[Misc][DP] support customized aggregated logger for dp (#24354)

Signed-off-by: Lu Fang <fanglu@fb.com>

examples/online_serving/multi_instance_data_parallel.py

@@ -1,11 +1,13 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 import asyncio
+import threading
 
 from vllm.engine.arg_utils import AsyncEngineArgs
 from vllm.engine.async_llm_engine import AsyncLLMEngine
 from vllm.outputs import RequestOutput
 from vllm.sampling_params import SamplingParams
+from vllm.v1.metrics.loggers import AggregatedLoggingStatLogger
 
 """
 To run this example, run the following commands simultaneously with
@@ -21,37 +23,64 @@ send a request to the instance with DP rank 1.
 """
 
 
+def _do_background_logging(engine, interval, stop_event):
+    try:
+        while not stop_event.is_set():
+            asyncio.run(engine.do_log_stats())
+            stop_event.wait(interval)
+    except Exception as e:
+        print(f"vLLM background logging shutdown: {e}")
+        pass
+
+
 async def main():
     engine_args = AsyncEngineArgs(
         model="ibm-research/PowerMoE-3b",
         data_parallel_size=2,
+        tensor_parallel_size=1,
         dtype="auto",
         max_model_len=2048,
         data_parallel_address="127.0.0.1",
         data_parallel_rpc_port=62300,
         data_parallel_size_local=1,
         enforce_eager=True,
+        enable_log_requests=True,
+        disable_custom_all_reduce=True,
     )
 
-    engine_client = AsyncLLMEngine.from_engine_args(engine_args)
+    engine_client = AsyncLLMEngine.from_engine_args(
-
+        engine_args,
+        # Example: Using aggregated logger
+        stat_loggers=[AggregatedLoggingStatLogger],
+    )
+    stop_logging_event = threading.Event()
+    logging_thread = threading.Thread(
+        target=_do_background_logging,
+        args=(engine_client, 5, stop_logging_event),
+        daemon=True,
+    )
+    logging_thread.start()
     sampling_params = SamplingParams(
         temperature=0.7,
         top_p=0.9,
         max_tokens=100,
     )
+    num_prompts = 10
+    for i in range(num_prompts):
+        prompt = "Who won the 2004 World Series?"
+        final_output: RequestOutput | None = None
+        async for output in engine_client.generate(
+            prompt=prompt,
+            sampling_params=sampling_params,
+            request_id=f"abcdef-{i}",
+            data_parallel_rank=1,
+        ):
+            final_output = output
+        if final_output:
+            print(final_output.outputs[0].text)
 
-    prompt = "Who won the 2004 World Series?"
+    stop_logging_event.set()
-    final_output: RequestOutput | None = None
+    logging_thread.join()
-    async for output in engine_client.generate(
-        prompt=prompt,
-        sampling_params=sampling_params,
-        request_id="abcdef",
-        data_parallel_rank=1,
-    ):
-        final_output = output
-    if final_output:
-        print(final_output.outputs[0].text)
 
 
 if __name__ == "__main__":

tests/v1/engine/test_async_llm.py

@@ -17,7 +17,12 @@ from vllm.platforms import current_platform
 from vllm.sampling_params import RequestOutputKind
 from vllm.utils import set_default_torch_num_threads
 from vllm.v1.engine.async_llm import AsyncLLM
-from vllm.v1.metrics.loggers import LoggingStatLogger
+from vllm.v1.metrics.loggers import (
+    AggregatedLoggingStatLogger,
+    LoggingStatLogger,
+    PerEngineStatLoggerAdapter,
+    PrometheusStatLogger,
+)
 
 if not current_platform.is_cuda():
     pytest.skip(reason="V1 currently only supported on CUDA.", allow_module_level=True)
@@ -384,6 +389,12 @@ class MockLoggingStatLogger(LoggingStatLogger):
         self.log = MagicMock()
 
 
+class MockAggregatedStatLogger(AggregatedLoggingStatLogger):
+    def __init__(self, vllm_config: VllmConfig, engine_indexes: list[int]):
+        super().__init__(vllm_config, engine_indexes)
+        self.log = MagicMock()
+
+
 @pytest.mark.asyncio
 async def test_customize_loggers(monkeypatch):
     """Test that we can customize the loggers.
@@ -401,10 +412,45 @@ async def test_customize_loggers(monkeypatch):
 
         await engine.do_log_stats()
 
