Update: Edited to english in 'train.py' and 'test_module.py'.

test/test_module.py

@@ -29,66 +29,65 @@
 
 class TestModule(unittest.TestCase):
     """
-    方法测试
-
-    1. 运行unittest测试模块
-        * 运行unittest测试模块。使用python -m unittest <test_module>命令运行测试，<test_module>是测试文件的名称或相对路径
-        * 例如：python -m unittest test_module.py
-    2. 运行单个测试类或测试方法
-        * 使用 -k 选项指定要运行的测试类或方法的名称，TestModule是要运行的测试类的名称，test_noising是要运行的测试方法的名称
-        * 例如：python -m unittest -k TestModule.test_noising
-
-    If you want to run the unittest test module, please use 'python -m unittest <test_module.py>'.
-    If you want to run a single test class or test method, please use
-    'python -m unittest -k <TestModule or TestClass>.<test_function_name>'.
+    Test Module
+
+    1. Run the unittest test module
+        * If you want to run the unittest test module, please use 'python -m unittest <test_module.py>',
+        <test module> is the name or relative path of the test file
+        * e.g: python -m unittest test_module.py
+    2. Run a single test class or test method
+        * Use the -k option to specify the name of the test class or method to run,
+        where TestModule is the name of the test class to run and test_noising is the name of the test method to run.
+        * e.g: python -m unittest -k TestModule.test_noising
+
     """
 
     def test_num_cases(self):
         """
-        获取所有测试类名称
+        Get all test class names
         :return: None
         """
-        # 获取所有测试名
+        # Get all test class names
         test_cases = [method for method in dir(TestModule) if method.startswith('test_')]
         logger.info(test_cases)
-        # 打印测试方法名称
+        # Print all test class names
         for method_name in test_cases:
             logger.info(method_name)
 
     def test_noising(self):
         """
-        测试噪声
+        Test noising
         :return: None
         """
-        # 参数设置
+        # Parameter settings
         parser = argparse.ArgumentParser()
         parser.add_argument("--batch_size", type=int, default=1)
         parser.add_argument("--num_workers", type=int, default=2)
-        # 输入图像大小
+        # Input image size
         parser.add_argument("--image_size", type=int, default=640)
         parser.add_argument("--dataset_path", type=str, default="./noising_test")
 
         args = parser.parse_args()
         logger.info(msg=f"Input params: {args}")
 
-        # 开始测试
+        # Start test
         logger.info(msg="Start noising noising_test.")
         dataset_path = args.dataset_path
         save_path = os.path.join(dataset_path, "noise")
-        # 需要先清除noise文件夹下所有文件
+        # You need to clear all files under the 'noise' folder first
         delete_files(path=save_path)
         dataloader = get_dataset(args=args)
-        # 重新创建文件夹
+        # Recreate the folder
         os.makedirs(name=save_path, exist_ok=True)
-        # 扩散模型初始化
+        # Diffusion model initialization
         diffusion = Diffusion(device="cpu")
-        # 获取图像和噪声Tensor
+        # Get image and noise tensor
         image = next(iter(dataloader))[0]
         time = torch.Tensor([0, 50, 125, 225, 350, 500, 675, 999]).long()
 
-        # 给图片分别增加噪声
+        # Add noise to the image
         noised_image, _ = diffusion.noise_images(x=image, time=time)
-        # 保存噪声图片
+        # Save noise images
         save_image(tensor=noised_image.add(1).mul(0.5), fp=os.path.join(save_path, "noise.jpg"))
         logger.info(msg="Finish noising noising_test.")
 
@@ -113,7 +112,7 @@ def test_lr(self):
 
     def test_summary(self):
         """
-        测试模型结构
+        Test model structure
         :return: None
         """
         image_size = 64