Multi-label Classification 用のロス比較2（全て同じ結果にはなる）

bce_losses_and_comparison.py

import torch
from torch import nn as nn
from torch import autograd as ag

data = ag.Variable(torch.Tensor(torch.randn([100, 100])))
labels = ag.Variable(torch.Tensor(torch.randn([100, 100])))

multi_label_soft_margin = nn.MultiLabelSoftMarginLoss()
print(multi_label_soft_margin(data, labels))

bce_with_logits = nn.BCEWithLogitsLoss()
print(bce_with_logits(data, labels))

bce = nn.BCELoss()
sigmoid = nn.Sigmoid()
print(bce(sigmoid(data), labels))