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Creates a criterion that optimizes a two-class classification logistic loss between input tensor x and target tensor y (containing 1 or -1).

Usage

nnf_soft_margin_loss(input, target, reduction = "mean")

Arguments

input

tensor (N,*) where ** means, any number of additional dimensions

target

tensor (N,*) , same shape as the input

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'