pytorch mseloss测试

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两个分布一样，loss为0

#双方都有0，会减少loss

x值不用在 0-1之间

mseloss测试

import torch

conf_mask = torch.FloatTensor([0.0, 1.0, 0.0, 1.0, 1.0])
conf_data = torch.FloatTensor([0.1, 0.9, 0.0, 0.2, 0.2])

loss_fn = torch.nn.MSELoss()  # reduce=False, size_average=False)

x= loss_fn(conf_mask, conf_data).item()
print('-----0&1',x)
x1= loss_fn(conf_mask[conf_mask == 0], conf_data[conf_mask == 0]).item()
print('-------0',x1)
x2= loss_fn( conf_mask[conf_mask == 1], conf_data[conf_mask == 1]).item()
print('-------1',x2)

x2= loss_fn(torch.FloatTensor([0.0, 1.0, 0.0, 1.0, 1.0,0]), torch.FloatTensor([0.1, 0.9, 0.0, 0.2, 0.2,0])).item()
print('---add 0',x2)
x2= loss_fn(torch.FloatTensor([0.0, 1.0, 0.0, 1.0, 1.0,0,0]), torch.FloatTensor([0.1, 0.9, 0.0, 0.2, 0.2,0,0])).item()
print('add 0×2',x2)