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import torch
from torch import nn
from torch.nn import Sequential, Conv2d, MaxPool2d, Flatten, Linear
class MyNN(nn.Module):
def __init__(self):
super(MyNN, self).__init__()
# Sequential组织多个卷积等操作，相当于transforms中的compose
self.module1 = Sequential(
Conv2d(3, 32, 5, padding=2),
MaxPool2d(2),
Conv2d(32, 32, 5, padding=2),
MaxPool2d(2),
Conv2d(32, 64, 5, padding=2),
MaxPool2d(2),
Flatten(),
Linear(1024, 64),
Linear(64, 10)
)
def forward(self, x):
x = self.module1(x)
return x
mynn = MyNN()
print(mynn)
# https://www.w3cschool.cn/pytorch/pytorch-skug3bpf.html,查看张量的四个属性
# torch.ones函数返回全1的张量，tensor数据类型
# 生成一个64Batch，3Channel，32Width, 32Height的源数据
input = torch.ones((64, 3, 32, 32))
# 卷积池化等操作
output = mynn(input)
# 查看结果
print(output.shape)
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