[tune] Introduce ability to turn off default logging.

doc/source/tune-usage.rst

@@ -415,15 +415,18 @@ You can pass in your own logging mechanisms to output logs in custom formats
 via the Experiment object as follows:
 
 .. code-block:: python
+    from ray.tune import DEFAULT_LOGGERS
 
     exp = Experiment(
         name="experiment_name",
         run=MyTrainableClass,
-        custom_loggers=[CustomLogger1, CustomLogger2]
+        loggers=DEFAULT_LOGGERS + (CustomLogger1, CustomLogger2)
     )
 
 These loggers will be called along with the default Tune loggers. All loggers must inherit the `Logger interface <tune-package-ref.html#ray.tune.logger.Logger>`__.
 
+Tune has default loggers for Tensorboard, CSV, and JSON formats.
+
 You can also check out `logger.py <https://github.com/ray-project/ray/blob/master/python/ray/tune/logger.py>`__ for implementation details.
 
 An example can be found in `logging_example.py <https://github.com/ray-project/ray/blob/master/python/ray/tune/examples/logging_example.py>`__.

python/ray/tune/__init__.py

@@ -4,6 +4,7 @@
 
 from ray.tune.error import TuneError
 from ray.tune.tune import run_experiments
+from ray.tune.logger import DEFAULT_LOGGERS
 from ray.tune.experiment import Experiment
 from ray.tune.registry import register_env, register_trainable
 from ray.tune.trainable import Trainable
@@ -19,4 +20,5 @@
     "Experiment",
     "function",
     "sample_from",
+    "DEFAULT_LOGGERS"
 ]

python/ray/tune/config_parser.py

@@ -12,7 +12,7 @@
 from ray.tune import TuneError
 from ray.tune.result import DEFAULT_RESULTS_DIR
 from ray.tune.trial import Trial, json_to_resources
-from ray.tune.logger import _SafeFallbackEncoder
+from ray.tune.logger import _SafeFallbackEncoder, DEFAULT_LOGGERS
 
 
 def make_parser(parser_creator=None, **kwargs):
@@ -88,9 +88,10 @@ def make_parser(parser_creator=None, **kwargs):
         "then it must be a string template for syncer to run and needs to "
         "include replacement fields '{local_dir}' and '{remote_dir}'.")
     parser.add_argument(
-        "--custom-loggers",
+        "--loggers",
         default=None,
-        help="List of custom logger creators to be used with each Trial.")
+        help="List of logger creators to be used with each Trial. "
+        "Defaults to ray.tune.loggers.DEFAULT_LOGGERS.")
     parser.add_argument(
         "--checkpoint-freq",
         default=0,
@@ -192,7 +193,7 @@ def create_trial_from_spec(spec, output_path, parser, **trial_kwargs):
         restore_path=spec.get("restore"),
         upload_dir=args.upload_dir,
         trial_name_creator=spec.get("trial_name_creator"),
-        custom_loggers=spec.get("custom_loggers"),
+        loggers=spec.get("loggers", DEFAULT_LOGGERS),
         # str(None) doesn't create None
         sync_function=spec.get("sync_function"),
         max_failures=args.max_failures,

python/ray/tune/examples/logging_example.py

@@ -66,7 +66,7 @@ def _restore(self, checkpoint_path):
         run=MyTrainableClass,
         num_samples=1,
         trial_name_creator=tune.function(trial_str_creator),
-        custom_loggers=[TestLogger],
+        loggers=[TestLogger],
         stop={"training_iteration": 1 if args.smoke_test else 99999},
         config={
             "width": tune.sample_from(

python/ray/tune/experiment.py

@@ -9,6 +9,7 @@
 import types
 
 from ray.tune.error import TuneError
+from ray.tune.logger import DEFAULT_LOGGERS
 from ray.tune.registry import register_trainable
 from ray.tune.result import DEFAULT_RESULTS_DIR
 
@@ -62,8 +63,9 @@ class Experiment(object):
             to (e.g. ``s3://bucket``).
         trial_name_creator (func): Optional function for generating
             the trial string representation.
-        custom_loggers (list): List of custom logger creators to be used with
-            each Trial. See `ray/tune/logger.py`.
+        loggers (list): List of logger creators to be used with
+            each Trial. Defaults to ray.tune.loggers.DEFAULT_LOGGERS.
+            See `ray/tune/logger.py`.
         sync_function (func|str): Function for syncing the local_dir to
             upload_dir. If string, then it must be a string template for
             syncer to run. If not provided, the sync command defaults
@@ -117,7 +119,7 @@ def __init__(self,
                  local_dir=None,
                  upload_dir=None,
                  trial_name_creator=None,
-                 custom_loggers=None,
+                 loggers=DEFAULT_LOGGERS,
                  sync_function=None,
                  checkpoint_freq=0,
                  checkpoint_at_end=False,
@@ -145,7 +147,7 @@ def __init__(self,
             "local_dir": os.path.expanduser(local_dir or DEFAULT_RESULTS_DIR),
             "upload_dir": upload_dir or "",  # argparse converts None to "null"
             "trial_name_creator": trial_name_creator,
-            "custom_loggers": custom_loggers,
+            "loggers": loggers,
             "sync_function": sync_function,
             "checkpoint_freq": checkpoint_freq,
             "checkpoint_at_end": checkpoint_at_end,

