
pos_weight (Tensor, optional) -- a weight of
        positive examples. Must be a vector with length equal to the
        number of classes.

Shape:
         * Input: (*), where * means any number of dimensions.
     * Target: (*), same shape as the input.

     * Output: scalar. If "reduction" is "'none'", then (*), same
       shape as input.

  Examples:

     >>> loss = nn.BCEWithLogitsLoss()
     >>> input = torch.randn(3, requires_grad=True)
     >>> target = torch.empty(3).random_(2)
     >>> output = loss(input, target)
     >>> output.backward()
