Pytorch 中怎么计算网络的参数量
本博文以 Dense Block 为例，Pytorch 为 DL 框架，*终计算模块参数量方法如下：
import torch
import torch.nn as nn
class Norm_Conv(nn.Module):
    def __init__(self,in_channel):
        super(Norm_Conv,self).__init__()
        self.layers = nn.Sequential(
            nn.Conv2d(in_channel,in_channel,3,1,1),
            nn.ReLU(True),
            nn.BatchNorm2d(in_channel),
            nn.Conv2d(in_channel,in_channel,3,1,1),
            nn.ReLU(True),
            nn.BatchNorm2d(in_channel),
            nn.Conv2d(in_channel,in_channel,3,1,1),
            nn.ReLU(True),
            nn.BatchNorm2d(in_channel))
    def forward(self,input):
        out = self.layers(input)
        return out
class DenseBlock_Norm(nn.Module):
    def __init__(self,in_channel):
        super(DenseBlock_Norm,self).__init__()
        self.first_layer = nn.Sequential(nn.Conv2d(in_channel,in_channel,3,1,1),
                                        nn.ReLU(True),
                                        nn.BatchNorm2d(in_channel))
        self.second_layer = nn.Sequential(nn.Conv2d(in_channel*2,in_channel,3,1,1),
                                          nn.ReLU(True),
                                          nn.BatchNorm2d(in_channel))
        self.third_layer = nn.Sequential(
            nn.Conv2d(in_channel*3,in_channel,3,1,1),
            nn.ReLU(True),
            nn.BatchNorm2d(in_channel))
    def forward(self,input):
        output1 = self.first_layer(input)
        output2 = self.second_layer(torch.cat((output1,input),dim=1))
        output3 = self.third_layer(torch.cat((input,output1,output2),dim=1))
        return output3
def count_param(model):
    param_count = 0
    for param in model.parameters():
        param_count += param.view(-1).size()[0]
    return param_count
# Get Parameter number of Network
in_channel = 128
net1 = Norm_Conv(in_channel)
print(‘Norm Conv parameter count is {}’.format(count_param(net1)))
net2 = DenseBlock_Norm(in_channel)
print(‘DenseBlock Norm parameter count is {}’.format(count_param(net2)))
*终结果如下
Norm Conv parameter count is 443520
DenseBlock Norm parameter count is 885888