Revert "Simplify logging configuration. (#30863)" (#31858)

This reverts commit 608276b.

Looks like this breaks the backward compatibility of rllib (it is supposed to print warn first, but it prints the info log).

python/ray/_private/runtime_env/_clonevirtualenv.py

@@ -15,7 +15,7 @@
 __version__ = "0.5.7"
 
 
-logger = logging.getLogger(__name__)
+logger = logging.getLogger()
 
 
 env_bin_dir = "bin"

python/ray/autoscaler/_private/kuberay/run_autoscaler.py

@@ -17,21 +17,7 @@
 
 
 def run_kuberay_autoscaler(cluster_name: str, cluster_namespace: str):
-    """Wait until the Ray head container is ready. Then start the autoscaler.
-
-    For kuberay's autoscaler integration, the autoscaler runs in a sidecar container
-    in the same pod as the main Ray container, which runs the rest of the Ray
-    processes.
-
-    The logging configuration here is for the sidecar container, but we need the
-    logs to go to the same place as the head node logs because the autoscaler is
-    allowed to send scaling events to Ray drivers' stdout. The implementation of
-    this feature involves the autoscaler communicating to another Ray process
-    (the log monitor) via logs in that directory.
-
-    However, the Ray head container sets up the log directory. Thus, we set up
-    logging only after the Ray head is ready.
-    """
+    """Wait until the Ray head container is ready. Then start the autoscaler."""
     head_ip = get_node_ip_address()
     ray_address = f"{head_ip}:6379"
     while True:
@@ -55,6 +41,8 @@ def run_kuberay_autoscaler(cluster_name: str, cluster_namespace: str):
             print(f"Will check again in {BACKOFF_S} seconds.")
             time.sleep(BACKOFF_S)
 
+    # The Ray head container sets up the log directory. Thus, we set up logging
+    # only after the Ray head is ready.
     _setup_logging()
 
     # autoscaling_config_producer reads the RayCluster CR from K8s and uses the CR

python/ray/autoscaler/_private/local/node_provider.py

@@ -25,7 +25,8 @@
 
 logger = logging.getLogger(__name__)
 
-logging.getLogger("filelock").setLevel(logging.WARNING)
+filelock_logger = logging.getLogger("filelock")
+filelock_logger.setLevel(logging.WARNING)
 
 
 class ClusterState:

python/ray/experimental/raysort/main.py

@@ -447,6 +447,7 @@ def init(args: Args):
         ray.init(resources={"worker": os.cpu_count()})
     else:
         ray.init(address=args.ray_address)
+    logging_utils.init()
     logging.info(args)
     os.makedirs(constants.WORK_DIR, exist_ok=True)
     resources = ray.cluster_resources()

python/ray/tests/kuberay/utils.py

@@ -33,18 +33,6 @@
 
 
 def setup_logging():
-    """Set up logging for kuberay.
-
-    For kuberay's autoscaler integration, the autoscaler runs in a sidecar container
-    in the same pod as the main Ray container, which runs the rest of the Ray
-    processes.
-
-    The logging configuration here is for the sidecar container, but we need the
-    logs to go to the same place as the head node logs because the autoscaler is
-    allowed to send scaling events to Ray drivers' stdout. The implementation of
-    this feature involves the autoscaler communicating to another Ray process
-    (the log monitor) via logs in that directory.
-    """
     logging.basicConfig(
         level=logging.INFO,
         format=LOG_FORMAT,

python/ray/util/client/server/logservicer.py

@@ -54,9 +54,6 @@ def unregister_global(self):
 
 
 def log_status_change_thread(log_queue, request_iterator):
-    """This is run in a separate thread and therefore needs a separate logging
-    configuration outside of the default ray logging configuration.
-    """
     std_handler = StdStreamHandler(log_queue)
     current_handler = None
     root_logger = logging.getLogger("ray")

release/ray_release/logger.py

@@ -1,7 +1,7 @@
 import logging
 import sys
 
-logger = logging.getLogger(__name__)
+logger = logging.getLogger()
 logger.setLevel(logging.INFO)
 
 

rllib/__init__.py

@@ -1,3 +1,5 @@
+import logging
+
 from ray._private.usage import usage_lib
 
 # Note: do not introduce unnecessary library dependencies here, e.g. gym.
@@ -14,6 +16,18 @@
 from ray.tune.registry import register_trainable
 