python/ray/tune/logger.py

@@ -66,81 +66,12 @@ def flush(self):
         pass
 
 
-class UnifiedLogger(Logger):
-    """Unified result logger for TensorBoard, rllab/viskit, plain json.
-
-    This class also periodically syncs output to the given upload uri.
-
-    Arguments:
-        config: Configuration passed to all logger creators.
-        logdir: Directory for all logger creators to log to.
-        upload_uri (str): Optional URI where the logdir is sync'ed to.
-        custom_loggers (list): List of custom logger creators.
-        sync_function (func|str): Optional function for syncer to run.
-            See ray/python/ray/tune/log_sync.py
-    """
-
-    def __init__(self,
-                 config,
-                 logdir,
-                 upload_uri=None,
-                 custom_loggers=None,
-                 sync_function=None):
-        self._logger_list = [_JsonLogger, _TFLogger, _CSVLogger]
-        self._sync_function = sync_function
-        self._log_syncer = None
-        if custom_loggers:
-            assert isinstance(custom_loggers, list), "Improper custom loggers."
-            self._logger_list += custom_loggers
-
-        Logger.__init__(self, config, logdir, upload_uri)
-
-    def _init(self):
-        self._loggers = []
-        for cls in self._logger_list:
-            try:
-                self._loggers.append(cls(self.config, self.logdir, self.uri))
-            except Exception:
-                logger.warning("Could not instantiate {} - skipping.".format(
-                    str(cls)))
-        self._log_syncer = get_syncer(
-            self.logdir, self.uri, sync_function=self._sync_function)
-
-    def on_result(self, result):
-        for _logger in self._loggers:
-            _logger.on_result(result)
-        self._log_syncer.set_worker_ip(result.get(NODE_IP))
-        self._log_syncer.sync_if_needed()
-
-    def close(self):
-        for _logger in self._loggers:
-            _logger.close()
-        self._log_syncer.sync_now(force=True)
-        self._log_syncer.close()
-
-    def flush(self):
-        for _logger in self._loggers:
-            _logger.flush()
-        self._log_syncer.sync_now(force=True)
-        self._log_syncer.wait()
-
-    def sync_results_to_new_location(self, worker_ip):
-        """Sends the current log directory to the remote node.
-
-        Syncing will not occur if the cluster is not started
-        with the Ray autoscaler.
-        """
-        if worker_ip != self._log_syncer.worker_ip:
-            self._log_syncer.set_worker_ip(worker_ip)
-            self._log_syncer.sync_to_worker_if_possible()
-
-
 class NoopLogger(Logger):
     def on_result(self, result):
         pass
 
 
-class _JsonLogger(Logger):
+class JsonLogger(Logger):
     def _init(self):
         config_out = os.path.join(self.logdir, "params.json")
         with open(config_out, "w") as f:
@@ -188,7 +119,7 @@ def to_tf_values(result, path):
     return values
 
 
-class _TFLogger(Logger):
+class TFLogger(Logger):
     def _init(self):
         self._file_writer = tf.summary.FileWriter(self.logdir)
 
@@ -217,7 +148,7 @@ def close(self):
         self._file_writer.close()
 
 
-class _CSVLogger(Logger):
+class CSVLogger(Logger):
     def _init(self):
         """CSV outputted with Headers as first set of results."""
         # Note that we assume params.json was already created by JsonLogger
@@ -242,6 +173,76 @@ def close(self):
         self._file.close()
 
