[Misc] Replace Optional[X] with X | None syntax (#33332)

Signed-off-by: carlory <baofa.fan@daocloud.io>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>

vllm/beam_search.py

@@ -2,7 +2,7 @@
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 from dataclasses import dataclass
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any
 
 from vllm.logprobs import Logprob
 from vllm.lora.request import LoRARequest
@@ -27,7 +27,7 @@ class BeamSearchSequence:
     text: str | None = None
     finish_reason: str | None = None
     stop_reason: int | str | None = None
-    multi_modal_data: Optional["MultiModalDataDict"] = None
+    multi_modal_data: "MultiModalDataDict | None" = None
     mm_processor_kwargs: dict[str, Any] | None = None
 
 

vllm/distributed/kv_transfer/kv_connector/factory.py

@@ -3,7 +3,7 @@
 
 import importlib
 from collections.abc import Callable
-from typing import TYPE_CHECKING, Optional, cast
+from typing import TYPE_CHECKING, cast
 
 from vllm.distributed.kv_transfer.kv_connector.base import (
     KVConnectorBase,
@@ -44,7 +44,7 @@ class KVConnectorFactory:
         cls,
         config: "VllmConfig",
         role: KVConnectorRole,
-        kv_cache_config: Optional["KVCacheConfig"] = None,
+        kv_cache_config: "KVCacheConfig | None" = None,
     ) -> KVConnectorBase:
         kv_transfer_config = config.kv_transfer_config
         if kv_transfer_config is None:

vllm/distributed/kv_transfer/kv_connector/v1/base.py

@@ -41,7 +41,7 @@ The class provides the following primitives:
 import enum
 from abc import ABC, abstractmethod
 from collections.abc import Callable, Iterable
-from typing import TYPE_CHECKING, Any, Literal, Optional
+from typing import TYPE_CHECKING, Any, Literal
 
 import torch
 
@@ -161,7 +161,7 @@ class KVConnectorBase_V1(ABC):
         self,
         vllm_config: "VllmConfig",
         role: KVConnectorRole,
-        kv_cache_config: Optional["KVCacheConfig"] = None,
+        kv_cache_config: "KVCacheConfig | None" = None,
     ):
         logger.warning(
             "Initializing KVConnectorBase_V1. This API is experimental and "
@@ -383,13 +383,13 @@ class KVConnectorBase_V1(ABC):
         """
         return None
 
-    def get_kv_connector_stats(self) -> Optional["KVConnectorStats"]:
+    def get_kv_connector_stats(self) -> "KVConnectorStats | None":
         """
         Get the KV connector stats collected during the last interval.
         """
         return None
 
-    def get_kv_connector_kv_cache_events(self) -> Optional["KVConnectorKVEvents"]:
+    def get_kv_connector_kv_cache_events(self) -> "KVConnectorKVEvents | None":
         """
         Get the KV connector kv cache events collected during the last interval.
         This function should be called by the model runner every time after the
@@ -558,7 +558,7 @@ class KVConnectorBase_V1(ABC):
     @classmethod
     def build_kv_connector_stats(
         cls, data: dict[str, Any] | None = None
-    ) -> Optional["KVConnectorStats"]:
+    ) -> "KVConnectorStats | None":
         """
         KVConnectorStats resolution method. This method allows dynamically
         registered connectors to return their own KVConnectorStats object,
@@ -584,7 +584,7 @@ class KVConnectorBase_V1(ABC):
         metric_types: dict[type["PromMetric"], type["PromMetricT"]],
         labelnames: list[str],
         per_engine_labelvalues: dict[int, list[object]],
-    ) -> Optional["KVConnectorPromMetrics"]:
+    ) -> "KVConnectorPromMetrics | None":
         """
         Create a KVConnectorPromMetrics subclass which should register
         per-connector Prometheus metrics and implement observe() to

vllm/distributed/kv_transfer/kv_connector/v1/decode_bench_connector.py

@@ -32,7 +32,7 @@ Usage:
 """
 
 from dataclasses import dataclass
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any
 
 import torch
 
@@ -84,7 +84,7 @@ class DecodeBenchConnector(KVConnectorBase_V1):
         self,
         vllm_config: "VllmConfig",
         role: KVConnectorRole,
-        kv_cache_config: Optional["KVCacheConfig"] = None,
+        kv_cache_config: "KVCacheConfig | None" = None,
     ):
         super().__init__(vllm_config, role, kv_cache_config)
 

vllm/distributed/kv_transfer/kv_connector/v1/example_connector.py

@@ -2,7 +2,7 @@
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 import os
 from dataclasses import dataclass, field
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any
 
 import safetensors
 import torch
@@ -91,7 +91,7 @@ class ExampleConnector(KVConnectorBase_V1):
         self,
         vllm_config: "VllmConfig",
         role: KVConnectorRole,
-        kv_cache_config: Optional["KVCacheConfig"] = None,
+        kv_cache_config: "KVCacheConfig | None" = None,
     ):
         super().__init__(
             vllm_config=vllm_config,

vllm/distributed/kv_transfer/kv_connector/v1/lmcache_integration/vllm_v1_adapter.py

