dropblock torch

https://github.com/Randl/DropBlock-pytorch/blob/master/DropBlock.py

官方：

Block_size=7时，获得最高验证集准确性

对Keep_prob值进行线性下降方式（scheduling）可以获得更好效果

Resnet-50的第3，4个block加Drouout比只在第4个block加Drouout更有效

在Resnet-50的卷积层和skip connection都使用Drouout效果更好
 

  

   

    

     

    
    

     

      import torch
     
    
   

    

     

    
    

     

      import torch.nn.functional as F
     
    
   

    

     

    
    

     

      from torch import nn
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      class DropBlock2D(nn.Module):
     
    
   

    

     

    
    

     
 r"""Randomly zeroes spatial blocks of the input tensor.
     
    
   

    

     

    
    

     

       As described in the paper
     
    
   

    

     

    
    

     

       `DropBlock: A regularization method for convolutional networks`_ ,
     
    
   

    

     

    
    

     

       dropping whole blocks of feature map allows to remove semantic
     
    
   

    

     

    
    

     

       information as compared to regular dropout.
     
    
   

    

     

    
    

     

       Args:
     
    
   

    

     

    
    

     

       keep_prob (float, optional): probability of an element to be kept.
     
    
   

    

     

    
    

     

       Authors recommend to linearly decrease
     
    
  
 

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/105930439