def __init__(self,
search_alg=None,
scheduler=None,
local_checkpoint_dir=None,
remote_checkpoint_dir=None,
sync_to_cloud=None,
stopper=None,
resume=False,
server_port=None,
fail_fast=False,
checkpoint_period=None,
trial_executor=None,
callbacks=None,
metric=None):
self._search_alg = search_alg or BasicVariantGenerator()
self._scheduler_alg = scheduler or FIFOScheduler()
self.trial_executor = trial_executor or RayTrialExecutor()
self._pending_trial_queue_times = {}
# Setting this to 0 still allows adding one new (pending) trial,
# but it will prevent us from trying to fill the trial list
self._max_pending_trials = 0 # Can be updated in `self.add_trial()`
self._metric = metric
if "TRIALRUNNER_WALLTIME_LIMIT" in os.environ:
raise ValueError(
"The TRIALRUNNER_WALLTIME_LIMIT environment variable is "
"deprecated. "
"Use `tune.run(time_budget_s=limit)` instead.")
self._total_time = 0
self._iteration = 0
self._has_errored = False
self._fail_fast = fail_fast
if isinstance(self._fail_fast, str):
self._fail_fast = self._fail_fast.upper()
if self._fail_fast == TrialRunner.RAISE:
warnings.warn(
"fail_fast='raise' detected. Be careful when using this "
"mode as resources (such as Ray processes, "
"file descriptors, and temporary files) may not be "
"cleaned up properly. To use "
"a safer mode, use fail_fast=True.")
else:
raise ValueError("fail_fast must be one of {bool, RAISE}. "
f"Got {self._fail_fast}.")
self._server = None
self._server_port = server_port
if server_port is not None:
self._server = TuneServer(self, self._server_port)
self._trials = []
self._cached_trial_decisions = {}
self._queued_trial_decisions = {}
self._updated_queue = False
self._stop_queue = []
self._should_stop_experiment = False # used by TuneServer
self._local_checkpoint_dir = local_checkpoint_dir
if self._local_checkpoint_dir:
os.makedirs(self._local_checkpoint_dir, exist_ok=True)
self._remote_checkpoint_dir = remote_checkpoint_dir
self._syncer = get_cloud_syncer(local_checkpoint_dir,
remote_checkpoint_dir, sync_to_cloud)
self._stopper = stopper or NoopStopper()
self._resumed = False
if self._validate_resume(resume_type=resume):
errored_only = False
if isinstance(resume, str):
errored_only = resume.upper() == "ERRORED_ONLY"
try:
self.resume(run_errored_only=errored_only)
self._resumed = True
except Exception as e:
if has_verbosity(Verbosity.V3_TRIAL_DETAILS):
logger.error(str(e))
logger.exception("Runner restore failed.")
if self._fail_fast:
raise
logger.info("Restarting experiment.")
else:
logger.debug("Starting a new experiment.")
self._start_time = time.time()
self._last_checkpoint_time = -float("inf")
self._session_str = datetime.fromtimestamp(
self._start_time).strftime("%Y-%m-%d_%H-%M-%S")
self.checkpoint_file = None
if self._local_checkpoint_dir:
self.checkpoint_file = os.path.join(
self._local_checkpoint_dir,
TrialRunner.CKPT_FILE_TMPL.format(self._session_str))
self._callbacks = CallbackList(callbacks or [])
self._callbacks.setup()
if checkpoint_period is None:
checkpoint_period = os.getenv("TUNE_GLOBAL_CHECKPOINT_S", "auto")
self._checkpoint_period = checkpoint_period
self._checkpoint_manager = self._create_checkpoint_manager()
def __init__(self,
search_alg=None,
scheduler=None,
local_checkpoint_dir=None,
remote_checkpoint_dir=None,
sync_to_cloud=None,
stopper=None,
resume=False,
server_port=None,
fail_fast=False,
verbose=True,
checkpoint_period=None,
trial_executor=None):
self._search_alg = search_alg or BasicVariantGenerator()
self._scheduler_alg = scheduler or FIFOScheduler()
self.trial_executor = trial_executor or RayTrialExecutor()
