[Bugfix] Make EngineArgs use named arguments for config construction (#5285)

vllm/engine/arg_utils.py

@@ -619,34 +619,48 @@ class EngineArgs:
                 "BitsAndBytes load format and QLoRA adapter only support "
                 f"'bitsandbytes' quantization, but got {self.quantization}")
 
-        device_config = DeviceConfig(self.device)
+        device_config = DeviceConfig(device=self.device)
         model_config = ModelConfig(
-            self.model, self.tokenizer, self.tokenizer_mode,
-            self.trust_remote_code, self.dtype, self.seed, self.revision,
-            self.code_revision, self.rope_scaling, self.tokenizer_revision,
-            self.max_model_len, self.quantization,
-            self.quantization_param_path, self.enforce_eager,
-            self.max_context_len_to_capture, self.max_seq_len_to_capture,
-            self.max_logprobs, self.disable_sliding_window,
-            self.skip_tokenizer_init, self.served_model_name)
-        cache_config = CacheConfig(self.block_size,
-                                   self.gpu_memory_utilization,
-                                   self.swap_space, self.kv_cache_dtype,
-                                   self.num_gpu_blocks_override,
-                                   model_config.get_sliding_window(),
-                                   self.enable_prefix_caching)
+            model=self.model,
+            tokenizer=self.tokenizer,
+            tokenizer_mode=self.tokenizer_mode,
+            trust_remote_code=self.trust_remote_code,
+            dtype=self.dtype,
+            seed=self.seed,
+            revision=self.revision,
+            code_revision=self.code_revision,
+            rope_scaling=self.rope_scaling,
+            tokenizer_revision=self.tokenizer_revision,
+            max_model_len=self.max_model_len,
+            quantization=self.quantization,
+            quantization_param_path=self.quantization_param_path,
+            enforce_eager=self.enforce_eager,
+            max_context_len_to_capture=self.max_context_len_to_capture,
+            max_seq_len_to_capture=self.max_seq_len_to_capture,
+            max_logprobs=self.max_logprobs,
+            disable_sliding_window=self.disable_sliding_window,
+            skip_tokenizer_init=self.skip_tokenizer_init,
+            served_model_name=self.served_model_name)
+        cache_config = CacheConfig(
+            block_size=self.block_size,
+            gpu_memory_utilization=self.gpu_memory_utilization,
+            swap_space=self.swap_space,
+            cache_dtype=self.kv_cache_dtype,
+            num_gpu_blocks_override=self.num_gpu_blocks_override,
+            sliding_window=model_config.get_sliding_window(),
+            enable_prefix_caching=self.enable_prefix_caching)
         parallel_config = ParallelConfig(
-            self.pipeline_parallel_size,
-            self.tensor_parallel_size,
-            self.worker_use_ray,
-            self.max_parallel_loading_workers,
-            self.disable_custom_all_reduce,
-            TokenizerPoolConfig.create_config(
+            pipeline_parallel_size=self.pipeline_parallel_size,
+            tensor_parallel_size=self.tensor_parallel_size,
+            worker_use_ray=self.worker_use_ray,
+            max_parallel_loading_workers=self.max_parallel_loading_workers,
+            disable_custom_all_reduce=self.disable_custom_all_reduce,
+            tokenizer_pool_config=TokenizerPoolConfig.create_config(
                 self.tokenizer_pool_size,
                 self.tokenizer_pool_type,
                 self.tokenizer_pool_extra_config,
             ),
-            self.ray_workers_use_nsight,
+            ray_workers_use_nsight=self.ray_workers_use_nsight,
             distributed_executor_backend=self.distributed_executor_backend)
 
         speculative_config = SpeculativeConfig.maybe_create_spec_config(
@@ -665,10 +679,10 @@ class EngineArgs:
         )
 
         scheduler_config = SchedulerConfig(
-            self.max_num_batched_tokens,
-            self.max_num_seqs,
-            model_config.max_model_len,
-            self.use_v2_block_manager,
+            max_num_batched_tokens=self.max_num_batched_tokens,
+            max_num_seqs=self.max_num_seqs,
+            max_model_len=model_config.max_model_len,
+            use_v2_block_manager=self.use_v2_block_manager,
             num_lookahead_slots=(self.num_lookahead_slots
                                  if speculative_config is None else
                                  speculative_config.num_lookahead_slots),