nnf_poisson_nll_loss function

Poisson_nll_loss

Poisson_nll_loss

Poisson negative log likelihood loss.

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(\mboxinput)\mboxtarget\mboxinput\exp(\mbox{input}) - \mbox{target} * \mbox{input}, if FALSE then loss is \mboxinput\mboxtargetlog(\mboxinput+\mboxeps)\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)\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'
  • Maintainer: Daniel Falbel
  • License: MIT + file LICENSE
  • Last published: 2025-02-14