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 jjj given by dim and other indices iii, the result is logcumsumexp(x)ij=log∑k=0jexp(xik)\text{logcumsumexp}(x)_{ij} = \log \sum\limits_{k=0}^{j} \exp(x_{ik}) logcumsumexp(x)ij=logk=0∑jexp(xik) 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]))
