Pytorch上下采样函数--interpolate

torch.nn的上下采样，只能是8的倍数，不能任意分辨率。

  

   

    

     

    
    

     

       self.upsample= nn.Upsample(scale_factor=2,mode='nearest', align_corners=None)#, mode='bilinear', align_corners=False)
     
    
   

    

     

    
    

     

       self.p3_downsample = nn.MaxPool2d(kernel_size=2)
     
    
  
 

enet下采样 

  

   

    

     

    
    

     

      class DownsamplingBottleneck(nn.Module):
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 def __init__(self,
     
    
   

    

     

    
    

     

       in_channels,
     
    
   

    

     

    
    

     

       out_channels,
     
    
   

    

     

    
    

     

       internal_ratio=4,
     
    
   

    

     

    
    

     

       return_indices=False,
     
    
   

    

     

    
    

     

       dropout_prob=0,
     
    
   

    

     

    
    

     

       bias=False,
     
    
   

    

     

    
    

     

       relu=True):
     
    
   

    

     

    
    

     

       super().__init__()
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 # Store parameters that are needed later
     
    
   

    

     

    
    

     

       self.return_indices = return_indices
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 # Check in the internal_scale parameter is within the expected range
     
    
   

    

     

    
    

     
 # [1, channels]
     
    
   

    

     

    
    

     
 if internal_ratio <= 1 or internal_ratio > in_channels:
     
    
   

    

     

    
    

     

       rais
     
    
  
 

文章来源: blog.csdn.net，作者：网奇，版权归原作者所有，如需转载，请联系作者。

原文链接：blog.csdn.net/jacke121/article/details/103976455