torch: nnf_poisson_nll_loss – R documentation

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torch

nnf_poisson_nll_loss

Poisson_nll_loss

Description

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}, if `FALSE` 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'

torch

Tensors and Neural Networks with 'GPU' Acceleration

v0.3.0

MIT + file LICENSE

Authors

Daniel Falbel [aut, cre, cph], Javier Luraschi [aut], Dmitriy Selivanov [ctb], Athos Damiani [ctb], Christophe Regouby [ctb], Krzysztof Joachimiak [ctb], RStudio [cph]

Initial release

nnf_poisson_nll_loss

Description

Usage

Arguments

torch

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