from torch import nn
from torch.nn import functional
import torch


class Entropy_Loss(nn.Module):
    def __init__(self):
        super(Entropy_Loss, self).__init__()

    def forward(self, outputs, labels):
        # 範例: 使用均方誤差作為損失計算
        # outputs = torch.argmax(outputs, 1)
        outputs = torch.tensor(outputs, dtype=torch.float32).clone().detach()
        labels = torch.tensor(labels, dtype=torch.float32).clone().detach()

        loss = functional.cross_entropy(outputs, labels)
        return torch.tensor(loss, requires_grad = True).clone().detach().requires_grad_(True)