 
+def _setup_logger():
+    logger = logging.getLogger("ray.rllib")
+    handler = logging.StreamHandler()
+    handler.setFormatter(
+        logging.Formatter(
+            "%(asctime)s\t%(levelname)s %(filename)s:%(lineno)s -- %(message)s"
+        )
+    )
+    logger.addHandler(handler)
+    logger.propagate = False
+
+
 def _register_all():
     from ray.rllib.algorithms.registry import ALGORITHMS, _get_algorithm_class
 
@@ -24,6 +38,8 @@ def _register_all():
         register_trainable(key, _get_algorithm_class(key))
 
 
+_setup_logger()
+
 usage_lib.record_library_usage("rllib")
 
 __all__ = [

rllib/algorithms/algorithm.py

@@ -494,6 +494,15 @@ def setup(self, config: AlgorithmConfig) -> None:
         self._record_usage(self.config)
 
         self.callbacks = self.config["callbacks"]()
+        log_level = self.config.get("log_level")
+        if log_level in ["WARN", "ERROR"]:
+            logger.info(
+                "Current log_level is {}. For more information, "
+                "set 'log_level': 'INFO' / 'DEBUG' or use the -v and "
+                "-vv flags.".format(log_level)
+            )
+        if self.config.get("log_level"):
+            logging.getLogger("ray.rllib").setLevel(self.config["log_level"])
 
         # Create local replay buffer if necessary.
         self.local_replay_buffer = self._create_local_replay_buffer_if_necessary(

rllib/algorithms/algorithm_config.py

@@ -385,7 +385,7 @@ def __init__(self, algo_class=None):
         # `self.debugging()`
         self.logger_creator = None
         self.logger_config = None
-        self.log_level = DEPRECATED_VALUE
+        self.log_level = "WARN"
         self.log_sys_usage = True
         self.fake_sampler = False
         self.seed = None
@@ -2052,7 +2052,7 @@ def debugging(
         *,
         logger_creator: Optional[Callable[[], Logger]] = NotProvided,
         logger_config: Optional[dict] = NotProvided,
-        log_level: Optional[str] = DEPRECATED_VALUE,
+        log_level: Optional[str] = NotProvided,
         log_sys_usage: Optional[bool] = NotProvided,
         fake_sampler: Optional[bool] = NotProvided,
         seed: Optional[int] = NotProvided,
@@ -2086,16 +2086,8 @@ def debugging(
             self.logger_creator = logger_creator
         if logger_config is not NotProvided:
             self.logger_config = logger_config
-        if log_level != DEPRECATED_VALUE:
-            deprecation_warning(
-                old="config.log_level",
-                help=(
-                    "RLlib no longer has a separate logging configuration from the rest"
-                    " of Ray. Configure logging on the root logger; RLlib messages "
-                    "will be propagated up the logger hierarchy to be handled there."
-                ),
-                error=False,
-            )
+        if log_level is not NotProvided:
+            self.log_level = log_level
         if log_sys_usage is not NotProvided:
             self.log_sys_usage = log_sys_usage
         if fake_sampler is not NotProvided:

rllib/evaluation/rollout_worker.py

@@ -521,6 +521,9 @@ def gen_rollouts():
         ):
             tf1.enable_eager_execution()
 
+        if self.config.log_level:
+            logging.getLogger("ray.rllib").setLevel(self.config.log_level)
+
         if self.worker_index > 1:
             disable_log_once_globally()  # only need 1 worker to log
         elif self.config.log_level == "DEBUG":

rllib/examples/simulators/sumo/connector.py

@@ -20,6 +20,7 @@
 
 ###############################################################################
 
+logging.basicConfig()
 logger = logging.getLogger(__name__)
 
 ###############################################################################

rllib/examples/simulators/sumo/utils.py

@@ -29,6 +29,7 @@
 
 ###############################################################################
 
+logging.basicConfig()
 logger = logging.getLogger(__name__)
 
 ###############################################################################

rllib/examples/sumo_env_local.py

@@ -23,7 +23,8 @@
 from ray.rllib.examples.simulators.sumo import marlenvironment
 from ray.rllib.utils.test_utils import check_learning_achieved
 
-logger = logging.getLogger(__name__)
+logging.basicConfig(level=logging.WARN)
+logger = logging.getLogger("ppotrain")
 
 parser = argparse.ArgumentParser()
 parser.add_argument(

rllib/examples/tune/framework.py

@@ -10,7 +10,8 @@
 from ray.rllib.algorithms.appo import APPOConfig
 from ray.tune import CLIReporter
 
-logger = logging.getLogger(__name__)
+logging.basicConfig(level=logging.WARN)
+logger = logging.getLogger("tune_framework")
 
 
 def run(smoke_test=False):