diff --git a/gpu_mnist_example/parallel_train.py b/gpu_mnist_example/parallel_train.py
index 4d2ac02..1f95d6f 100644
--- a/gpu_mnist_example/parallel_train.py
+++ b/gpu_mnist_example/parallel_train.py
@@ -43,10 +43,14 @@ WORKERS = 0   # dataloder线程数
 # 检查可用GPU数量
 if torch.cuda.device_count() < 2:
     raise RuntimeError("需要至少2块GPU，但当前只有 {} 块".format(torch.cuda.device_count()))
+else:
+    print('当前有 {} 块GPU'.format(torch.cuda.device_count()))  
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 # 2. 初始化模型并并行化
 model = Model().to(device)
+
+print('开始进行并行训练！')  
 model = nn.DataParallel(model, device_ids=[0, 1])  # 使用GPU 0和1
 
 optimizer = SGD(model.parameters(), lr=1e-1)