update model_name

gcu_mnist_example/README.md

@@ -23,7 +23,7 @@ Torch_MNIST_Example_Model模型可从本项目的模型目录中引用，[预训
 * Torch_MNIST_Example_Model模型的目录结构如下：
 
   > Torch_MNIST_Example_Model
-  > ├── mnist_epoch1_0.76.pkl
+  > ├── mnist_epoch1.pkl
   >
 
 ## 二. 如何在云脑上获取代码路径，数据集路径，预训练模型路径，输出路径

gcu_mnist_example/train.py

@@ -13,7 +13,7 @@ If there are Chinese comments in the code，please add at the beginning：
 
 预训练模型文件夹结构是：
 Torch_MNIST_Example_Model
-├── mnist_epoch1_0.76.pkl  
+├── mnist_epoch1.pkl  
 
 '''
 
@@ -88,8 +88,8 @@ if __name__ == '__main__':
     print('epoch_size is:{}'.format(epochs))
 
     # 如果有保存的模型，则加载模型，并在其基础上继续训练
-    if os.path.exists(os.path.join(Torch_MNIST_Example_Model_path, "mnist_epoch1_0.76.pkl")):
-        checkpoint = torch.load(os.path.join(Torch_MNIST_Example_Model_path, "mnist_epoch1_0.76.pkl"))
+    if os.path.exists(os.path.join(Torch_MNIST_Example_Model_path, "mnist_epoch1.pkl")):
+        checkpoint = torch.load(os.path.join(Torch_MNIST_Example_Model_path, "mnist_epoch1.pkl"))
         model.load_state_dict(checkpoint['model'])
         optimizer.load_state_dict(checkpoint['optimizer'])
         start_epoch = checkpoint['epoch']

gpgpu_mnist_example/README.md

@@ -23,7 +23,7 @@ Torch_MNIST_Example_Model模型可从本项目的模型目录中引用，[预训
 * Torch_MNIST_Example_Model模型的目录结构如下：
 
   > Torch_MNIST_Example_Model
-  > ├── mnist_epoch1_0.76.pkl
+  > ├── mnist_epoch1.pkl
   >
 
 ## 二. 如何在云脑上获取代码路径，数据集路径，预训练模型路径，输出路径

gpgpu_mnist_example/inference.py

@@ -13,7 +13,7 @@ If there are Chinese comments in the code，please add at the beginning：
 
 预训练模型文件夹结构是：
 Torch_MNIST_Example_Model
-├── mnist_epoch1_0.76.pkl  
+├── mnist_epoch1.pkl  
 
 '''
 from model import Model

gpgpu_mnist_example/train.py

@@ -12,7 +12,7 @@ If there are Chinese comments in the code，please add at the beginning：
 
 预训练模型文件夹结构是：
 Torch_MNIST_Example_Model
-├── mnist_epoch1_0.76.pkl
+├── mnist_epoch1.pkl
 
 '''
 
@@ -99,8 +99,8 @@ if __name__ == '__main__':
     test_loader = DataLoader(test_dataset, batch_size=batch_size)
 
     #如果有保存的模型，则加载模型，并在其基础上继续训练
-    if os.path.exists(os.path.join(Torch_MNIST_Example_Model_path, "mnist_epoch1_0.76.pkl")):
-        checkpoint = torch.load(os.path.join(Torch_MNIST_Example_Model_path, "mnist_epoch1_0.76.pkl"))
+    if os.path.exists(os.path.join(Torch_MNIST_Example_Model_path, "mnist_epoch1.pkl")):
+        checkpoint = torch.load(os.path.join(Torch_MNIST_Example_Model_path, "mnist_epoch1.pkl"))
         model.load_state_dict(checkpoint['model'])
         optimizer.load_state_dict(checkpoint['optimizer'])
         start_epoch = checkpoint['epoch']

gpu_mnist_example/README.md

@@ -23,7 +23,7 @@ Torch_MNIST_Example_Model模型可从本项目的模型目录中引用，[预训
 * Torch_MNIST_Example_Model模型的目录结构如下：
 
   > Torch_MNIST_Example_Model
-  > ├── mnist_epoch1_0.76.pkl
+  > ├── mnist_epoch1.pkl
   >
 
 ## 二. 如何在云脑上获取代码路径，数据集路径，预训练模型路径，输出路径

gpu_mnist_example/inference.py

@@ -13,7 +13,7 @@ If there are Chinese comments in the code，please add at the beginning：
 
 预训练模型文件夹结构是：
 Torch_MNIST_Example_Model
-├── mnist_epoch1_0.76.pkl  
+├── mnist_epoch1.pkl  
 
 '''
 from model import Model

gpu_mnist_example/train.py

@@ -12,7 +12,7 @@ If there are Chinese comments in the code，please add at the beginning：
 
 预训练模型文件夹结构是：
 Torch_MNIST_Example_Model
-├── mnist_epoch1_0.76.pkl
+├── mnist_epoch1.pkl
 
 '''
 
@@ -99,8 +99,8 @@ if __name__ == '__main__':
     test_loader = DataLoader(test_dataset, batch_size=batch_size)
 
     #如果有保存的模型，则加载模型，并在其基础上继续训练
-    if os.path.exists(os.path.join(Torch_MNIST_Example_Model_path, "mnist_epoch1_0.76.pkl")):
-        checkpoint = torch.load(os.path.join(Torch_MNIST_Example_Model_path, "mnist_epoch1_0.76.pkl"))
+    if os.path.exists(os.path.join(Torch_MNIST_Example_Model_path, "mnist_epoch1.pkl")):
+        checkpoint = torch.load(os.path.join(Torch_MNIST_Example_Model_path, "mnist_epoch1.pkl"))
         model.load_state_dict(checkpoint['model'])
         optimizer.load_state_dict(checkpoint['optimizer'])
         start_epoch = checkpoint['epoch']