-        stat_loggers = engine.logger_manager.per_engine_logger_dict
+        stat_loggers = engine.logger_manager.stat_loggers
-        assert len(stat_loggers) == 1
+        assert (
-        assert len(stat_loggers[0]) == 2  # LoggingStatLogger + MockLoggingStatLogger
+            len(stat_loggers) == 3
-        stat_loggers[0][0].log.assert_called_once()
+        )  # MockLoggingStatLogger + LoggingStatLogger +  Promethus Logger
+        print(f"{stat_loggers=}")
+        stat_loggers[0].per_engine_stat_loggers[0].log.assert_called_once()
+        assert isinstance(stat_loggers[1], PerEngineStatLoggerAdapter)
+        assert isinstance(stat_loggers[1].per_engine_stat_loggers[0], LoggingStatLogger)
+        assert isinstance(stat_loggers[2], PrometheusStatLogger)
+
+
+@pytest.mark.asyncio
+async def test_customize_aggregated_loggers(monkeypatch):
+    """Test that we can customize the aggregated loggers.
+    If a customized logger is provided at the init, it should
+    be added to the default loggers.
+    """
+
+    with monkeypatch.context() as m, ExitStack() as after:
+        m.setenv("VLLM_USE_V1", "1")
+
+        with set_default_torch_num_threads(1):
+            engine = AsyncLLM.from_engine_args(
+                TEXT_ENGINE_ARGS,
+                stat_loggers=[MockLoggingStatLogger, MockAggregatedStatLogger],
+            )
+        after.callback(engine.shutdown)
+
+        await engine.do_log_stats()
+
+        stat_loggers = engine.logger_manager.stat_loggers
+        assert len(stat_loggers) == 4
+        #  MockLoggingStatLogger + MockAggregatedStatLogger
+        # + LoggingStatLogger + PrometheusStatLogger
+        stat_loggers[0].per_engine_stat_loggers[0].log.assert_called_once()
+        stat_loggers[1].log.assert_called_once()
+        assert isinstance(stat_loggers[2], PerEngineStatLoggerAdapter)
+        assert isinstance(stat_loggers[2].per_engine_stat_loggers[0], LoggingStatLogger)
+        assert isinstance(stat_loggers[3], PrometheusStatLogger)
 
 
 @pytest.mark.asyncio(scope="module")

tests/v1/metrics/test_engine_logger_apis.py

@@ -54,7 +54,7 @@ async def test_async_llm_replace_default_loggers(log_stats_enabled_engine_args):
     engine = AsyncLLM.from_engine_args(
         log_stats_enabled_engine_args, stat_loggers=[RayPrometheusStatLogger]
     )
-    assert isinstance(engine.logger_manager.prometheus_logger, RayPrometheusStatLogger)
+    assert isinstance(engine.logger_manager.stat_loggers[0], RayPrometheusStatLogger)
     engine.shutdown()
 
 
@@ -73,9 +73,11 @@ async def test_async_llm_add_to_default_loggers(log_stats_enabled_engine_args):
         disabled_log_engine_args, stat_loggers=[DummyStatLogger]
     )
 
-    assert len(engine.logger_manager.per_engine_logger_dict[0]) == 1
+    assert len(engine.logger_manager.stat_loggers) == 2
+    assert len(engine.logger_manager.stat_loggers[0].per_engine_stat_loggers) == 1
     assert isinstance(
-        engine.logger_manager.per_engine_logger_dict[0][0], DummyStatLogger
+        engine.logger_manager.stat_loggers[0].per_engine_stat_loggers[0],
+        DummyStatLogger,
     )
 
     # log_stats is still True, since custom stat loggers are used

vllm/engine/arg_utils.py

@@ -410,6 +410,7 @@ class EngineArgs:
     max_logprobs: int = ModelConfig.max_logprobs
     logprobs_mode: LogprobsMode = ModelConfig.logprobs_mode
     disable_log_stats: bool = False
+    aggregate_engine_logging: bool = False
     revision: str | None = ModelConfig.revision
     code_revision: str | None = ModelConfig.code_revision
     rope_scaling: dict[str, Any] = get_field(ModelConfig, "rope_scaling")
@@ -1043,6 +1044,12 @@ class EngineArgs:
             help="Disable logging statistics.",
         )
 
