[feat]添加qwen的lora单测

tests/lora/conftest.py

@@ -212,6 +212,11 @@ def phi2_lora_files():
     # return snapshot_download(repo_id="isotr0py/phi-2-test-sql-lora")
     return os.path.join(models_path_prefix, "isotr0py/phi-2-test-sql-lora")
 
+@pytest.fixture(scope="session")
+def qwen_lora_files():
+    # return snapshot_download(repo_id="jeeejeee/chatglm3-text2sql-spider")
+    return os.path.join(models_path_prefix, "customize/qwen-nl2dsl-lora")
+
 
 @pytest.fixture(scope="session")
 def long_context_lora_files_16k_1():

tests/lora/test_qwen.py

+from typing import List
+import os
+
+import vllm
+from vllm.lora.request import LoRARequest
+from ..utils import models_path_prefix
+
+MODEL_PATH = os.path.join(models_path_prefix, "Qwen/Qwen1.5-32B-Chat")
+
+PROMPT_TEMPLATE = """<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n<|im_start|>user\n{query}<|im_end|>\n<|im_start|>assistant\n"""
+
+
+def do_sample(llm: vllm.LLM, lora_path: str, lora_id: int) -> List[str]:
+    prompts = [
+        PROMPT_TEMPLATE.format(query="who are you?"),
+        PROMPT_TEMPLATE.format(
+            query="What is the capital city of China?"
+        ),
+        PROMPT_TEMPLATE.format(
+            query="What is the longest river in the world?"
+        ),
+    ]
+    print(prompts)
+    sampling_params = vllm.SamplingParams(temperature=0, max_tokens=256)
+    outputs = llm.generate(
+        prompts,
+        sampling_params,
+        lora_request=LoRARequest(str(lora_id), lora_id, lora_path)
+        if lora_id else None)
+    # Print the outputs.
+    generated_texts: List[str] = []
+    for output in outputs:
+        prompt = output.prompt
+        generated_text = output.outputs[0].text.strip()
+        generated_texts.append(generated_text)
+        print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
+    return generated_texts
+
+
+def test_qwen_lora(qwen_lora_files):
+    llm = vllm.LLM(MODEL_PATH,
+                   max_model_len=1024,
+                   enable_lora=True,
+                   max_loras=4,
+                   max_lora_rank=64,
+                   tensor_parallel_size=4,
+                   trust_remote_code=True)
+
+    expected_lora_output = [
+        "I am a large language model created by Alibaba Cloud. I am called Qwen.",
+        "The capital city of China is Beijing.",
+        "The longest river in the world is the Nile, located in Africa. It stretches for approximately 4,135 miles (6,650 kilometers) from its source in the highlands of Rwanda, through Tanzania, Uganda, South Sudan, Sudan, and Egypt, before emptying into the Mediterranean Sea. The Nile is famous for its historical and cultural significance, particularly in relation to ancient Egyptian civilization.",
+    ]
+
+    output1 = do_sample(llm, qwen_lora_files, lora_id=1)
+    for i in range(len(expected_lora_output)):
+        assert output1[i] == expected_lora_output[i]
+    output2 = do_sample(llm, qwen_lora_files, lora_id=2)
+    for i in range(len(expected_lora_output)):
+        assert output2[i] == expected_lora_output[i]