Linting fixes

Signed-off-by: Flavia Beo <[email protected]>
flaviabeo · Oct 24, 2024 · 8dc6ed3 · 8dc6ed3
1 parent 8407ac7
commit 8dc6ed3
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Showing 6 changed files with 25 additions and 24 deletions.
diff --git a/tests/model_executor/test_model_load_with_params.py b/tests/model_executor/test_model_load_with_params.py
@@ -6,6 +6,7 @@
 MODEL_NAME = os.environ.get("MODEL_NAME", "BAAI/bge-base-en-v1.5")
 REVISION = os.environ.get("REVISION", "main")
 
+
 def test_model_loading_with_params(vllm_runner):
     """
     Test parameter weight loading with tp>1.

diff --git a/vllm/config.py b/vllm/config.py
@@ -112,8 +112,8 @@ class ModelConfig:
             can not be gathered from the vllm arguments. 
         config_format: The config format which shall be loaded.
             Defaults to 'auto' which defaults to 'hf'.
-        pooling_config:  pooling and normalize config from the model - only applies 
-            to sentence-transformers models. 
+        pooling_config:  pooling and normalize config from the model - 
+            only applies to sentence-transformers models. 
         bert_config: tokenizationconfiguration dictionary for a given 
             Sentence Transformer BERT model.
         mm_processor_kwargs: Arguments to be forwarded to the model's processor
@@ -180,7 +180,7 @@ def __init__(self,
                                     config_format)
         self.hf_text_config = get_hf_text_config(self.hf_config)
         self.pooling_config = self.get_pooling_config()
-        self.bert_config = self._get_bert_config() 
+        self.bert_config = self._get_bert_config()
         self.do_lower_case = self._get_bert_config()
         self.hf_image_processor_config = get_hf_image_processor_config(
             self.model, revision)

diff --git a/vllm/engine/llm_engine.py b/vllm/engine/llm_engine.py
@@ -293,7 +293,7 @@ def __init__(
             model_config.pooling_config.pooling_type,
             model_config.pooling_config.normalize,
             model_config.chat_template_text_format,
-            model_config.mm_processor_kwargs,)
+            model_config.mm_processor_kwargs)
         # TODO(woosuk): Print more configs in debug mode.
         self.model_config = model_config
         self.cache_config = cache_config

diff --git a/vllm/model_executor/model_loader/loader.py b/vllm/model_executor/model_loader/loader.py
@@ -148,17 +148,18 @@ def _get_model_initialization_kwargs(
     return extra_kwargs
 
 
-def build_model(model_class: Type[nn.Module], hf_config: PretrainedConfig,
+def build_model(model_class: Type[nn.Module],
+                hf_config: PretrainedConfig,
                 cache_config: Optional[CacheConfig],
-                quant_config: Optional[QuantizationConfig], *,
+                quant_config: Optional[QuantizationConfig],
+                *,
                 lora_config: Optional[LoRAConfig],
                 multimodal_config: Optional[MultiModalConfig],
                 scheduler_config: Optional[SchedulerConfig],
                 pooling_config: Optional[PoolingConfig] = None) -> nn.Module:
     extra_kwargs = _get_model_initialization_kwargs(model_class, lora_config,
                                                     multimodal_config,
-                                                    scheduler_config
-                                                    )
+                                                    scheduler_config)
 
     return model_class(config=hf_config,
                        cache_config=cache_config,
@@ -176,16 +177,15 @@ def _initialize_model(
     """Initialize a model with the given configurations."""
     model_class, _ = get_model_architecture(model_config)
 
-    return build_model(
-        model_class,
-        model_config.hf_config,
-        cache_config=cache_config,
-        quant_config=_get_quantization_config(model_config, load_config),
-        lora_config=lora_config,
-        multimodal_config=model_config.multimodal_config,
-        scheduler_config=scheduler_config,
-        pooling_config=model_config.pooling_config
-    )
+    return build_model(model_class,
+                       model_config.hf_config,
+                       cache_config=cache_config,
+                       quant_config=_get_quantization_config(
+                           model_config, load_config),
+                       lora_config=lora_config,
+                       multimodal_config=model_config.multimodal_config,
+                       scheduler_config=scheduler_config,
+                       pooling_config=model_config.pooling_config)
 
 
 class BaseModelLoader(ABC):

diff --git a/vllm/transformers_utils/config.py b/vllm/transformers_utils/config.py
@@ -328,10 +328,8 @@ def get_sentence_transformer_tokenizer_config(model, revision='main'):
             "sentence_albert_config.json",
             "sentence_xlm-roberta_config.json",
             "sentence_xlnet_config.json",
-        ]:
-        bert_dict = get_hf_file_to_dict(config_name, 
-                                        model,
-                                        revision)
+    ]:
+        bert_dict = get_hf_file_to_dict(config_name, model, revision)
         if bert_dict:
             break
 

diff --git a/vllm/transformers_utils/tokenizer_group/__init__.py b/vllm/transformers_utils/tokenizer_group/__init__.py
@@ -25,8 +25,10 @@ def init_tokenizer_from_configs(model_config: ModelConfig,
                        trust_remote_code=model_config.trust_remote_code,
                        revision=model_config.tokenizer_revision)
 
-    if model_config.bert_config is not None and "do_lower_case" in model_config.bert_config:
-        init_kwargs["do_lower_case"] = model_config.bert_config["do_lower_case"]
+    if (model_config.bert_config is not None
+            and "do_lower_case" in model_config.bert_config):
+        init_kwargs["do_lower_case"] = model_config.bert_config[
+            "do_lower_case"]
 
     return get_tokenizer_group(parallel_config.tokenizer_pool_config,
                                **init_kwargs)