pytorch-填充和步幅

import torch
from torch import nn

def comp_conv2d(conv2d,X):
    X=X.reshape((1,1)+X.shape)
    Y=conv2d(X)
    return Y.reshape(Y.shape[2:])

conv2d=nn.Conv2d(1,1,kernel_size=3,padding=1)  #上下左右各加一行.
X=torch.rand(size=(8,8))
print(comp_conv2d(conv2d,X).shape)

conv2d=nn.Conv2d(1,1,kernel_size=(5,3),padding=(2,1))
print(comp_conv2d(conv2d,X).shape)
#核为3*3：（8-3+1+2）)/2
conv2d=nn.Conv2d(1,1,kernel_size=3,padding=1,stride=2)
print(comp_conv2d(conv2d,X).shape)

conv2d=nn.Conv2d(1,1,kernel_size=(3,5),padding=(0,1),stride=(3,4))
print(comp_conv2d(conv2d,X).shape)

输出：

torch.Size([8, 8])
torch.Size([8, 8])
torch.Size([4, 4])
torch.Size([2, 2])