# For debugging, it may be useful to halt trials after some time has
# elapsed. TODO(ekl) consider exposing this in the API.
self._global_time_limit = float(
os.environ.get("TRIALRUNNER_WALLTIME_LIMIT", float("inf")))
self._total_time = 0
self._iteration = 0
self._has_errored = False
self._fail_fast = fail_fast
if isinstance(self._fail_fast, str):
self._fail_fast = self._fail_fast.upper()
if self._fail_fast == TrialRunner.RAISE:
logger.warning(
"fail_fast='raise' detected. Be careful when using this "
"mode as resources (such as Ray processes, "
"file descriptors, and temporary files) may not be "
"cleaned up properly. To use "
"a safer mode, use fail_fast=True.")
else:
raise ValueError("fail_fast must be one of {bool, RAISE}. "
f"Got {self._fail_fast}.")
self._verbose = verbose
self._server = None
self._server_port = server_port
if server_port is not None:
self._server = TuneServer(self, self._server_port)
self._trials = []
self._cached_trial_decisions = {}
self._stop_queue = []
self._should_stop_experiment = False # used by TuneServer
self._local_checkpoint_dir = local_checkpoint_dir
if self._local_checkpoint_dir:
os.makedirs(self._local_checkpoint_dir, exist_ok=True)
self._remote_checkpoint_dir = remote_checkpoint_dir
self._syncer = get_cloud_syncer(local_checkpoint_dir,
remote_checkpoint_dir, sync_to_cloud)
self._stopper = stopper or NoopStopper()
self._resumed = False
if self._validate_resume(resume_type=resume):
errored_only = False
if isinstance(resume, str):
errored_only = resume.upper() == "ERRORED_ONLY"
try:
self.resume(run_errored_only=errored_only)
self._resumed = True
except Exception as e:
if self._verbose:
logger.error(str(e))
logger.exception("Runner restore failed.")
if self._fail_fast:
raise
logger.info("Restarting experiment.")
else:
logger.debug("Starting a new experiment.")
self._start_time = time.time()
self._last_checkpoint_time = -float("inf")
if checkpoint_period is None:
checkpoint_period = env_integer("TUNE_GLOBAL_CHECKPOINT_S", 10)
self._checkpoint_period = checkpoint_period
self._session_str = datetime.fromtimestamp(
self._start_time).strftime("%Y-%m-%d_%H-%M-%S")
self.checkpoint_file = None
if self._local_checkpoint_dir:
self.checkpoint_file = os.path.join(
self._local_checkpoint_dir,
TrialRunner.CKPT_FILE_TMPL.format(self._session_str))
def __init__(self,
search_alg=None,
scheduler=None,
launch_web_server=False,
local_checkpoint_dir=None,
remote_checkpoint_dir=None,
sync_to_cloud=None,
stopper=None,
resume=False,
server_port=TuneServer.DEFAULT_PORT,
fail_fast=False,
verbose=True,
checkpoint_period=10,
trial_executor=None):
self._search_alg = search_alg or BasicVariantGenerator()
self._scheduler_alg = scheduler or FIFOScheduler()
self.trial_executor = trial_executor or RayTrialExecutor()
# For debugging, it may be useful to halt trials after some time has
# elapsed. TODO(ekl) consider exposing this in the API.
self._global_time_limit = float(
os.environ.get("TRIALRUNNER_WALLTIME_LIMIT", float("inf")))
self._total_time = 0
self._iteration = 0
self._has_errored = False
self._fail_fast = fail_fast
self._verbose = verbose
self._server = None
self._server_port = server_port
if launch_web_server:
self._server = TuneServer(self, self._server_port)
self._trials = []
self._cached_trial_decisions = {}
self._stop_queue = []
self._should_stop_experiment = False # used by TuneServer
self._local_checkpoint_dir = local_checkpoint_dir
if self._local_checkpoint_dir:
os.makedirs(self._local_checkpoint_dir, exist_ok=True)
self._remote_checkpoint_dir = remote_checkpoint_dir
self._syncer = get_cloud_syncer(local_checkpoint_dir,
remote_checkpoint_dir, sync_to_cloud)
self._stopper = stopper or NoopStopper()
self._resumed = False
if self._validate_resume(resume_type=resume):
try:
self.resume()
logger.info("Resuming trial.")
