net.py

@@ -239,7 +239,7 @@ class DepthwiseSeparableConvBlock(nn.Module):
         return x
 
 class DetailNode(nn.Module):
-    def __init__(self,useBlock=1):
+    def __init__(self,useBlock=0):
         super(DetailNode, self).__init__()
         if useBlock == 0:
             self.theta_phi = DepthwiseSeparableConvBlock(inp=32, oup=32)

train.py

@@ -80,9 +80,6 @@ print(f"Clip gradient norm value: {clip_grad_norm_value}")
 print(f"Optimization step: {optim_step}")
 print(f"Optimization gamma: {optim_gamma}")
 
-# 控制台输入
-model_str = input("Model: ")
-print(f"Model: {model_str}")
 
 # Model
 device = 'cuda' if torch.cuda.is_available() else 'cpu'