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

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

vllm/model_executor/parameter.py

@@ -1,9 +1,8 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
-from collections.abc import Hashable
+from collections.abc import Callable, Hashable
 from fractions import Fraction
-from typing import Callable, Optional, Union
 from weakref import WeakValueDictionary
 
 import torch
@@ -36,7 +35,7 @@ class BasevLLMParameter(Parameter):
     into the parameter when the provided weight loader is called.
     """
 
-    def __new__(cls, data: Optional[torch.Tensor], **kwargs):
+    def __new__(cls, data: torch.Tensor | None, **kwargs):
         return super().__new__(cls, data=data, requires_grad=False)
 
     def __init__(self, data: torch.Tensor, weight_loader: Callable):
@@ -109,7 +108,7 @@ class BasevLLMParameter(Parameter):
     def load_qkv_weight(self, loaded_weight: torch.Tensor, **kwargs):
         self._assert_and_load(loaded_weight)
 
-    def _shard_id_as_int(self, shard_id: Union[str, int]) -> int:
+    def _shard_id_as_int(self, shard_id: str | int) -> int:
         if isinstance(shard_id, int):
             return shard_id
 
@@ -290,7 +289,7 @@ class PerTensorScaleParameter(BasevLLMParameter):
         super().load_row_parallel_weight(*args, **kwargs)
 
     def _load_into_shard_id(
-        self, loaded_weight: torch.Tensor, shard_id: Union[str, int], **kwargs
+        self, loaded_weight: torch.Tensor, shard_id: str | int, **kwargs
     ):
         """
         Slice the parameter data based on the shard id for
@@ -320,10 +319,10 @@ class PackedColumnParameter(_ColumnvLLMParameter):
 
     def __init__(
         self,
-        packed_factor: Union[int, Fraction],
+        packed_factor: int | Fraction,
         packed_dim: int,
-        marlin_tile_size: Optional[int] = None,
-        bitblas_tile_size: Optional[int] = None,
+        marlin_tile_size: int | None = None,
+        bitblas_tile_size: int | None = None,
         **kwargs,
     ):
         self._packed_factor = packed_factor
@@ -371,10 +370,10 @@ class PackedvLLMParameter(ModelWeightParameter):
 
     def __init__(
         self,
-        packed_factor: Union[int, Fraction],
+        packed_factor: int | Fraction,
         packed_dim: int,
-        marlin_tile_size: Optional[int] = None,
-        bitblas_tile_size: Optional[int] = None,
+        marlin_tile_size: int | None = None,
+        bitblas_tile_size: int | None = None,
         **kwargs,
     ):
         self._packed_factor = packed_factor
@@ -437,7 +436,7 @@ class SharedWeightParameter(BasevLLMParameter):
     local_tensors: set[torch.Tensor]
 
     # dictionary mapping partition indices to associated parameters
-    partitions: dict[int, Union[ModelWeightParameter, Parameter]]
+    partitions: dict[int, ModelWeightParameter | Parameter]
 
     def __new__(cls, **kwargs):
         return super().__new__(cls, data=None, **kwargs)
@@ -547,7 +546,7 @@ class SharedWeightParameter(BasevLLMParameter):
         self,
         param: BasevLLMParameter,
         loaded_weight: torch.Tensor,
-        loaded_weight_shard_id: Optional[Union[str, int]],
+        loaded_weight_shard_id: str | int | None,
     ):
         raise ValueError(
             "When loading partition weights of "