+        parser.add_argument(
+            "--aggregate-engine-logging",
+            action="store_true",
+            help="Log aggregate rather than per-engine statistics "
+            "when using data parallelism.",
+        )
         return parser
 
     @classmethod

vllm/entrypoints/openai/api_server.py

@@ -239,6 +239,7 @@ async def build_async_engine_client_from_engine_args(
             vllm_config=vllm_config,
             usage_context=usage_context,
             enable_log_requests=engine_args.enable_log_requests,
+            aggregate_engine_logging=engine_args.aggregate_engine_logging,
             disable_log_stats=engine_args.disable_log_stats,
             client_addresses=client_config,
             client_count=client_count,

vllm/v1/engine/async_llm.py

@@ -57,6 +57,7 @@ class AsyncLLM(EngineClient):
         log_requests: bool = True,
         start_engine_loop: bool = True,
         stat_loggers: list[StatLoggerFactory] | None = None,
+        aggregate_engine_logging: bool = False,
         client_addresses: dict[str, str] | None = None,
         client_count: int = 1,
         client_index: int = 0,
@@ -144,6 +145,7 @@ class AsyncLLM(EngineClient):
                 custom_stat_loggers=stat_loggers,
                 enable_default_loggers=log_stats,
                 client_count=client_count,
+                aggregate_engine_logging=aggregate_engine_logging,
             )
             self.logger_manager.log_engine_initialized()
 
@@ -187,6 +189,7 @@ class AsyncLLM(EngineClient):
         usage_context: UsageContext = UsageContext.ENGINE_CONTEXT,
         stat_loggers: list[StatLoggerFactory] | None = None,
         enable_log_requests: bool = False,
+        aggregate_engine_logging: bool = False,
         disable_log_stats: bool = False,
         client_addresses: dict[str, str] | None = None,
         client_count: int = 1,
@@ -209,6 +212,7 @@ class AsyncLLM(EngineClient):
             stat_loggers=stat_loggers,
             log_requests=enable_log_requests,
             log_stats=not disable_log_stats,
+            aggregate_engine_logging=aggregate_engine_logging,
             usage_context=usage_context,
             client_addresses=client_addresses,
             client_count=client_count,

vllm/v1/engine/llm_engine.py

@@ -51,6 +51,7 @@ class LLMEngine:
         vllm_config: VllmConfig,
         executor_class: type[Executor],
         log_stats: bool,
+        aggregate_engine_logging: bool = False,
         usage_context: UsageContext = UsageContext.ENGINE_CONTEXT,
         stat_loggers: list[StatLoggerFactory] | None = None,
         mm_registry: MultiModalRegistry = MULTIMODAL_REGISTRY,
@@ -132,6 +133,7 @@ class LLMEngine:
                 vllm_config=vllm_config,
                 custom_stat_loggers=stat_loggers,
                 enable_default_loggers=log_stats,
+                aggregate_engine_logging=aggregate_engine_logging,
             )
             self.logger_manager.log_engine_initialized()
 

vllm/v1/metrics/loggers.py

@@ -24,7 +24,9 @@ from vllm.v1.spec_decode.metrics import SpecDecodingLogging, SpecDecodingProm
 
 logger = init_logger(__name__)
 
-StatLoggerFactory = Callable[[VllmConfig, int], "StatLoggerBase"]
+PerEngineStatLoggerFactory = Callable[[VllmConfig, int], "StatLoggerBase"]
+AggregateStatLoggerFactory = type["AggregateStatLoggerBase"]
+StatLoggerFactory = AggregateStatLoggerFactory | PerEngineStatLoggerFactory
 
 
 class StatLoggerBase(ABC):
@@ -54,6 +56,14 @@ class StatLoggerBase(ABC):
         pass
 
