Error in Inverse_Sigmoid_Loss ??

[JoyMaz222]

Hi, I was looking into the code and found some mismatch in Inverse_Sigmoid_Loss function.

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

	def forward(self, prediction, target, weight=None):
		trans_prediction = 1 / torch.sigmoid(target) - 1
		loss = F.l1_loss(trans_prediction, target, reduction='none')
		
		if weight is not None:
			loss = loss * weight

		return loss

This looks odd to me. trans_prediction is calculated from target and L1 loss is calculated between trans_prediction and target which doesn't make sense. variable prediction wasn't even used in this function. Any explanation for that ? Thanks