[Chore] Rename SchedulerConfig.chunked_prefill_enabled (#28735)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>

vllm/config/scheduler.py

@@ -8,7 +8,7 @@ from typing import TYPE_CHECKING, Any, ClassVar, Literal, cast
 
 from pydantic import Field, field_validator, model_validator
 from pydantic.dataclasses import dataclass
-from typing_extensions import Self
+from typing_extensions import Self, deprecated
 
 from vllm.config.utils import config
 from vllm.logger import init_logger
@@ -233,6 +233,11 @@ class SchedulerConfig:
             )
 
     @property
+    @deprecated(
+        "`SchedulerConfig.chunked_prefill_enabled` has been renamed to "
+        "`SchedulerConfig.enable_chunked_prefill`. "
+        "The old name will be removed in v0.12."
+    )
     def chunked_prefill_enabled(self) -> bool:
         return self.enable_chunked_prefill
 
@@ -244,7 +249,7 @@ class SchedulerConfig:
     def _verify_args(self) -> Self:
         if (
             self.max_num_batched_tokens < self.max_model_len
-            and not self.chunked_prefill_enabled
+            and not self.enable_chunked_prefill
         ):
             raise ValueError(
                 f"max_num_batched_tokens ({self.max_num_batched_tokens}) is "
@@ -271,7 +276,7 @@ class SchedulerConfig:
             )
 
         if self.max_num_partial_prefills > 1:
-            if not self.chunked_prefill_enabled:
+            if not self.enable_chunked_prefill:
                 raise ValueError(
                     "Chunked prefill must be enabled to set "
                     "max_num_partial_prefills > 1."

vllm/config/vllm.py

@@ -411,7 +411,7 @@ class VllmConfig:
 
         if (
             self.model_config is not None
-            and self.scheduler_config.chunked_prefill_enabled
+            and self.scheduler_config.enable_chunked_prefill
             and self.model_config.dtype == torch.float32
             and current_platform.get_device_capability() == (7, 5)
         ):
@@ -584,7 +584,7 @@ class VllmConfig:
         ):
             for reason in disable_chunked_prefill_reasons:
                 logger.info(reason)
-            self.scheduler_config.chunked_prefill_enabled = False
+            self.scheduler_config.enable_chunked_prefill = False
             self.scheduler_config.long_prefill_token_threshold = 0
 
             if self.cache_config is not None:
@@ -1026,7 +1026,7 @@ class VllmConfig:
             f"seed={self.model_config.seed}, "
             f"served_model_name={self.model_config.served_model_name}, "
             f"enable_prefix_caching={self.cache_config.enable_prefix_caching}, "
-            f"chunked_prefill_enabled={self.scheduler_config.chunked_prefill_enabled}, "  # noqa
+            f"enable_chunked_prefill={self.scheduler_config.enable_chunked_prefill}, "  # noqa
             f"pooler_config={self.model_config.pooler_config!r}, "
             f"compilation_config={self.compilation_config!r}"
         )

vllm/platforms/cpu.py

@@ -192,7 +192,7 @@ class CpuPlatform(Platform):
 
         scheduler_config = vllm_config.scheduler_config
         if (
-            scheduler_config.chunked_prefill_enabled
+            scheduler_config.enable_chunked_prefill
             or cache_config.enable_prefix_caching
         ) and cache_config.cache_dtype != "auto":
             raise RuntimeError(

vllm/v1/core/sched/scheduler.py

@@ -497,7 +497,7 @@ class Scheduler(SchedulerInterface):
                     # chunked prefill has to be enabled explicitly to allow
                     # pooling requests to be chunked
                     if (
-                        not self.scheduler_config.chunked_prefill_enabled
+                        not self.scheduler_config.enable_chunked_prefill
                         and num_new_tokens > token_budget
                     ):
                         self.waiting.pop_request()

vllm/v1/engine/core.py

@@ -124,7 +124,7 @@ class EngineCore:
             # Encoder models without KV cache don't support
             # chunked prefill. But do SSM models?
             logger.info("Disabling chunked prefill for model without KVCache")
-            vllm_config.scheduler_config.chunked_prefill_enabled = False
+            vllm_config.scheduler_config.enable_chunked_prefill = False
 
         scheduler_block_size = (
             vllm_config.cache_config.block_size

vllm/v1/worker/gpu_model_runner.py

@@ -2031,7 +2031,7 @@ class GPUModelRunner(
 
         supported_tasks = list(model.pooler.get_supported_tasks())
 
-        if self.scheduler_config.chunked_prefill_enabled:
+        if self.scheduler_config.enable_chunked_prefill:
             if "token_embed" in supported_tasks:
                 supported_tasks.remove("token_embed")
             if "token_classify" in supported_tasks:
@@ -3825,7 +3825,7 @@ class GPUModelRunner(
         supported_pooling_tasks = self.get_supported_pooling_tasks()
 
         if not supported_pooling_tasks:
-            if self.scheduler_config.chunked_prefill_enabled:
+            if self.scheduler_config.enable_chunked_prefill:
                 raise RuntimeError(
                     f"Model {self.model_config.model} does not support "
                     "any pooling tasks with chunked prefill enabled. "