[Misc] Upgrade to Python 3.9 typing for additional directories (#14492)

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

vllm/inputs/preprocess.py

@@ -1,7 +1,8 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import asyncio
-from typing import List, Mapping, Optional, Tuple, Union, cast
+from collections.abc import Mapping
+from typing import Optional, Union, cast
 
 from typing_extensions import assert_never
 
@@ -92,7 +93,7 @@ class InputPreprocessor:
 
         return dec_start_token_id
 
-    def _get_default_enc_dec_decoder_prompt(self) -> List[int]:
+    def _get_default_enc_dec_decoder_prompt(self) -> list[int]:
         '''
         Specifically for encoder/decoder models:
         generate a default decoder prompt for when
@@ -130,8 +131,8 @@ class InputPreprocessor:
 
     def _prepare_decoder_input_ids_for_generation(
         self,
-        decoder_input_ids: Optional[List[int]],
-    ) -> List[int]:
+        decoder_input_ids: Optional[list[int]],
+    ) -> list[int]:
         """
         Prepares `decoder_input_ids` for generation with encoder-decoder models.
 
@@ -168,9 +169,9 @@ class InputPreprocessor:
 
     def _apply_prompt_adapter(
         self,
-        prompt_token_ids: List[int],
+        prompt_token_ids: list[int],
         prompt_adapter_request: Optional[PromptAdapterRequest],
-    ) -> List[int]:
+    ) -> list[int]:
         if prompt_adapter_request:
             prompt_token_ids = (
                 [0] * prompt_adapter_request.prompt_adapter_num_virtual_tokens
@@ -183,7 +184,7 @@ class InputPreprocessor:
         prompt: str,
         request_id: str,
         lora_request: Optional[LoRARequest],
-    ) -> List[int]:
+    ) -> list[int]:
         """
         Apply the model's tokenizer to a text prompt, returning the
         corresponding token IDs.
@@ -211,7 +212,7 @@ class InputPreprocessor:
         prompt: str,
         request_id: str,
         lora_request: Optional[LoRARequest],
-    ) -> List[int]:
+    ) -> list[int]:
         """Async version of :meth:`_tokenize_prompt`."""
         tokenizer = self.get_tokenizer_group()
         add_special_tokens = None
@@ -250,7 +251,7 @@ class InputPreprocessor:
 
     def _process_multimodal(
         self,
-        prompt: Union[str, List[int]],
+        prompt: Union[str, list[int]],
         mm_data: MultiModalDataDict,
         mm_processor_kwargs: Optional[Mapping[str, object]],
         lora_request: Optional[LoRARequest],
@@ -280,7 +281,7 @@ class InputPreprocessor:
 
     async def _process_multimodal_async(
         self,
-        prompt: Union[str, List[int]],
+        prompt: Union[str, list[int]],
         mm_data: MultiModalDataDict,
         mm_processor_kwargs: Optional[Mapping[str, object]],
         lora_request: Optional[LoRARequest],
@@ -511,7 +512,7 @@ class InputPreprocessor:
         self,
         inputs: SingletonInputs,
         decoder_inputs_to_override: Optional[SingletonInputs] = None,
-    ) -> Tuple[SingletonInputs, SingletonInputs]:
+    ) -> tuple[SingletonInputs, SingletonInputs]:
         """
         For encoder/decoder models only:
         Separate Encoder/Decoder inputs from a MultiModalEncDecInputs