@@ -5,7 +5,7 @@ import os
 import uuid
 from collections.abc import Generator
 from dataclasses import dataclass, field
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any
 
 import torch
 from lmcache import utils
@@ -274,7 +274,7 @@ class ReqMeta:
         load_spec: LoadSpec | None = None,
         discard_partial_chunks: bool = True,
         save_decode_cache: bool = False,
-    ) -> Optional["ReqMeta"]:
+    ) -> "ReqMeta | None":
         """Create the request metadata from a request tracker.
 
         Args:

vllm/distributed/kv_transfer/kv_connector/v1/lmcache_mp_connector.py

@@ -3,7 +3,7 @@
 import enum
 from collections.abc import Iterable
 from dataclasses import dataclass, field
-from typing import TYPE_CHECKING, Any, Literal, Optional, cast
+from typing import TYPE_CHECKING, Any, Literal, cast
 
 import torch
 import zmq
@@ -385,7 +385,7 @@ class LMCacheMPConnector(KVConnectorBase_V1):
         self,
         vllm_config: "VllmConfig",
         role: KVConnectorRole,
-        kv_cache_config: Optional["KVCacheConfig"] = None,
+        kv_cache_config: "KVCacheConfig | None" = None,
     ):
         super().__init__(vllm_config, role, kv_cache_config)
 
@@ -595,7 +595,7 @@ class LMCacheMPConnector(KVConnectorBase_V1):
             self.worker_adapter.shutdown()
         return None
 
-    def get_kv_connector_stats(self) -> Optional["KVConnectorStats"]:
+    def get_kv_connector_stats(self) -> "KVConnectorStats | None":
         """
         Get the KV connector stats collected during the last interval.
         """
@@ -810,7 +810,7 @@ class LMCacheMPConnector(KVConnectorBase_V1):
     @classmethod
     def build_kv_connector_stats(
         cls, data: dict[str, Any] | None = None
-    ) -> Optional["KVConnectorStats"]:
+    ) -> "KVConnectorStats | None":
         """
         KVConnectorStats resolution method. This method allows dynamically
         registered connectors to return their own KVConnectorStats object,
@@ -825,7 +825,7 @@ class LMCacheMPConnector(KVConnectorBase_V1):
         metric_types: dict[type["PromMetric"], type["PromMetricT"]],
         labelnames: list[str],
         per_engine_labelvalues: dict[int, list[object]],
-    ) -> Optional["KVConnectorPromMetrics"]:
+    ) -> "KVConnectorPromMetrics | None":
         """
         Create a KVConnectorPromMetrics subclass which should register
         per-connector Prometheus metrics and implement observe() to

vllm/distributed/kv_transfer/kv_connector/v1/mooncake_connector.py

@@ -6,7 +6,7 @@ import time
 from collections import defaultdict
 from concurrent.futures import ThreadPoolExecutor
 from dataclasses import dataclass
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any
 
 import msgspec
 import numpy as np
@@ -115,7 +115,7 @@ class MooncakeConnector(KVConnectorBase_V1):
         self,
         vllm_config: VllmConfig,
         role: KVConnectorRole,
-        kv_cache_config: Optional["KVCacheConfig"] = None,
+        kv_cache_config: "KVCacheConfig | None" = None,
     ):
         super().__init__(vllm_config, role, kv_cache_config)
 

vllm/distributed/kv_transfer/kv_connector/v1/moriio/moriio_common.py

@@ -5,7 +5,7 @@ import threading
 import time
 from collections.abc import Iterator
 from dataclasses import dataclass
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any
 
 import msgspec
 import torch
@@ -101,7 +101,7 @@ class MoRIIOAgentMetadata(
 class RoleManager:
     """Manages role state across the connector."""
 
