MSELoss ( 均 值 损 失 ) pytorch:
def MSELoss(pred,target):
return (pred-target)**2
代码示例:
import torch
import torch.nn as nn
a = torch.tensor([[1, 2], [3, 4]], dtype=torch.float32)
b = torch.tensor([[3, 5], [8, 6]], dtype=torch.float32)
loss_fn1 = torch.nn.MSELoss(reduction='none')
loss1 = loss_fn1(a, b)
print(loss1) # 输出结果:tensor([[ 4., 9.],
# [25., 4.]])
loss_fn2 = torch.nn.MSELoss(reduction='sum')
loss2 = loss_fn2(a, b)
print(loss2) # 输出结果:tensor(42.)
loss_fn3 = torch.nn.MSELoss(reduction='mean')
loss3 = loss_fn3(a, b)
print(loss3) # 输出结果:tensor(10.5000)