The negative log likelihood loss.
nnf_nll_loss( input, target, weight = NULL, ignore_index = -100, reduction = "mean" )
input | \((N, C)\) where |
---|---|
target | \((N)\) where each value is \(0 \leq \mbox{targets}[i] \leq C-1\), or \((N, d_1, d_2, ..., d_K)\) where \(K \geq 1\) for K-dimensional loss. |
weight | (Tensor, optional) a manual rescaling weight given to each class.
If given, has to be a Tensor of size |
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' |