tfp.stats.log_loosum_exp

Computes the log-leave-one-out-sum of exp(logx).

tfp.stats.log_loosum_exp(
    logx, axis=None, keepdims=False, name=None
)

Args
`logx`	Floating-type `Tensor` representing `log(x)` where `x` is some positive value.
`axis`	The dimensions to sum across. If `None` (the default), reduces all dimensions. Must be in the range `[-rank(logx), rank(logx)]`. Default value: `None` (i.e., reduce over all dims).
`keepdims`	If true, retains reduced dimensions with length 1. Default value: `False` (i.e., keep all dims in `log_sum_x`).
`name`	Python `str` name prefixed to Ops created by this function. Default value: `None` (i.e., `"log_loosum_exp"`).

Returns
`log_loosum_exp`	`Tensor` with same shape and dtype as `logx` representing the natural-log of the sum of `exp(logx)` except that the element `logx[i]` is removed.
`log_sum_x`	`logx.dtype` `Tensor` corresponding to the natural-log of the sum of `exp(logx)`. Has reduced shape of `logx` (per `axis` and `keepdims`).

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2023-11-21 UTC.

Args