[Feature] Pluggable platform-specific scheduler (vllm-project#13161)

Signed-off-by: Yannick Schnider <yannick.schnider1@ibm.com>
Signed-off-by: Yannick Schnider <Yannick.Schnider1@ibm.com>

Author: yannicks1

.buildkite/test-pipeline.yaml

@@ -531,6 +531,7 @@ steps:
   - pip uninstall vllm_add_dummy_platform -y
   # end platform plugin tests
   # other tests continue here:
+  - pytest -v -s plugins_tests/test_scheduler_plugins.py
   - pip install -e ./plugins/vllm_add_dummy_model
   - pytest -v -s distributed/test_distributed_oot.py
   - pytest -v -s entrypoints/openai/test_oot_registration.py # it needs a clean process

tests/plugins_tests/test_scheduler_plugins.py

@@ -0,0 +1,33 @@
+# SPDX-License-Identifier: Apache-2.0
+
+from vllm.core.scheduler import Scheduler
+
+
+class DummyScheduler(Scheduler):
+
+    def schedule(self):
+        raise Exception("Exception raised by DummyScheduler")
+
+
+def test_scheduler_plugins():
+    import pytest
+
+    from vllm.engine.arg_utils import EngineArgs
+    from vllm.engine.llm_engine import LLMEngine
+    from vllm.sampling_params import SamplingParams
+
+    with pytest.raises(Exception) as exception_info:
+
+        engine_args = EngineArgs(
+            model="facebook/opt-125m",
+            enforce_eager=True,  # reduce test time
+            scheduler_cls=DummyScheduler,
+        )
+
+        engine = LLMEngine.from_engine_args(engine_args=engine_args)
+
+        sampling_params = SamplingParams(max_tokens=1)
+        engine.add_request("0", "foo", sampling_params)
+        engine.step()
+
+    assert str(exception_info.value) == "Exception raised by DummyScheduler"

vllm/config.py

@@ -1495,6 +1495,10 @@ class SchedulerConfig:
 
     chunked_prefill_enabled: bool = field(init=False)
 
+    # scheduler class or path. "vllm.core.scheduler.Scheduler" (default)
+    # or "mod.custom_class".
+    scheduler_cls: Union[str, Type[object]] = "vllm.core.scheduler.Scheduler"
+
     def compute_hash(self) -> str:
         """
         WARNING: Whenever a new field is added to this config,

vllm/engine/arg_utils.py

@@ -192,6 +192,7 @@ class EngineArgs:
     collect_detailed_traces: Optional[str] = None
     disable_async_output_proc: bool = False
     scheduling_policy: Literal["fcfs", "priority"] = "fcfs"
+    scheduler_cls: Union[str, Type[object]] = "vllm.core.scheduler.Scheduler"
 
     override_neuron_config: Optional[Dict[str, Any]] = None
     override_pooler_config: Optional[PoolerConfig] = None
@@ -938,6 +939,13 @@ def add_cli_args(parser: FlexibleArgumentParser) -> FlexibleArgumentParser:
             'priority (lower value means earlier handling) and time of '
             'arrival deciding any ties).')
 
+        parser.add_argument(
+            '--scheduler-cls',
+            default=EngineArgs.scheduler_cls,
+            help='The scheduler class to use. "vllm.core.scheduler.Scheduler" '
+            'is the default scheduler. Can be a class directly or the path to '
+            'a class of form "mod.custom_class".')
+
         parser.add_argument(
             '--override-neuron-config',
             type=json.loads,
@@ -1273,10 +1281,12 @@ def create_engine_config(self,
             send_delta_data=(envs.VLLM_USE_RAY_SPMD_WORKER
                              and parallel_config.use_ray),
             policy=self.scheduling_policy,
+            scheduler_cls=self.scheduler_cls,
             max_num_partial_prefills=self.max_num_partial_prefills,
             max_long_partial_prefills=self.max_long_partial_prefills,
             long_prefill_token_threshold=self.long_prefill_token_threshold,
         )
+
         lora_config = LoRAConfig(
             bias_enabled=self.enable_lora_bias,
             max_lora_rank=self.max_lora_rank,

vllm/engine/llm_engine.py

@@ -19,8 +19,7 @@
 from vllm.config import (DecodingConfig, LoRAConfig, ModelConfig,
                          ObservabilityConfig, ParallelConfig, SchedulerConfig,
                          VllmConfig)
-from vllm.core.scheduler import (ScheduledSequenceGroup, Scheduler,
-                                 SchedulerOutputs)
+from vllm.core.scheduler import ScheduledSequenceGroup, SchedulerOutputs
 from vllm.engine.arg_utils import EngineArgs
 from vllm.engine.metrics_types import StatLoggerBase, Stats
 from vllm.engine.output_processor.interfaces import (
@@ -58,7 +57,8 @@
     BaseTokenizerGroup, init_tokenizer_from_configs)
 from vllm.usage.usage_lib import (UsageContext, is_usage_stats_enabled,
                                   usage_message)
-from vllm.utils import Counter, Device, deprecate_kwargs, weak_bind
+from vllm.utils import (Counter, Device, deprecate_kwargs,
+                        resolve_obj_by_qualname, weak_bind)
 from vllm.version import __version__ as VLLM_VERSION
 
 logger = init_logger(__name__)
@@ -346,6 +346,11 @@ def get_tokenizer_for_seq(sequence: Sequence) -> AnyTokenizer:
         # Create the scheduler.
         # NOTE: the cache_config here have been updated with the numbers of
         # GPU and CPU blocks, which are profiled in the distributed executor.
+        if isinstance(self.vllm_config.scheduler_config.scheduler_cls, str):
+            Scheduler = resolve_obj_by_qualname(
+                self.vllm_config.scheduler_config.scheduler_cls)
+        else:
+            Scheduler = self.vllm_config.scheduler_config.scheduler_cls
         self.scheduler = [
             Scheduler(
                 self.scheduler_config, self.cache_config, self.lora_config,