torch.logcumsumexp
torch.logcumsumexp(input, dim, *, out=None) -> Tensor
Returns the logarithm of the cumulative summation of the
   exponentiation of elements of "input" in the dimension "dim".
For summation index j given by dim and other indices i, the
   result is
     \text{logcumsumexp}(x)_{ij} = \log \sum\limits_{j=0}^{i}
     \exp(x_{ij})

Parameters:
      * input (Tensor) -- the input tensor.
  * **dim** (*int*) -- the dimension to do the operation over

Keyword Arguments:
      out (Tensor, optional) -- the output tensor.
Example:
  >>> a = torch.randn(10)
  >>> torch.logcumsumexp(a, dim=0)
  tensor([-0.42296738, -0.04462666,  0.86278635,  0.94622083,  1.05277811,
           1.39202815,  1.83525007,  1.84492621,  2.06084887,  2.06844475]))
