Source code for hive.utils.experiment

"""Implementation of a simple experiment class."""
import logging
import os

import yaml

from hive.utils.utils import Chomp, create_folder


[docs]class Experiment(object): """Implementation of a simple experiment class.""" def __init__(self, name, dir_name, schedule): """Initializes an experiment object. The experiment state is an exposed property of objects of this class. It can be used to keep track of objects that need to be saved to keep track of the experiment, but don't fit in one of the standard categories. One example of this is the various schedules used in the Runner class. Args: name (str): Name of the experiment. dir_name (str): Absolute path to the directory to save/load the experiment. """ self._name = name self._dir_name = os.path.join(dir_name, name) self._schedule = schedule self._step = 0 create_folder(self._dir_name) self._config = None self._logger = None self._agents = None self._environment = None self.experiment_state = Chomp() self.experiment_state["saving_schedule"] = self._schedule
[docs] def register_experiment( self, config=None, logger=None, agents=None, environment=None, ): """Registers all the components of an experiment. Args: config (Chomp): a config dictionary. logger (Logger): a logger object. agents (Agent | list[Agent]): either an agent object or a list of agents. environment (BaseEnv): an environment object. """ self._config = config self._logger = logger self._logger.log_config(config) if agents is not None and not isinstance(agents, list): agents = [agents] self._agents = agents self._environment = environment
[docs] def update_step(self): """Updates the step of the saving schedule for the experiment.""" self._step += 1 return self._schedule.update()
[docs] def should_save(self): """Returns whether you should save the experiment at the current step.""" return self._schedule.get_value()
[docs] def save(self, tag="current"): """Saves the experiment. Args: tag (str): Tag to prefix the folder. """ save_dir = os.path.join(self._dir_name, tag) create_folder(save_dir) logging.info("Saving the experiment at {}".format(save_dir)) flag_file = os.path.join(save_dir, "flag.p") if os.path.isfile(flag_file): os.remove(flag_file) if self._config is not None: file_name = os.path.join(save_dir, "config.yml") with open(file_name, "w") as f: yaml.safe_dump(dict(self._config), f) if self._logger is not None: folder_name = os.path.join(save_dir, "logger") create_folder(folder_name) self._logger.save(folder_name) if self._agents is not None: for idx, agent in enumerate(self._agents): agent_dir = os.path.join(save_dir, f"agent_{idx}") create_folder(agent_dir) agent.save(agent_dir) if self._environment is not None: file_name = os.path.join(save_dir, "environment.p") self._environment.save(file_name) file_name = os.path.join(save_dir, "experiment_state.p") self.experiment_state.save(file_name) file = open(flag_file, "w") file.close()
[docs] def is_resumable(self, tag="current"): """Returns true if the experiment is resumable. Args: tag (str): Tag for the saved experiment. """ flag_file = os.path.join(self._dir_name, tag, "flag.p") if os.path.isfile(flag_file): return True else: return False
[docs] def resume(self, tag="current"): """Resumes the experiment from a checkpoint. Args: tag (str): Tag for the saved experiment. """ if self.is_resumable(tag): save_dir = os.path.join(self._dir_name, tag) logging.info("Loading the experiment from {}".format(save_dir)) if self._config is not None: file_name = os.path.join(save_dir, "config.yml") with open(file_name) as f: self._config = Chomp(yaml.safe_load(f)) if self._logger is not None: folder_name = os.path.join(save_dir, "logger") self._logger.load(folder_name) if self._agents is not None: for idx, agent in enumerate(self._agents): agent_dir = os.path.join(save_dir, f"agent_{idx}") agent.load(agent_dir) if self._environment is not None: file_name = os.path.join(save_dir, "environment.p") self._environment.load(file_name) file_name = os.path.join(save_dir, "experiment_state.p") self.experiment_state.load(file_name) self._schedule = self.experiment_state["saving_schedule"]