MSELoss ( 均 值 損 失 ) pytorch：

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

代碼示例：

import torch import torch.nn as nna = 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) # 輸出結(jié)果：tensor([[ 4., 9.],# [25., 4.]])loss_fn2 = torch.nn.MSELoss(reduction='sum') loss2 = loss_fn2(a, b) print(loss2) # 輸出結(jié)果：tensor(42.)loss_fn3 = torch.nn.MSELoss(reduction='mean') loss3 = loss_fn3(a, b) print(loss3) # 輸出結(jié)果：tensor(10.5000)

總結(jié)

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