This function is more numerically stable than log(sum(exp(x))). It avoids
overflows caused by taking the exp of large inputs and underflows caused by
taking the log of small inputs.

k_logsumexp(x, axis = NULL, keepdims = FALSE)

## Arguments

x |
A tensor or variable. |

axis |
An integer, the axis to reduce over (axis indexes are 1-based). |

keepdims |
A boolean, whether to keep the dimensions or not. If
`keepdims` is `FALSE` , the rank of the tensor is reduced by 1. If
`keepdims` is `TRUE` , the reduced dimension is retained with length 1. |

## Value

The reduced tensor.

## Keras Backend

This function is part of a set of Keras backend functions that enable
lower level access to the core operations of the backend tensor engine
(e.g. TensorFlow, CNTK, Theano, etc.).

You can see a list of all available backend functions here:
https://keras.rstudio.com/articles/backend.html#backend-functions.