Nll_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 $K\ge 1$ in the case of K-dimensional loss.

target

$(N)$ where each value is $0\le \text{targets}[i]\le C-1$, or $(N,d_1,d_2,...,d_K)$ where $K\ge 1$ 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'