 
+class AggregateStatLoggerBase(StatLoggerBase):
+    """Abstract base class for loggers that
+    aggregate across multiple DP engines."""
+
+    @abstractmethod
+    def __init__(self, vllm_config: VllmConfig, engine_indexes: list[int]): ...
+
+
 class LoggingStatLogger(StatLoggerBase):
     def __init__(self, vllm_config: VllmConfig, engine_index: int = 0):
         self.engine_index = engine_index
@@ -72,6 +82,8 @@ class LoggingStatLogger(StatLoggerBase):
         self.kv_connector_logging = KVConnectorLogging(kv_tranfer_config)
         self.last_prompt_throughput: float = 0.0
         self.last_generation_throughput: float = 0.0
+        self.engine_is_idle = False
+        self.aggregated = False
 
     def _reset(self, now):
         self.last_log_time = now
@@ -92,6 +104,10 @@ class LoggingStatLogger(StatLoggerBase):
             return 0.0
         return float(tracked_stats / delta_time)
 
+    @property
+    def log_prefix(self):
+        return "Engine {:03d}: ".format(self.engine_index)
+
     def record(
         self,
         scheduler_stats: SchedulerStats | None,
@@ -110,34 +126,37 @@ class LoggingStatLogger(StatLoggerBase):
                 self.spec_decoding_logging.observe(scheduler_stats.spec_decoding_stats)
             if kv_connector_stats := scheduler_stats.kv_connector_stats:
                 self.kv_connector_logging.observe(kv_connector_stats)
-            self.last_scheduler_stats = scheduler_stats
+            if not self.aggregated:
-
+                self.last_scheduler_stats = scheduler_stats
         if mm_cache_stats:
             self.mm_caching_metrics.observe(mm_cache_stats)
 
-    def log(self):
+    def _update_stats(self):
         now = time.monotonic()
         prompt_throughput = self._get_throughput(self.num_prompt_tokens, now)
         generation_throughput = self._get_throughput(self.num_generation_tokens, now)
 
         self._reset(now)
-
+        self.engine_is_idle = not any(
-        scheduler_stats = self.last_scheduler_stats
-
-        log_fn = logger.info
-        if not any(
             (
                 prompt_throughput,
                 generation_throughput,
                 self.last_prompt_throughput,
                 self.last_generation_throughput,
             )
-        ):
+        )
-            # Avoid log noise on an idle production system
-            log_fn = logger.debug
         self.last_generation_throughput = generation_throughput
         self.last_prompt_throughput = prompt_throughput
 
+    def aggregate_scheduler_stats(self):
+        # noop for per engine loggers
+        return
+
+    def log(self):
+        self._update_stats()
+        self.aggregate_scheduler_stats()
+        # Avoid log noise on an idle production system
+        log_fn = logger.debug if self.engine_is_idle else logger.info
         # Format and print output.
         log_parts = [
             "Avg prompt throughput: %.1f tokens/s",
@@ -148,11 +167,11 @@ class LoggingStatLogger(StatLoggerBase):
             "Prefix cache hit rate: %.1f%%",
         ]
         log_args = [
-            prompt_throughput,
+            self.last_prompt_throughput,
-            generation_throughput,
+            self.last_generation_throughput,
-            scheduler_stats.num_running_reqs,
+            self.last_scheduler_stats.num_running_reqs,
-            scheduler_stats.num_waiting_reqs,
+            self.last_scheduler_stats.num_waiting_reqs,
-            scheduler_stats.kv_cache_usage * 100,
+            self.last_scheduler_stats.kv_cache_usage * 100,
             self.prefix_caching_metrics.hit_rate * 100,
         ]
         if not self.mm_caching_metrics.empty:
@@ -160,8 +179,7 @@ class LoggingStatLogger(StatLoggerBase):
             log_args.append(self.mm_caching_metrics.hit_rate * 100)
 
         log_fn(
-            "Engine %03d: " + ", ".join(log_parts),
+            self.log_prefix + ", ".join(log_parts),
-            self.engine_index,
             *log_args,
         )
 
@@ -178,7 +196,114 @@ class LoggingStatLogger(StatLoggerBase):
             )
 
