def __init__(self, config=None, logger_creator=None):
"""Initialize an Trainable.
Sets up logging and points ``self.logdir`` to a directory in which
training outputs should be placed.
Subclasses should prefer defining ``setup()`` instead of overriding
``__init__()`` directly.
Args:
config (dict): Trainable-specific configuration data. By default
will be saved as ``self.config``.
logger_creator (func): Function that creates a ray.tune.Logger
object. If unspecified, a default logger is created.
"""
self._experiment_id = uuid.uuid4().hex
self.config = config or {}
trial_info = self.config.pop(TRIAL_INFO, None)
if self.is_actor():
disable_ipython()
self._result_logger = self._logdir = None
self._create_logger(self.config, logger_creator)
self._stdout_context = self._stdout_fp = self._stdout_stream = None
self._stderr_context = self._stderr_fp = self._stderr_stream = None
self._stderr_logging_handler = None
stdout_file = self.config.pop(STDOUT_FILE, None)
stderr_file = self.config.pop(STDERR_FILE, None)
self._open_logfiles(stdout_file, stderr_file)
self._iteration = 0
self._time_total = 0.0
self._timesteps_total = None
self._episodes_total = None
self._time_since_restore = 0.0
self._timesteps_since_restore = 0
self._iterations_since_restore = 0
self._restored = False
self._trial_info = trial_info
self._stdout_file = stdout_file
self._stderr_file = stderr_file
start_time = time.time()
self.setup(copy.deepcopy(self.config))
setup_time = time.time() - start_time
if setup_time > SETUP_TIME_THRESHOLD:
logger.info("Trainable.setup took {:.3f} seconds. If your "
"trainable is slow to initialize, consider setting "
"reuse_actors=True to reduce actor creation "
"overheads.".format(setup_time))
self._local_ip = self.get_current_ip()
log_sys_usage = self.config.get("log_sys_usage", False)
self._monitor = UtilMonitor(start=log_sys_usage)
def __init__(
self,
config: Dict[str, Any] = None,
logger_creator: Callable[[Dict[str, Any]], Logger] = None,
remote_checkpoint_dir: Optional[str] = None,
sync_function_tpl: Optional[str] = None,
):
"""Initialize an Trainable.
Sets up logging and points ``self.logdir`` to a directory in which
training outputs should be placed.
Subclasses should prefer defining ``setup()`` instead of overriding
``__init__()`` directly.
Args:
config (dict): Trainable-specific configuration data. By default
will be saved as ``self.config``.
logger_creator (func): Function that creates a ray.tune.Logger
object. If unspecified, a default logger is created.
remote_checkpoint_dir (str): Upload directory (S3 or GS path).
This is **per trial** directory,
which is different from **per checkpoint** directory.
sync_function_tpl (str): Sync function template to use. Defaults
to `cls._sync_function` (which defaults to `None`).
"""
self._experiment_id = uuid.uuid4().hex
self.config = config or {}
trial_info = self.config.pop(TRIAL_INFO, None)
if self.is_actor():
disable_ipython()
self._result_logger = self._logdir = None
self._create_logger(self.config, logger_creator)
self._stdout_context = self._stdout_fp = self._stdout_stream = None
self._stderr_context = self._stderr_fp = self._stderr_stream = None
self._stderr_logging_handler = None
stdout_file = self.config.pop(STDOUT_FILE, None)
stderr_file = self.config.pop(STDERR_FILE, None)
self._open_logfiles(stdout_file, stderr_file)
self._iteration = 0
self._time_total = 0.0
self._timesteps_total = None
self._episodes_total = None
self._time_since_restore = 0.0
self._timesteps_since_restore = 0
self._iterations_since_restore = 0
self._restored = False
self._trial_info = trial_info
self._stdout_file = stdout_file
self._stderr_file = stderr_file
start_time = time.time()
self._local_ip = self.get_current_ip()
self.setup(copy.deepcopy(self.config))
setup_time = time.time() - start_time
if setup_time > SETUP_TIME_THRESHOLD:
logger.info("Trainable.setup took {:.3f} seconds. If your "
"trainable is slow to initialize, consider setting "
"reuse_actors=True to reduce actor creation "
"overheads.".format(setup_time))
log_sys_usage = self.config.get("log_sys_usage", False)
self._start_time = start_time
self._warmup_time = None
self._monitor = UtilMonitor(start=log_sys_usage)
self.remote_checkpoint_dir = remote_checkpoint_dir
self.sync_function_tpl = sync_function_tpl or self._sync_function_tpl
self.storage_client = None
if self.uses_cloud_checkpointing:
self.storage_client = self._create_storage_client()
