Update Optional[x] -> x | None and Union[x, y] to x | y (#26633)

Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>

docs/contributing/model/transcription.md

@@ -16,7 +16,7 @@ Declare supported languages and capabilities:
 
 ??? code "supported_languages and supports_transcription_only"
     ```python
-    from typing import ClassVar, Mapping, Optional, Literal
+    from typing import ClassVar, Mapping, Literal
     import numpy as np
     import torch
     from torch import nn
@@ -81,10 +81,10 @@ Return a dict containing `multi_modal_data` with the audio, and either a `prompt
             audio: np.ndarray,
             stt_config: SpeechToTextConfig,
             model_config: ModelConfig,
-            language: Optional[str],
+            language: str | None,
             task_type: Literal["transcribe", "translate"],
             request_prompt: str,
-            to_language: Optional[str],
+            to_language: str | None,
         ) -> PromptType:
             # Example with a free-form instruction prompt
             task_word = "Transcribe" if task_type == "transcribe" else "Translate"
@@ -117,10 +117,10 @@ Return a dict with separate `encoder_prompt` and `decoder_prompt` entries:
             audio: np.ndarray,
             stt_config: SpeechToTextConfig,
             model_config: ModelConfig,
-            language: Optional[str],
+            language: str | None,
             task_type: Literal["transcribe", "translate"],
             request_prompt: str,
-            to_language: Optional[str],
+            to_language: str | None,
         ) -> PromptType:
             if language is None:
                 raise ValueError("Language must be specified")
@@ -150,7 +150,7 @@ If your model requires a language and you want a default, override this method (
 ??? code "validate_language()"
     ```python
     @classmethod
-    def validate_language(cls, language: Optional[str]) -> Optional[str]:
+    def validate_language(cls, language: str | None) -> str | None:
         if language is None:
             logger.warning(
                 "Defaulting to language='en'. If you wish to transcribe audio in a different language, pass the `language` field.")
@@ -175,7 +175,7 @@ Provide a fast duration→token estimate to improve streaming usage statistics:
             audio_duration_s: float,
             stt_config: SpeechToTextConfig,
             model_config: ModelConfig,
-        ) -> Optional[int]:
+        ) -> int | None:
             # Return None if unknown; otherwise return an estimate.
             return int(audio_duration_s * stt_config.sample_rate // 320)  # example
     ```

docs/design/logits_processors.md

@@ -174,7 +174,7 @@ The previous sections alluded to the interfaces which vLLM logits processors mus
     from collections.abc import Sequence
     from dataclasses import dataclass
     from enum import Enum, auto
-    from typing import TYPE_CHECKING, Optional
+    from typing import TYPE_CHECKING
 
     import torch
 
@@ -244,7 +244,7 @@ The previous sections alluded to the interfaces which vLLM logits processors mus
         @abstractmethod
         def update_state(
             self,
-            batch_update: Optional["BatchUpdate"],
+            batch_update: "BatchUpdate" | None,
         ) -> None:
             """Called when there are new output tokens, prior
             to each forward pass.
@@ -274,7 +274,7 @@ A vLLM logits processor must subclass `LogitsProcessor` and define (at minimum)
     * Return `True` if the logits processor is argmax invariant (never changes what is the highest-logit-value token ID for a given request), `False` if the logits processor may modify argmax
     * `is_argmax_invariant()` is evaluated once at startup; if `True`, vLLM will skip applying this logits processor in a given step when all requests use greedy sampling
 
-* `update_state(self, batch_update: Optional["BatchUpdate"]) -> None`:
+* `update_state(self, batch_update: "BatchUpdate" | None) -> None`:
     * Consume a `BatchUpdate` data structure representing persistent batch state changes at the beginning of the current engine step
     * Use the `BatchUpdate` members to update logits processor internal state
     * **Note:** batch update data structure may be `None`, signaling no change to the batch constituents. In this case, the LogitsProcessor might still want to update its state based on the updated `output_token_ids` lists that it could have retained when they were added.

docs/features/custom_logitsprocs.md

@@ -93,7 +93,6 @@ The contrived example below implements a custom logits processor which consumes
 ??? code "Example custom logits processor definition"
 
     ``` python
-    from typing import Optional
     import torch
     from vllm.config import VllmConfig
     from vllm.sampling_params import SamplingParams
@@ -112,7 +111,7 @@ The contrived example below implements a custom logits processor which consumes
             """Never impacts greedy sampling"""
             return False
 
-        def update_state(self, batch_update: Optional[BatchUpdate]):
+        def update_state(self, batch_update: BatchUpdate | None):
             if not batch_update:
                 return