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nnf_nll_loss

Nll_loss

Description

The negative log likelihood loss.

Usage

nnf_nll_loss(
  input,
  target,
  weight = NULL,
  ignore_index = -100,
  reduction = "mean"
)

Arguments

input

(N, C) where C = number of classes or (N, C, H, W) in case of 2D Loss, or (N, C, d_1, d_2, ..., d_K) where K ≥q 1 in the case of K-dimensional loss.
target

(N) where each value is 0 ≤q \mbox{targets}[i] ≤q C-1, or (N, d_1, d_2, ..., d_K) where K ≥q 1 for K-dimensional loss.
weight

(Tensor, optional) a manual rescaling weight given to each class. If given, has to be a Tensor of size C
ignore_index

(int, optional) Specifies a target value that is ignored and does not contribute to the input gradient.
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

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