the output will be divided by the number of elements in the
        output, "'sum'": the output will be summed. Note:
        "size_average" and "reduce" are in the process of being
        deprecated, and in the meantime, specifying either of those
        two args will override "reduction". Default: "'mean'"
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:
  >>> m = nn.Sigmoid()
  >>> loss = nn.BCELoss()
  >>> input = torch.randn(3, requires_grad=True)
  >>> target = torch.empty(3).random_(2)
  >>> output = loss(m(input), target)
  >>> output.backward()
