pytorch 创建网络的8种方法

我会带着你远行 2023-03-12 09:19 4阅读 0赞

import torch.nn as nn
    from torch.nn import Conv2d
    from collections import OrderedDict
    
    
    class net1(nn.Module):
        def __init__(self):
            super(net1, self).__init__()
            self.conv1 = Conv2d(3, 3, 1)
            self.conv2 = Conv2d(3, 3, 1)
    
        def forward(self, x):
            return self.conv1(self.conv2(x))
    
    
    net1 = net1()
    print(net1)
    
    
    class net2(nn.Module):
        def __init__(self):
            super(net2, self).__init__()
            self.layer = nn.Sequential(
                Conv2d(3, 3, 1),
                Conv2d(3, 3, 1)
            )
    
        def forward(self, x):
            return self.conv1(self.conv2(x))
    
    
    net2 = net2()
    print(net2)
    
    
    class net3(nn.Module):
        def __init__(self):
            super(net3, self).__init__()
            self.layer = nn.Sequential(OrderedDict([
                ('conv1', Conv2d(3, 3, 1)),
                ('conv2', Conv2d(3, 3, 1))
            ]))
    
        def forward(self, x):
            return self.conv1(self.conv2(x))
    
    
    net3 = net3()
    print(net3)
    
    
    class net4(nn.Module):
        def __init__(self):
            super(net4, self).__init__()
            self.layer = nn.Sequential()  # nn.ModuleDict(), nn.ModuleList()
            self.layer.add_module('conv1', Conv2d(3, 3, 3))
            self.layer.add_module('conv2', Conv2d(3, 3, 3))
    
        def forward(self, x):
            return self.conv1(self.conv2(x))
    
    
    net4 = net4()
    print(net4)
    
    
    class net5(nn.Module):
        def __init__(self):
            super(net5, self).__init__()
            self.layer = nn.ModuleList([Conv2d(3, 3, 3), Conv2d(3, 3, 3)])
    
        def forward(self, x):
            return self.conv1(self.conv2(x))
    
    
    net5 = net5()
    print(net5)
    
    
    class net6(nn.Module):
        def __init__(self):
            super(net6, self).__init__()
            self.layer = nn.ModuleDict({
                'conv1': Conv2d(3, 3, 3),
                'conv2': Conv2d(3, 3, 3)
            })
    
        def forward(self, x):
            return self.conv1(self.conv2(x))
    
    
    net6 = net6()
    print(net6)
    
    
    class net7(nn.Module):
        def __init__(self):
            super(net7, self).__init__()
            self.layer = nn.ModuleDict([
                ('conv1', Conv2d(3, 3, 3)),
                ('conv2', Conv2d(3, 3, 3))
            ])
    
        def forward(self, x):
            return self.conv1(self.conv2(x))
    
    
    net7 = net7()
    print(net7)
    
    
    class net8(nn.Module):
        def __init__(self):
            super(net8, self).__init__()
            self.list = [Conv2d(3, 3, 3), Conv2d(3, 3, 3)]  # 不建议使用， 不会加入到Module中
    
        def forward(self, x):
            return self.list(x)
    
    
    model = net8()
    print(model)

**输出结果：**

net1(
      (conv1): Conv2d(3, 3, kernel_size=(1, 1), stride=(1, 1))
      (conv2): Conv2d(3, 3, kernel_size=(1, 1), stride=(1, 1))
    )
    net2(
      (layer): Sequential(
        (0): Conv2d(3, 3, kernel_size=(1, 1), stride=(1, 1))
        (1): Conv2d(3, 3, kernel_size=(1, 1), stride=(1, 1))
      )
    )
    net3(
      (layer): Sequential(
        (conv1): Conv2d(3, 3, kernel_size=(1, 1), stride=(1, 1))
        (conv2): Conv2d(3, 3, kernel_size=(1, 1), stride=(1, 1))
      )
    )
    net4(
      (layer): Sequential(
        (conv1): Conv2d(3, 3, kernel_size=(3, 3), stride=(1, 1))
        (conv2): Conv2d(3, 3, kernel_size=(3, 3), stride=(1, 1))
      )
    )
    net5(
      (layer): ModuleList(
        (0): Conv2d(3, 3, kernel_size=(3, 3), stride=(1, 1))
        (1): Conv2d(3, 3, kernel_size=(3, 3), stride=(1, 1))
      )
    )
    net6(
      (layer): ModuleDict(
        (conv1): Conv2d(3, 3, kernel_size=(3, 3), stride=(1, 1))
        (conv2): Conv2d(3, 3, kernel_size=(3, 3), stride=(1, 1))
      )
    )
    net7(
      (layer): ModuleDict(
        (conv1): Conv2d(3, 3, kernel_size=(3, 3), stride=(1, 1))
        (conv2): Conv2d(3, 3, kernel_size=(3, 3), stride=(1, 1))
      )
    )
    net8()
    
    Process finished with exit code 0