 
-class PrometheusStatLogger(StatLoggerBase):
+class AggregatedLoggingStatLogger(LoggingStatLogger, AggregateStatLoggerBase):
+    def __init__(
+        self,
+        vllm_config: VllmConfig,
+        engine_indexes: list[int],
+    ):
+        self.engine_indexes = engine_indexes
+        self.last_scheduler_stats_dict: dict[int, SchedulerStats] = {
+            idx: SchedulerStats() for idx in self.engine_indexes
+        }
+        LoggingStatLogger.__init__(self, vllm_config, engine_index=-1)
+        self.aggregated = True
+
+    @property
+    def log_prefix(self):
+        return "{} Engines Aggregated: ".format(len(self.engine_indexes))
+
+    def record(
+        self,
+        scheduler_stats: SchedulerStats | None,
+        iteration_stats: IterationStats | None,
+        mm_cache_stats: MultiModalCacheStats | None = None,
+        engine_idx: int = 0,
+    ):
+        if engine_idx not in self.engine_indexes:
+            logger.warning("Unexpected engine_idx: %d", engine_idx)
+            return
+        LoggingStatLogger.record(
+            self,
+            scheduler_stats,
+            iteration_stats,
+            mm_cache_stats=mm_cache_stats,
+            engine_idx=engine_idx,
+        )
+        if scheduler_stats is not None:
+            self.last_scheduler_stats_dict[engine_idx] = scheduler_stats
+
+    def aggregate_scheduler_stats(self):
+        self.last_scheduler_stats = SchedulerStats()
+        for last_scheduler_stats in self.last_scheduler_stats_dict.values():
+            self.last_scheduler_stats.num_waiting_reqs += (
+                last_scheduler_stats.num_waiting_reqs
+            )
+            self.last_scheduler_stats.num_running_reqs += (
+                last_scheduler_stats.num_running_reqs
+            )
+            self.last_scheduler_stats.num_corrupted_reqs += (
+                last_scheduler_stats.num_corrupted_reqs
+            )
+            self.last_scheduler_stats.kv_cache_usage += (
+                last_scheduler_stats.kv_cache_usage
+            )
+        self.last_scheduler_stats.kv_cache_usage /= len(self.last_scheduler_stats_dict)
+
+    def log(self):
+        LoggingStatLogger.log(self)
+
+    def log_engine_initialized(self):
+        if self.vllm_config.cache_config.num_gpu_blocks:
+            logger.info(
+                "%d Engines: vllm cache_config_info with initialization "
+                "after num_gpu_blocks is: %d",
+                len(self.engine_indexes),
+                self.vllm_config.cache_config.num_gpu_blocks,
+            )
+
+
+class PerEngineStatLoggerAdapter(AggregateStatLoggerBase):
+    def __init__(
+        self,
+        vllm_config: VllmConfig,
+        engine_indexes: list[int],
+        per_engine_stat_logger_factory: PerEngineStatLoggerFactory,
+    ) -> None:
+        self.per_engine_stat_loggers = {}
+        self.engine_indexes = engine_indexes
+        for engine_index in engine_indexes:
+            self.per_engine_stat_loggers[engine_index] = per_engine_stat_logger_factory(
+                vllm_config, engine_index
+            )
+
+    def record(
+        self,
+        scheduler_stats: SchedulerStats | None,
+        iteration_stats: IterationStats | None,
+        mm_cache_stats: MultiModalCacheStats | None = None,
+        engine_idx: int = 0,
+    ):
+        if engine_idx not in self.per_engine_stat_loggers:
+            logger.warning("Unexpected engine_idx: %d", engine_idx)
+            return
+        self.per_engine_stat_loggers[engine_idx].record(
+            scheduler_stats,
+            iteration_stats,
+            mm_cache_stats=mm_cache_stats,
+            engine_idx=engine_idx,
+        )
+
+    def log(self):
+        for per_engine_stat_logger in self.per_engine_stat_loggers.values():
+            per_engine_stat_logger.log()
+
+    def log_engine_initialized(self):
+        for per_engine_stat_logger in self.per_engine_stat_loggers.values():
+            per_engine_stat_logger.log_engine_initialized()
+
+
+class PrometheusStatLogger(AggregateStatLoggerBase):
     _gauge_cls = Gauge
     _counter_cls = Counter
     _histogram_cls = Histogram
@@ -189,6 +314,7 @@ class PrometheusStatLogger(StatLoggerBase):
     ):
         if engine_indexes is None:
             engine_indexes = [0]
+
         self.engine_indexes = engine_indexes
 
