[fix]修复test_long_context中报错问题，单测依然无法通过，nv也是同样的问题

tests/lora/test_long_context.py

@@ -81,6 +81,9 @@ def generate(
     inputs: Tuple[str, SamplingParams, Optional[LoRARequest]],
 ):
     prompts, sampling_param, lora_request = inputs
+    max_model_len = llm.llm_engine.model_config.max_model_len
+    if len(prompts) >= max_model_len:
+        prompts = prompts[:max_model_len-1]
     outputs = llm.generate(prompts, sampling_param, lora_request=lora_request)
     return outputs[0].outputs[0].text.strip()
 
@@ -89,8 +92,11 @@ def batched_generate(
     llm: vllm.LLM,
     inputs: List[Tuple[str, SamplingParams, Optional[LoRARequest]]],
 ):
+    max_model_len = llm.llm_engine.model_config.max_model_len
     for input in inputs:
         prompt, sampling_param, lora_req = input
+        if len(prompt) >= max_model_len:
+            prompt = prompt[:max_model_len-1]
         # Add requests to the engine and run the engine
         llm._validate_and_add_requests(prompt,
                                        sampling_param,
@@ -111,7 +117,7 @@ def lora_llm(long_context_infos):
     llm = vllm.LLM("meta-llama/Llama-2-13b-chat-hf",
                    enable_lora=True,
                    max_num_seqs=16,
-                   max_loras=2,
+                   max_loras=8,
                    long_lora_scaling_factors=tuple(scaling_factors),
                    max_num_batched_tokens=4096 * 8,
                    tensor_parallel_size=4,

vllm/lora/request.py

@@ -83,7 +83,9 @@ class LoRARequest(
         and comparison lora adapter across engines.
         """
         return isinstance(value,
-                          self.__class__) and self.lora_name == value.lora_name
+                          self.__class__) and self.lora_name == value.lora_name and \
+                            self.lora_int_id == value.lora_int_id and \
+                            self.lora_path == value.lora_path
 
     def __hash__(self) -> int:
         """