2021-10-12-torch.nn.linear

参考：
https://zhuanlan.zhihu.com/p/152198144

import torch

x = torch.randn(128, 20)  # 输入的维度是（128，20）
m = torch.nn.Linear(20, 30)  # 20,30是指维度
output = m(x)
print('m.weight.shape:\n ', m.weight.shape)
print('m.bias.shape:\n', m.bias.shape)
print('output.shape:\n', output.shape)

# ans = torch.mm(input,torch.t(m.weight))+m.bias 等价于下面的
ans = torch.mm(x, m.weight.t()) + m.bias   
print('ans.shape:\n', ans.shape)

print(torch.equal(ans, output))


m.weight.shape:
  torch.Size([30, 20])
m.bias.shape:
 torch.Size([30])
output.shape:
 torch.Size([128, 30])
ans.shape:
 torch.Size([128, 30])
True

为什么 m.weight.shape = (30,20)?

答：因为线性变换的公式是：

image

先生成一个（30，20）的weight，实际运算中再转置，这样就能和x做矩阵乘法了