         unregister_vllm_metrics()
@@ -880,14 +1006,14 @@ class StatLoggerManager:
         engine_idxs: list[int] | None = None,
         custom_stat_loggers: list[StatLoggerFactory] | None = None,
         enable_default_loggers: bool = True,
+        aggregate_engine_logging: bool = False,
         client_count: int = 1,
     ):
-        self.engine_idxs = engine_idxs if engine_idxs else [0]
+        self.engine_indexes = engine_idxs if engine_idxs else [0]
-
+        self.stat_loggers: list[AggregateStatLoggerBase] = []
-        factories: list[StatLoggerFactory] = []
+        stat_logger_factories: list[StatLoggerFactory] = []
         if custom_stat_loggers is not None:
-            factories.extend(custom_stat_loggers)
+            stat_logger_factories.extend(custom_stat_loggers)
-
         if enable_default_loggers and logger.isEnabledFor(logging.INFO):
             if client_count > 1:
                 logger.warning(
@@ -895,27 +1021,35 @@ class StatLoggerManager:
                     "disabling stats logging to avoid incomplete stats."
                 )
             else:
-                factories.append(LoggingStatLogger)
+                default_logger_factory = (
-
+                    AggregatedLoggingStatLogger
-        # engine_idx: StatLogger
+                    if aggregate_engine_logging
-        self.per_engine_logger_dict: dict[int, list[StatLoggerBase]] = {}
+                    else LoggingStatLogger
-        prometheus_factory = PrometheusStatLogger
+                )
-        for engine_idx in self.engine_idxs:
+                stat_logger_factories.append(default_logger_factory)
-            loggers: list[StatLoggerBase] = []
+        custom_prometheus_logger: bool = False
-            for logger_factory in factories:
+        for stat_logger_factory in stat_logger_factories:
-                # If we get a custom prometheus logger, use that
+            if isinstance(stat_logger_factory, type) and issubclass(
-                # instead. This is typically used for the ray case.
+                stat_logger_factory, AggregateStatLoggerBase
-                if isinstance(logger_factory, type) and issubclass(
+            ):
-                    logger_factory, PrometheusStatLogger
+                global_stat_logger = stat_logger_factory(
-                ):
+                    vllm_config=vllm_config,
-                    prometheus_factory = logger_factory
+                    engine_indexes=self.engine_indexes,
-                    continue
+                )
-                loggers.append(logger_factory(vllm_config, engine_idx))  # type: ignore
+                if isinstance(global_stat_logger, PrometheusStatLogger):
-            self.per_engine_logger_dict[engine_idx] = loggers
+                    custom_prometheus_logger = True
-
+            else:
-        # For Prometheus, need to share the metrics between EngineCores.
+                # per engine logger
-        # Each EngineCore's metrics are expressed as a unique label.
+                global_stat_logger = PerEngineStatLoggerAdapter(
-        self.prometheus_logger = prometheus_factory(vllm_config, engine_idxs)
+                    vllm_config=vllm_config,
+                    engine_indexes=self.engine_indexes,
+                    per_engine_stat_logger_factory=stat_logger_factory,  # type: ignore[arg-type]
+                )
+            self.stat_loggers.append(global_stat_logger)
+        if not custom_prometheus_logger:
+            self.stat_loggers.append(
+                PrometheusStatLogger(vllm_config, self.engine_indexes)
+            )
 
     def record(
         self,
@@ -926,9 +1060,7 @@ class StatLoggerManager:
     ):
         if engine_idx is None:
             engine_idx = 0
-
+        for logger in self.stat_loggers:
-        per_engine_loggers = self.per_engine_logger_dict[engine_idx]
-        for logger in per_engine_loggers:
             logger.record(
                 scheduler_stats,
                 iteration_stats,
@@ -936,21 +1068,10 @@ class StatLoggerManager:
                 engine_idx=engine_idx,
             )
 
-        self.prometheus_logger.record(
-            scheduler_stats,
-            iteration_stats,
-            mm_cache_stats=mm_cache_stats,
-            engine_idx=engine_idx,
-        )
-
     def log(self):
-        for per_engine_loggers in self.per_engine_logger_dict.values():
+        for logger in self.stat_loggers:
-            for logger in per_engine_loggers:
+            logger.log()
-                logger.log()
 
     def log_engine_initialized(self):
-        self.prometheus_logger.log_engine_initialized()
+        for agg_logger in self.stat_loggers:
-
+            agg_logger.log_engine_initialized()
-        for per_engine_loggers in self.per_engine_logger_dict.values():
-            for logger in per_engine_loggers:
-                logger.log_engine_initialized()