MSELoss() 函数「建议收藏」

def MSELoss(pred,target):
    return (pred-target)**2

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)