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MindSpore/src/step3/train_net.py

@@ -157,10 +157,10 @@ def train_net(args, model, epoch_size, mnist_path, repeat_size, ckpoint_cb):
     print("============== Starting Training ==============")
     # load training dataset
     # 请在此添加代码完成本关任务
-    # **********Begin*********#
-    ##提示：完成网络的配置
+    #********** Begin *********#
+    ## 提示：完成网络的配置
 
-    # **********End**********#
+    #********** End **********#
 
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(description='MindSpore LeNet Example')
@@ -183,10 +183,10 @@ if __name__ == "__main__":
     # define the optimizer
     net_opt = nn.Momentum(network.trainable_params(), lr, momentum)
     # 请在此添加代码完成本关任务
-    # **********Begin*********#
-    ##提示：配置模型保存
+    #********** Begin *********#
+    ## 提示：配置模型保存
 
-    # **********End**********#
+    #********** End **********#
     # group layers into an object with training and evaluation features
     model = Model(network, net_loss, net_opt, metrics={"Accuracy": Accuracy()})