[mypy] Add mypy type annotation part 1 (#4006)

vllm/transformers_utils/config.py

@@ -2,7 +2,8 @@ from typing import Dict, Optional
 
 from transformers import AutoConfig, PretrainedConfig
 
-from vllm.transformers_utils.configs import *
+from vllm.transformers_utils.configs import (ChatGLMConfig, DbrxConfig,
+                                             JAISConfig, MPTConfig, RWConfig)
 
 _CONFIG_REGISTRY: Dict[str, PretrainedConfig] = {
     "chatglm": ChatGLMConfig,

vllm/transformers_utils/detokenizer.py

@@ -168,8 +168,8 @@ def _convert_tokens_to_string_with_added_encoders(
     # NOTE(woosuk): The following code is slow because it runs a for loop over
     # the output_tokens. In Python, running a for loop over a list can be slow
     # even when the loop body is very simple.
-    sub_texts = []
-    current_sub_text = []
+    sub_texts: List[str] = []
+    current_sub_text: List[str] = []
     all_special_tokens = set(tokenizer.all_special_tokens)
     for token in output_tokens:
         if skip_special_tokens and token in all_special_tokens:
@@ -263,6 +263,7 @@ def detokenize_incrementally(
              tokenizer,
              all_input_ids[:-1],
              skip_special_tokens=skip_special_tokens)
+    assert prev_tokens is not None
 
     # If the new token id is out of bounds, return an empty string.
     if new_token_id >= len(tokenizer):
@@ -271,6 +272,8 @@ def detokenize_incrementally(
         # Put new_token_id in a list so skip_special_tokens is respected
         new_tokens = tokenizer.convert_ids_to_tokens(
             [new_token_id], skip_special_tokens=skip_special_tokens)
+        if isinstance(new_tokens, str):
+            new_tokens = [new_tokens]
     output_tokens = prev_tokens + new_tokens
 
     # If this is the first iteration, return all tokens.

vllm/transformers_utils/tokenizer.py

@@ -5,7 +5,7 @@ from transformers import (AutoTokenizer, PreTrainedTokenizer,
 
 from vllm.logger import init_logger
 from vllm.lora.request import LoRARequest
-from vllm.transformers_utils.tokenizers import *
+from vllm.transformers_utils.tokenizers import BaichuanTokenizer
 from vllm.utils import make_async
 
 logger = init_logger(__name__)
@@ -28,7 +28,7 @@ def get_cached_tokenizer(
     tokenizer_all_special_tokens = set(tokenizer.all_special_tokens)
     tokenizer_len = len(tokenizer)
 
-    class CachedTokenizer(tokenizer.__class__):
+    class CachedTokenizer(tokenizer.__class__):  # type: ignore
 
         @property
         def all_special_ids(self):