Poisson negative log likelihood loss.
Usage
nnf_poisson_nll_loss(
input,
target,
log_input = TRUE,
full = FALSE,
eps = 1e-08,
reduction = "mean"
)
Arguments
- input
tensor (N,*) where ** means, any number of additional dimensions
- target
tensor (N,*) , same shape as the input
- log_input
if
TRUE
the loss is computed as \(\exp(\mbox{input}) - \mbox{target} * \mbox{input}\), ifFALSE
then loss is \(\mbox{input} - \mbox{target} * \log(\mbox{input}+\mbox{eps})\). Default:TRUE
.- full
whether to compute full loss, i. e. to add the Stirling approximation term. Default:
FALSE
.- eps
(float, optional) Small value to avoid evaluation of \(\log(0)\) when
log_input
=FALSE
. Default: 1e-8- reduction
(string, optional) – Specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. 'none': no reduction will be applied, 'mean': the sum of the output will be divided by the number of elements in the output, 'sum': the output will be summed. Default: 'mean'