Machine learning 模型未学习：自定义激活功能和/或自定义丢失功能存在问题

当我训练我的模型时，这就是我所拥有的（我打印了损失函数、我的目标和模型的输出）：

你知道为什么我的模型不学习吗？因为我的数据是好的，所以激活功能或丢失一定有问题。事实上，我已经在TensorFlow上创建了相同的模型，并且可以正常工作

class QuaternionLoss(torch.nn.Module):
    def __init__(self):
        super(QuaternionLoss, self).__init__()
        
    def forward(self, output, target):
        loss = 100 * (1 - torch.dot(output.squeeze(0), target.squeeze(0)))
        return loss

class LinearNormalized(torch.nn.Module):
    def __init__(self):
        super(LinearNormalized, self).__init__() # init the class 
    
    def forward(self, x):
        return linear_normalized(x)

class VGGOrientation(torch.nn.Module):
    def __init__(self):
        super(VGGOrientation, self).__init__()
        self.model_vgg_orientation = torchvision.models.vgg16(pretrained=True)
        self.model_vgg_orientation.classifier = torch.nn.Sequential(
            torch.nn.Linear(25088, 256),
            torch.nn.ReLU(inplace=True),
            torch.nn.Linear(256, 64),
            torch.nn.ReLU(inplace=True), 
            torch.nn.Linear(64, 2),
            LinearNormalized()
        )

    def forward(self, x):
        output_orientation = self.model_vgg_orientation(x)
        return output_orientation