 
+DEFAULT_LOGGERS = (JsonLogger, CSVLogger, TFLogger)
+
+
+class UnifiedLogger(Logger):
+    """Unified result logger for TensorBoard, rllab/viskit, plain json.
+
+    This class also periodically syncs output to the given upload uri.
+
+    Arguments:
+        config: Configuration passed to all logger creators.
+        logdir: Directory for all logger creators to log to.
+        upload_uri (str): Optional URI where the logdir is sync'ed to.
+        loggers (list): List of logger creators. Defaults to CSV, Tensorboard,
+            and JSON loggers.
+        sync_function (func|str): Optional function for syncer to run.
+            See ray/python/ray/tune/log_sync.py
+    """
+
+    def __init__(self,
+                 config,
+                 logdir,
+                 upload_uri=None,
+                 loggers=DEFAULT_LOGGERS,
+                 sync_function=None):
+        self._logger_cls_list = loggers
+        self._sync_function = sync_function
+        self._log_syncer = None
+
+        Logger.__init__(self, config, logdir, upload_uri)
+
+    def _init(self):
+        self._loggers = []
+        for cls in self._logger_cls_list:
+            try:
+                self._loggers.append(cls(self.config, self.logdir, self.uri))
+            except Exception:
+                logger.warning("Could not instantiate {} - skipping.".format(
+                    str(cls)))
+        self._log_syncer = get_syncer(
+            self.logdir, self.uri, sync_function=self._sync_function)
+
+    def on_result(self, result):
+        for _logger in self._loggers:
+            _logger.on_result(result)
+        self._log_syncer.set_worker_ip(result.get(NODE_IP))
+        self._log_syncer.sync_if_needed()
+
+    def close(self):
+        for _logger in self._loggers:
+            _logger.close()
+        self._log_syncer.sync_now(force=True)
+        self._log_syncer.close()
+
+    def flush(self):
+        for _logger in self._loggers:
+            _logger.flush()
+        self._log_syncer.sync_now(force=True)
+        self._log_syncer.wait()
+
+    def sync_results_to_new_location(self, worker_ip):
+        """Sends the current log directory to the remote node.
+
+        Syncing will not occur if the cluster is not started
+        with the Ray autoscaler.
+        """
+        if worker_ip != self._log_syncer.worker_ip:
+            self._log_syncer.set_worker_ip(worker_ip)
+            self._log_syncer.sync_to_worker_if_possible()
+
+
 class _SafeFallbackEncoder(json.JSONEncoder):
     def __init__(self, nan_str="null", **kwargs):
         super(_SafeFallbackEncoder, self).__init__(**kwargs)

python/ray/tune/test/trial_runner_test.py

@@ -793,10 +793,12 @@ def on_result(self, result):
                 "stop": {
                     "training_iteration": 1
                 },
-                "custom_loggers": [CustomLogger]
+                "loggers": [CustomLogger]
             }
         })
         self.assertTrue(os.path.exists(os.path.join(trial.logdir, "test.log")))
+        self.assertFalse(
+            os.path.exists(os.path.join(trial.logdir, "params.json")))
 
     def testCustomTrialString(self):
         [trial] = run_experiments({

python/ray/tune/trial.py

@@ -19,7 +19,7 @@
 import ray
 from ray.tune import TuneError
 from ray.tune.log_sync import validate_sync_function
-from ray.tune.logger import pretty_print, UnifiedLogger
+from ray.tune.logger import pretty_print, UnifiedLogger, DEFAULT_LOGGERS
 # NOTE(rkn): We import ray.tune.registry here instead of importing the names we
 # need because there are cyclic imports that may cause specific names to not
 # have been defined yet. See https://github.com/ray-project/ray/issues/1716.
@@ -256,7 +256,7 @@ def __init__(self,
                  restore_path=None,
                  upload_dir=None,
                  trial_name_creator=None,
-                 custom_loggers=None,
+                 loggers=DEFAULT_LOGGERS,
                  sync_function=None,
                  max_failures=0):
         """Initialize a new trial.
@@ -276,7 +276,7 @@ def __init__(self,
             or self._get_trainable_cls().default_resource_request(self.config))
         self.stopping_criterion = stopping_criterion or {}
         self.upload_dir = upload_dir
-        self.custom_loggers = custom_loggers
+        self.loggers = loggers
         self.sync_function = sync_function
         validate_sync_function(sync_function)
         self.verbose = True
@@ -333,7 +333,7 @@ def init_logger(self):
                 self.config,
                 self.logdir,
                 upload_uri=self.upload_dir,
-                custom_loggers=self.custom_loggers,
+                loggers=self.loggers,
                 sync_function=self.sync_function)
 
     def sync_logger_to_new_location(self, worker_ip):
@@ -509,10 +509,11 @@ def __getstate__(self):
         state = self.__dict__.copy()
         state["resources"] = resources_to_json(self.resources)
 
+        # These are non-pickleable entries.
         pickle_data = {
             "_checkpoint": self._checkpoint,
             "config": self.config,
-            "custom_loggers": self.custom_loggers,
+            "loggers": self.loggers,
             "sync_function": self.sync_function,
             "last_result": self.last_result
         }
@@ -535,7 +536,7 @@ def __setstate__(self, state):
         logger_started = state.pop("__logger_started__")
         state["resources"] = json_to_resources(state["resources"])
         for key in [
-                "_checkpoint", "config", "custom_loggers", "sync_function",
+                "_checkpoint", "config", "loggers", "sync_function",
                 "last_result"
         ]:
             state[key] = cloudpickle.loads(hex_to_binary(state[key]))