卷积神经网络

卷积神经网络
首先需要完成卷积网络的维度的推断
import torch
width, height = 28, 28
in_channle = 1
batch_size = 1
inputs = torch.randn(batch_size, in_channle,
                     width, height)
print(inputs.shape)
conv_lay1 = torch.nn.Conv2d(in_channels=1,
                            out_channels=10,
                            kernel_size=5)
output1 = conv_lay1(inputs)
print(output1.shape)
maxpool_lay = torch.nn.MaxPool2d(kernel_size=2)
output2 = maxpool_lay(output1)
print(output2.shape)
conv_lay2 = torch.nn.Conv2d(in_channels=10,
                            out_channels=20,
                            kernel_size=5)
output3 = conv_lay2(output2)
print(output3.shape)
output4 = maxpool_lay(output3)
print(output4.shape)
output5 = output4.view(1, -1)
linear_lay = torch.nn.Linear(320, 10)
output6 = linear_lay(output5)
print(output6.shape)
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原文链接：https://blog.csdn.net/qq_57943526/article/details/128227936