-    _instance: Optional["RoleManager"] = None
+    _instance: "RoleManager | None" = None
     _lock = threading.Lock()
 
     def __init__(self) -> None:

vllm/distributed/kv_transfer/kv_connector/v1/moriio/moriio_connector.py

@@ -7,7 +7,7 @@ import threading
 import time
 from collections import defaultdict
 from concurrent.futures import Future, ThreadPoolExecutor
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any
 
 import msgpack
 import msgspec
@@ -90,7 +90,7 @@ class MoRIIOConnector(KVConnectorBase_V1):
         self,
         vllm_config: VllmConfig,
         role: KVConnectorRole,
-        kv_cache_config: Optional["KVCacheConfig"] = None,
+        kv_cache_config: "KVCacheConfig | None" = None,
     ):
         super().__init__(vllm_config, role)
         assert vllm_config.kv_transfer_config is not None, (
@@ -333,7 +333,7 @@ class MoRIIOConnectorScheduler:
         request: "Request",
         blocks: "KVCacheBlocks",
         num_external_tokens: int,
-        connector_worker: Optional["MoRIIOConnectorWorker"] = None,
+        connector_worker: "MoRIIOConnectorWorker | None" = None,
     ):
         params = request.kv_transfer_params
         if not params:

vllm/distributed/kv_transfer/kv_connector/v1/moriio/moriio_engine.py

 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 import threading
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any
 from weakref import ref as weakref_ref
 
 import msgpack
@@ -340,7 +340,7 @@ class MoRIIOWrapper:
 
     def __init__(
         self,
-        moriio_engine: Optional["IOEngine"] = None,
+        moriio_engine: "IOEngine | None" = None,
         tp_rank: int = 0,
         dp_rank: int = 0,
     ):

vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py

@@ -14,7 +14,7 @@ from collections import defaultdict
 from collections.abc import Iterator
 from concurrent.futures import Future, ThreadPoolExecutor
 from dataclasses import dataclass
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any
 
 import msgspec
 import numpy as np
@@ -302,7 +302,7 @@ class NixlConnector(KVConnectorBase_V1):
         self,
         vllm_config: VllmConfig,
         role: KVConnectorRole,
-        kv_cache_config: Optional["KVCacheConfig"] = None,
+        kv_cache_config: "KVCacheConfig | None" = None,
     ):
         super().__init__(vllm_config, role, kv_cache_config)
 

vllm/distributed/kv_transfer/kv_connector/v1/p2p/p2p_nccl_connector.py

@@ -2,7 +2,7 @@
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 from dataclasses import dataclass
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any
 
 import regex as re
 import torch
@@ -76,7 +76,7 @@ class P2pNcclConnector(KVConnectorBase_V1):
         self,
         vllm_config: "VllmConfig",
         role: KVConnectorRole,
-        kv_cache_config: Optional["KVCacheConfig"] = None,
+        kv_cache_config: "KVCacheConfig | None" = None,
     ):
         super().__init__(
             vllm_config=vllm_config,

vllm/distributed/kv_transfer/kv_transfer_state.py

 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
-from typing import TYPE_CHECKING, Optional
+from typing import TYPE_CHECKING
 
 from vllm.distributed.kv_transfer.kv_connector.base import KVConnectorBaseType
 from vllm.distributed.kv_transfer.kv_connector.factory import KVConnectorFactory
@@ -49,7 +49,7 @@ def is_v1_kv_transfer_group(connector: KVConnectorBaseType | None = None) -> boo
 
 
 def ensure_kv_transfer_initialized(
-    vllm_config: "VllmConfig", kv_cache_config: Optional["KVCacheConfig"] = None
+    vllm_config: "VllmConfig", kv_cache_config: "KVCacheConfig | None" = None
 ) -> None:
     """
     Initialize KV cache transfer parallel group.

vllm/distributed/parallel_state.py

@@ -33,7 +33,7 @@ from contextlib import contextmanager, nullcontext
 from dataclasses import dataclass
 from datetime import timedelta
 from multiprocessing import shared_memory
-from typing import Any, Optional
+from typing import Any
 from unittest.mock import patch
 
 import torch
@@ -106,7 +106,7 @@ def _get_unique_name(name: str) -> str:
     return newname
 
 
-_groups: dict[str, Callable[[], Optional["GroupCoordinator"]]] = {}
+_groups: dict[str, Callable[[], "GroupCoordinator | None"]] = {}
 
 
 def _register_group(group: "GroupCoordinator") -> None:
@@ -784,7 +784,7 @@ class GroupCoordinator:
         self,
         tensor_dict: dict[str, torch.Tensor | Any],
         dst: int | None = None,
-        all_gather_group: Optional["GroupCoordinator"] = None,
+        all_gather_group: "GroupCoordinator | None" = None,
         all_gather_tensors: dict[str, bool] | None = None,
     ) -> dict[str, torch.Tensor | Any] | None:
         """Send the input tensor dictionary.
@@ -871,7 +871,7 @@ class GroupCoordinator:
     def recv_tensor_dict(
         self,
         src: int | None = None,
-        all_gather_group: Optional["GroupCoordinator"] = None,
+        all_gather_group: "GroupCoordinator | None" = None,
         all_gather_tensors: dict[str, bool] | None = None,
     ) -> dict[str, torch.Tensor | Any] | None:
         """Recv the input tensor dictionary.

