LogSoftmax
class torch.nn.LogSoftmax(dim=None)
Applies the \log(\text{Softmax}(x)) function to an n-dimensional
   input Tensor. The LogSoftmax formulation can be simplified as:
  \text{LogSoftmax}(x_{i}) = \log\left(\frac{\exp(x_i) }{ \sum_j
  \exp(x_j)} \right)

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

Parameters:
      dim (int) -- A dimension along which LogSoftmax will be
      computed.
Returns:
      a Tensor of the same dimension and shape as the input with
      values in the range [-inf, 0)
Return type:
      None
Examples:
  >>> m = nn.LogSoftmax(dim=1)
  >>> input = torch.randn(2, 3)
  >>> output = m(input)
