fix formatter

volcengine · Jan 27, 2025 · e265deb · e265deb
1 parent 6400075
commit e265deb
Showing 1 changed file with 14 additions and 13 deletions.
diff --git a/verl/workers/rollout/vllm_rollout/vllm_rollout.py b/verl/workers/rollout/vllm_rollout/vllm_rollout.py
@@ -89,19 +89,20 @@ def __init__(self, actor_module: nn.Module, config: DictConfig, tokenizer, model
 
         assert model_hf_config.max_position_embeddings >= config.prompt_length + config.response_length, \
             "model context length should be greater than total sequence length"
-        self.inference_engine = LLM(actor_module,
-                                    tokenizer=tokenizer,
-                                    model_hf_config=model_hf_config,
-                                    tensor_parallel_size=tensor_parallel_size,
-                                    dtype=config.dtype,
-                                    enforce_eager=config.enforce_eager,
-                                    gpu_memory_utilization=config.gpu_memory_utilization,
-                                    skip_tokenizer_init=False,
-                                    max_model_len=config.prompt_length + config.response_length,
-                                    load_format=config.load_format,
-                                    disable_log_stats=False,
-                                    max_num_batched_tokens=max_num_batched_tokens,
-                                    )
+        self.inference_engine = LLM(
+            actor_module,
+            tokenizer=tokenizer,
+            model_hf_config=model_hf_config,
+            tensor_parallel_size=tensor_parallel_size,
+            dtype=config.dtype,
+            enforce_eager=config.enforce_eager,
+            gpu_memory_utilization=config.gpu_memory_utilization,
+            skip_tokenizer_init=False,
+            max_model_len=config.prompt_length + config.response_length,
+            load_format=config.load_format,
+            disable_log_stats=False,
+            max_num_batched_tokens=max_num_batched_tokens,
+        )
 
         # Offload vllm model to reduce peak memory usage
         self.inference_engine.offload_model_weights()