self._resumed = True
except Exception:
logger.exception(
"Runner restore failed. Restarting experiment.")
else:
logger.debug("Starting a new experiment.")
self._start_time = time.time()
self._last_checkpoint_time = -float("inf")
self._checkpoint_period = checkpoint_period
self._session_str = datetime.fromtimestamp(
self._start_time).strftime("%Y-%m-%d_%H-%M-%S")
self.checkpoint_file = None
if self._local_checkpoint_dir:
self.checkpoint_file = os.path.join(
self._local_checkpoint_dir,
TrialRunner.CKPT_FILE_TMPL.format(self._session_str))
def __init__(self,
search_alg=None,
scheduler=None,
launch_web_server=False,
local_checkpoint_dir=None,
remote_checkpoint_dir=None,
sync_to_cloud=None,
stopper=None,
resume=False,
server_port=TuneServer.DEFAULT_PORT,
verbose=True,
checkpoint_period=10,
trial_executor=None):
"""Initializes a new TrialRunner.
Args:
search_alg (SearchAlgorithm): SearchAlgorithm for generating
Trial objects.
scheduler (TrialScheduler): Defaults to FIFOScheduler.
launch_web_server (bool): Flag for starting TuneServer
local_checkpoint_dir (str): Path where
global checkpoints are stored and restored from.
remote_checkpoint_dir (str): Remote path where
global checkpoints are stored and restored from. Used
if `resume` == REMOTE.
stopper: Custom class for stopping whole experiments. See
``Stopper``.
resume (str|False): see `tune.py:run`.
sync_to_cloud (func|str): See `tune.py:run`.
server_port (int): Port number for launching TuneServer.
verbose (bool): Flag for verbosity. If False, trial results
will not be output.
trial_executor (TrialExecutor): Defaults to RayTrialExecutor.
"""
self._search_alg = search_alg or BasicVariantGenerator()
self._scheduler_alg = scheduler or FIFOScheduler()
self.trial_executor = trial_executor or RayTrialExecutor()
# For debugging, it may be useful to halt trials after some time has
# elapsed. TODO(ekl) consider exposing this in the API.
self._global_time_limit = float(
os.environ.get("TRIALRUNNER_WALLTIME_LIMIT", float("inf")))
self._total_time = 0
self._iteration = 0
self._verbose = verbose
self._server = None
self._server_port = server_port
if launch_web_server:
self._server = TuneServer(self, self._server_port)
self._trials = []
self._stop_queue = []
self._local_checkpoint_dir = local_checkpoint_dir
if self._local_checkpoint_dir:
os.makedirs(self._local_checkpoint_dir, exist_ok=True)
self._remote_checkpoint_dir = remote_checkpoint_dir
self._syncer = get_cloud_syncer(local_checkpoint_dir,
remote_checkpoint_dir, sync_to_cloud)
self._stopper = stopper or NoopStopper()
self._resumed = False
if self._validate_resume(resume_type=resume):
try:
self.resume()
logger.info("Resuming trial.")
self._resumed = True
except Exception:
logger.exception(
"Runner restore failed. Restarting experiment.")
else:
logger.debug("Starting a new experiment.")
self._start_time = time.time()
self._last_checkpoint_time = -float("inf")
self._checkpoint_period = checkpoint_period
self._session_str = datetime.fromtimestamp(
self._start_time).strftime("%Y-%m-%d_%H-%M-%S")
self.checkpoint_file = None
if self._local_checkpoint_dir:
self.checkpoint_file = os.path.join(
self._local_checkpoint_dir,
TrialRunner.CKPT_FILE_TMPL.format(self._session_str))