facebox retina

  

   

    

     

    
    

     

      # coding:utf-8
     
    
   

    

     

    
    

     

      import time
     
    
   

    

     

    
    

     

      import torch
     
    
   

    

     

    
    

     

      import torch.nn as nn
     
    
   

    

     

    
    

     

      import torch.nn.functional as F
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      class conv_bn_relu6(nn.Module):
     
    
   

    

     

    
    

     
    def __init__(self, nin, nout, kernel_size, stride, padding, bias=False):
     
    
   

    

     

    
    

     
        super(conv_bn_relu6, self).__init__()
     
    
   

    

     

    
    

     

              self.conv = nn.Conv2d(nin, nout, kernel_size=kernel_size, stride=stride, padding=padding, bias=bias)
     
    
   

    

     

    
    

     

              self.batch_norm = nn.BatchNorm2d(nout)
     
    
   

    

     

    
    

     

              self.relu = nn.ReLU6(True)
     
    
   

    

     

    
    

     
        # self.relu = mish.Mish()
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
    def forward(self, x):
     
    
   

    

     

    
    

     

              out = self.conv(x)
     
    
   

    

     

    
    

     

              out = self.batch_norm(out)
     
    
   

    

     

    
    

     

              out = self.relu(out)
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
        return out
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      def conv_bn_relu(in_channels, out_channels, kernel_size, stride=1, padding=0):
     
    
   

    

     

    
    

     

      	m0 = nn.Conv2d(in_channels, out_channels, kernel_size=kernel_size, padding=padding, stride=stride)
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      	m1 = nn.BatchNorm2d(out_channels)
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
	return nn.Sequential(m0, m1, nn.ReLU6(True))
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 
     
    
  
 

文章来源: blog.csdn.net，作者：AI视觉网奇，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/104595935