fix mypy

Signed-off-by: wwl2755 <wangwenlong2755@gmail.com>

Author: wwl2755

tools/pre_commit/mypy.py

@@ -27,6 +27,7 @@
 FILES = [
     "vllm/*.py",
     "vllm/assets",
+    "vllm/engine",
     "vllm/entrypoints",
     "vllm/inputs",
     "vllm/logging_utils",

vllm/engine/arg_utils.py

@@ -1243,7 +1243,7 @@ def create_engine_config(
         (self.model, self.tokenizer, self.speculative_config) = (
             maybe_override_with_speculators(
                 model=self.model,
-                tokenizer=self.tokenizer,
+                tokenizer=self.tokenizer if self.tokenizer is not None else self.model,
                 revision=self.revision,
                 trust_remote_code=self.trust_remote_code,
                 vllm_speculative_config=self.speculative_config,
@@ -1685,7 +1685,7 @@ def _is_v1_supported_oracle(self, model_config: ModelConfig) -> bool:
         return True
 
     def _set_default_args(
-        self, usage_context: UsageContext, model_config: ModelConfig
+        self, usage_context: Optional[UsageContext], model_config: ModelConfig
     ) -> None:
         """Set Default Arguments for V1 Engine."""
 

vllm/multimodal/parse.py

@@ -13,6 +13,7 @@
     Optional,
     TypeVar,
     Union,
+    cast,
 )
 
 import numpy as np
@@ -366,7 +367,8 @@ def _is_embeddings(
         if isinstance(data, torch.Tensor):
             return data.ndim == 3
         if is_list_of(data, torch.Tensor):
-            return data[0].ndim == 2
+            tensors = cast(list[torch.Tensor], data)
+            return tensors[0].ndim == 2
 
         return False
 
@@ -434,7 +436,7 @@ def _parse_audio_data(
         elif isinstance(data, (np.ndarray, torch.Tensor)):
             data_items = [elem for elem in data]
         else:
-            data_items = data
+            data_items = data  # type: ignore[assignment]
 
         new_audios = list[np.ndarray]()
         for data_item in data_items:
@@ -498,7 +500,7 @@ def _parse_video_data(
         elif isinstance(data, tuple) and len(data) == 2:
             data_items = [data]
         else:
-            data_items = data
+            data_items = data  # type: ignore[assignment]
 
         new_videos = list[tuple[np.ndarray, Optional[dict[str, Any]]]]()
         metadata_lst: list[Optional[dict[str, Any]]] = []

vllm/transformers_utils/tokenizers/mistral.py

@@ -350,16 +350,17 @@ def __call__(
         # For list[str], original prompt text
         if is_list_of(text, str):
             input_ids_: list[list[int]] = []
-            for p in text:
+            text_strs = cast(list[str], text)
+            for p in text_strs:
                 each_input_ids = self.encode_one(p, truncation, max_length)
                 input_ids_.append(each_input_ids)
             input_ids = input_ids_
         # For list[int], apply chat template output, already tokens.
         elif is_list_of(text, int):
-            input_ids = text
+            input_ids = cast(list[int], text)
         # For str, single prompt text
         else:
-            input_ids = self.encode_one(text, truncation, max_length)
+            input_ids = self.encode_one(cast(str, text), truncation, max_length)
         return BatchEncoding({"input_ids": input_ids})
 
     def get_vocab(self) -> dict[str, int]: