style: 使用ruff 工具优化代码风格

tests/trainer/test_early_stopping.py

@@ -5,31 +5,32 @@ from khaosz.config import *
 from khaosz.trainer import *
 from khaosz.data.serialization import Checkpoint
 
+
 def test_early_stopping_simulation(base_test_env, early_stopping_dataset):
     """Simulate early stopping behavior"""
-    
+
     schedule_config = CosineScheduleConfig(warmup_steps=10, total_steps=20)
-    
+
     optimizer_fn = lambda model: torch.optim.AdamW(model.parameters())
     scheduler_fn = lambda optim: SchedulerFactory.load(optim, schedule_config)
-    
+
     train_config = TrainConfig(
         strategy="seq",
         optimizer_fn=optimizer_fn,
         scheduler_fn=scheduler_fn,
         model=base_test_env["model"],
         dataset=early_stopping_dataset,
-        checkpoint_dir=base_test_env["test_dir"],
+        ckpt_dir=base_test_env["test_dir"],
         n_epoch=2,
         batch_size=2,
-        checkpoint_interval=1,
+        ckpt_interval=1,
         accumulation_steps=2,
         random_seed=np.random.randint(1e4),
-        device_type=base_test_env["device"]
+        device_type=base_test_env["device"],
     )
 
     trainer = Trainer(train_config)
-    
+
     # Should handle early stopping gracefully
     checkpoint = None
     try:
@@ -37,11 +38,11 @@ def test_early_stopping_simulation(base_test_env, early_stopping_dataset):
     except Exception:
         # Handle any exceptions
         pass
-    
+
     load_dir = os.path.join(base_test_env["test_dir"], "epoch_0_iter_2")
     checkpoint = Checkpoint.load(load_dir)
     trainer.train(checkpoint)
-    
+
     load_dir = os.path.join(base_test_env["test_dir"], "epoch_1_iter_10")
     checkpoint = Checkpoint.load(load_dir)
-    assert checkpoint.iteration == 10
+    assert checkpoint.iteration == 10