# torch_logsumexp: Logsumexp In torch: Tensors and Neural Networks with 'GPU' Acceleration

Logsumexp

## Usage

 `1` ```torch_logsumexp(self, dim, keepdim = FALSE) ```

## Arguments

 `self` (Tensor) the input tensor. `dim` (int or tuple of ints) the dimension or dimensions to reduce. `keepdim` (bool) whether the output tensor has `dim` retained or not.

## logsumexp(input, dim, keepdim=False, out=NULL)

Returns the log of summed exponentials of each row of the `input` tensor in the given dimension `dim`. The computation is numerically stabilized.

For summation index j given by `dim` and other indices i, the result is

\mbox{logsumexp}(x)_{i} = \log ∑_j \exp(x_{ij})

If `keepdim` is `TRUE`, the output tensor is of the same size as `input` except in the dimension(s) `dim` where it is of size 1. Otherwise, `dim` is squeezed (see `torch_squeeze`), resulting in the output tensor having 1 (or `len(dim)`) fewer dimension(s).

## Examples

 ```1 2 3 4 5``` ```if (torch_is_installed()) { a = torch_randn(c(3, 3)) torch_logsumexp(a, 1) } ```

torch documentation built on Oct. 7, 2021, 9:22 a.m.