vllm/entrypoints/anthropic/protocol.py

@@ -3,7 +3,7 @@
 """Pydantic models for Anthropic API protocol"""
 
 import time
-from typing import Any, Literal, Optional
+from typing import Any, Literal
 
 from pydantic import BaseModel, field_validator
 
@@ -135,7 +135,7 @@ class AnthropicStreamEvent(BaseModel):
         "ping",
         "error",
     ]
-    message: Optional["AnthropicMessagesResponse"] = None
+    message: "AnthropicMessagesResponse | None" = None
     delta: AnthropicDelta | None = None
     content_block: AnthropicContentBlock | None = None
     index: int | None = None

vllm/lora/lora_weights.py

@@ -2,7 +2,6 @@
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 from collections.abc import Sequence as GenericSequence
-from typing import Optional
 
 import torch
 import torch.types
@@ -126,7 +125,7 @@ class PackedLoRALayerWeights(LoRALayerWeights):
 
     @classmethod
     def pack(
-        cls, loras: GenericSequence[Optional["LoRALayerWeights"]]
+        cls, loras: GenericSequence["LoRALayerWeights | None"]
     ) -> "PackedLoRALayerWeights":
         """Pack a list of LoRAs into a single LoRA.
 
@@ -155,7 +154,7 @@ class PackedLoRALayerWeights(LoRALayerWeights):
     @classmethod
     def pack_moe(
         cls,
-        loras: GenericSequence[Optional["LoRALayerWeights"]],
+        loras: GenericSequence["LoRALayerWeights | None"],
         module_name: str,
         is_non_gated_moe: bool = False,
     ) -> "PackedLoRALayerWeights":

vllm/lora/utils.py

@@ -2,7 +2,7 @@
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 import os
-from typing import TYPE_CHECKING, Optional
+from typing import TYPE_CHECKING
 
 import huggingface_hub
 from huggingface_hub.utils import HfHubHTTPError, HFValidationError
@@ -131,7 +131,7 @@ def replace_submodule(
 
 
 def parse_fine_tuned_lora_name(
-    name: str, weights_mapper: Optional["WeightsMapper"] = None
+    name: str, weights_mapper: "WeightsMapper | None" = None
 ) -> tuple[str, bool]:
     """Parse the name of lora weights.
 

vllm/model_executor/layers/fused_moe/config.py

@@ -2,7 +2,7 @@
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 from dataclasses import dataclass
 from enum import IntEnum
-from typing import Optional, Union
+from typing import Union
 
 import torch
 
@@ -284,7 +284,7 @@ class FusedMoEQuantConfig:
         return self._w1.bias
 
     @property
-    def w1_precision(self) -> Optional["PrecisionConfig"]:
+    def w1_precision(self) -> "PrecisionConfig | None":
         assert self._w1.scale is None or isinstance(self._w1.scale, PrecisionConfig)
         return self._w1.scale
 
@@ -306,7 +306,7 @@ class FusedMoEQuantConfig:
         return self._w2.bias
 
     @property
-    def w2_precision(self) -> Optional["PrecisionConfig"]:
+    def w2_precision(self) -> "PrecisionConfig | None":
         assert self._w2.scale is None or isinstance(self._w2.scale, PrecisionConfig)
         return self._w2.scale
 

vllm/model_executor/layers/quantization/awq_marlin.py

 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any
 
 import torch
 from safetensors.torch import _TYPES as _SAFETENSORS_TO_TORCH_DTYPE
@@ -148,7 +148,7 @@ class AWQMarlinConfig(QuantizationConfig):
     @classmethod
     def override_quantization_method(
         cls, hf_quant_cfg, user_quant
-    ) -> Optional["QuantizationMethods"]:
+    ) -> "QuantizationMethods | None":
         can_convert = cls.is_awq_marlin_compatible(hf_quant_cfg)
         is_valid_user_quant = (
             user_quant is None or user_quant == "marlin" or user_quant == "awq_marlin"
@@ -173,7 +173,7 @@ class AWQMarlinConfig(QuantizationConfig):
 
     def get_quant_method(
         self, layer: torch.nn.Module, prefix: str
-    ) -> Optional["QuantizeMethodBase"]:
+    ) -> "QuantizeMethodBase | None":
         if isinstance(layer, LinearBase) or (
             isinstance(layer, ParallelLMHead) and self.lm_head_quantized
         ):