From 38dd2ac13d10ae7ac635c862b96cfdcea74b8f54 Mon Sep 17 00:00:00 2001
From: xffxff <1247714429@qq.com>
Date: Tue, 19 Nov 2024 08:14:30 +0000
Subject: [PATCH] make format happy

---
 aria/vllm/aria.py | 20 ++++++++++----------
 1 file changed, 10 insertions(+), 10 deletions(-)

diff --git a/aria/vllm/aria.py b/aria/vllm/aria.py
index 7c0c31e..6bc666b 100644
--- a/aria/vllm/aria.py
+++ b/aria/vllm/aria.py
@@ -26,15 +26,14 @@
 from transformers import LlamaConfig
 from transformers.utils import logging
 from vllm.attention import AttentionMetadata
-from vllm.config import CacheConfig, LoRAConfig, MultiModalConfig
-from vllm.config import VllmConfig
+from vllm.config import CacheConfig, LoRAConfig, VllmConfig
 from vllm.distributed import (
     get_pp_group,
     get_tensor_model_parallel_rank,
     get_tensor_model_parallel_world_size,
     tensor_model_parallel_all_reduce,
 )
-from vllm.inputs import INPUT_REGISTRY, LLMInputs, token_inputs
+from vllm.inputs import INPUT_REGISTRY, token_inputs
 from vllm.model_executor.layers.fused_moe import fused_moe
 from vllm.model_executor.layers.layernorm import RMSNorm
 from vllm.model_executor.layers.logits_processor import LogitsProcessor
@@ -338,8 +337,8 @@ def __init__(
         prefix: str = "",
     ) -> None:
         nn.Module.__init__(self)
-        
-        # FIXME(zhoufan): this is a hack to avoid the error: AttributeError: 'AriaMoELMModel' object has no attribute 'do_not_compile'. 
+
+        # FIXME(zhoufan): this is a hack to avoid the error: AttributeError: 'AriaMoELMModel' object has no attribute 'do_not_compile'.
         self.do_not_compile = True
 
         self.config = config
@@ -692,7 +691,12 @@ def input_processor(ctx, llm_inputs):
         repeat_count=image_feature_sizes,
     )
 
-    return token_inputs(prompt_token_ids=new_token_ids, prompt=new_prompt, multi_modal_data=multi_modal_data, multi_modal_placeholders={"image": ranges})
+    return token_inputs(
+        prompt_token_ids=new_token_ids,
+        prompt=new_prompt,
+        multi_modal_data=multi_modal_data,
+        multi_modal_placeholders={"image": ranges},
+    )
 
 
 # adapted from transformers.models.llava.modeling_llava.LlavaForConditionalGeneration
@@ -711,10 +715,6 @@ def __init__(
         self,
         vllm_config: VllmConfig,
         prefix: str = "",
-        # config: AriaConfig,
-        # multimodal_config: MultiModalConfig,
-        # cache_config: Optional[CacheConfig] = None,
-        # quant_config: Optional[QuantizationConfig] = None,
     ):
         super().__init__()
         config = vllm_config.model_config.hf_config