李沐笔记（池化层）

 
 
 
 
import torch
from torch import nn
from d2l import torch as d2l

# 实现池化层的正向传播
def pool2d(X, pool_size, mode='max'):
p_h, p_w = pool_size
Y = torch.zeros((X.shape[0] - p_h + 1, X.shape[1] - p_w + 1))
for i in range(Y.shape[0]):
for j in range(Y.shape[1]):
if mode == 'max':
Y[i, j] = X[i:i + p_h, j:j + p_w].max()
elif mode == 'avg':
Y[i, j] = X[i:i + p_h, j:j + p_w].mean()
return Y

李沐笔记（池化层）最先出现在Python成神之路。