f"simulation_traces: {list(map(lambda x: str(x), self.simulation_traces))}," \ f"num_cached_traces: {self.num_cached_traces}, log_file_path: {self.log_file_path}, " \ f"descr: {self.descr}, physical_host_ip: {self.physical_host_ip}"
[docs] @staticmethod def from_json_file(json_file_path: str) -> "TrainingJobConfig": """ Reads a json file and converts it to a DTO :param json_file_path: the json file path :return: the converted DTO """ import io import json with io.open(json_file_path, 'r') as f: json_str = f.read() return TrainingJobConfig.from_dict(json.loads(json_str))