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[tune] Clean up result logging: move out of /tmp, add timestamp (#1297)
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@@ -18,7 +18,7 @@ import uuid
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import tensorflow as tf
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from ray.tune.logger import UnifiedLogger
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from ray.tune.registry import ENV_CREATOR
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from ray.tune.result import TrainingResult
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from ray.tune.result import DEFAULT_RESULTS_DIR, TrainingResult
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from ray.tune.trainable import Trainable
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logger = logging.getLogger(__name__)
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@@ -72,7 +72,6 @@ class Agent(Trainable):
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_allow_unknown_configs = False
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_allow_unknown_subkeys = []
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_default_logdir = "/tmp/ray"
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def __init__(
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self, config={}, env=None, registry=None, logger_creator=None):
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@@ -111,10 +110,10 @@ class Agent(Trainable):
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logdir_suffix = "{}_{}_{}".format(
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env, self._agent_name,
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datetime.today().strftime("%Y-%m-%d_%H-%M-%S"))
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if not os.path.exists(self._default_logdir):
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os.makedirs(self._default_logdir)
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if not os.path.exists(DEFAULT_RESULTS_DIR):
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os.makedirs(DEFAULT_RESULTS_DIR)
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self.logdir = tempfile.mkdtemp(
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prefix=logdir_suffix, dir=self._default_logdir)
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prefix=logdir_suffix, dir=DEFAULT_RESULTS_DIR)
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self._result_logger = UnifiedLogger(self.config, self.logdir, None)
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self._iteration = 0
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@@ -155,8 +154,11 @@ class Agent(Trainable):
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self._time_total += time_this_iter
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self._timesteps_total += result.timesteps_this_iter
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now = datetime.today()
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result = result._replace(
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experiment_id=self._experiment_id,
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date=now.strftime("%Y-%m-%d_%H-%M-%S"),
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timestamp=int(time.mktime(now.timetuple())),
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training_iteration=self._iteration,
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timesteps_total=self._timesteps_total,
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time_this_iter_s=time_this_iter,
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@@ -57,7 +57,7 @@ if __name__ == "__main__":
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else:
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# Note: keep this in sync with tune/config_parser.py
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experiments = {
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args.experiment_name: { # i.e. log to /tmp/ray/default
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args.experiment_name: { # i.e. log to ~/ray_results/default
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"run": args.run,
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"checkpoint_freq": args.checkpoint_freq,
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"local_dir": args.local_dir,
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