code format

Signed-off-by: MengqingCao <cmq0113@163.com>

Author: MengqingCao

tests/singlecard/test_accuracy.py

@@ -26,10 +26,7 @@
 import torch
 
 # pre-trained model path on Hugging Face.
-MODELS = [
-    "Qwen/Qwen2.5-0.5B-Instruct",
-    "deepseek-ai/DeepSeek-V2-Lite"
-]
+MODELS = ["Qwen/Qwen2.5-0.5B-Instruct", "deepseek-ai/DeepSeek-V2-Lite"]
 # Math reasoning benchmark (Grade School Math 8K).
 TASK = "gsm8k"
 # Answer validation requiring format consistency.
@@ -39,6 +36,7 @@
 # Baseline accuracy after VLLM optimization.
 EXPECTED_VALUE = 0.316
 
+
 def run_test(model_name, queue, more_args=None):
     model_args = f"pretrained={model_name},max_model_len=4096,trust_remote_code=True"
     if more_args is not None:
@@ -61,9 +59,13 @@ def run_test(model_name, queue, more_args=None):
 def test_lm_eval_accuracy(model, monkeypatch: pytest.MonkeyPatch):
     with monkeypatch.context():
         result_queue: Queue[float] = multiprocessing.Queue()
-        p = multiprocessing.Process(target=run_test, args=(model, result_queue, ))
+        p = multiprocessing.Process(target=run_test,
+                                    args=(
+                                        model,
+                                        result_queue,
+                                    ))
         p.start()
         p.join()
         result = result_queue.get()
         assert (EXPECTED_VALUE - RTOL < result < EXPECTED_VALUE + RTOL), \
-            f"Expected: {EXPECTED_VALUE}±{RTOL} | Measured: {result}"
+            f"Expected: {EXPECTED_VALUE}±{RTOL} | Measured: {result}"