Multilabel_soft_margin_loss
Creates a criterion that optimizes a multi-label one-versus-all loss based on max-entropy, between input x and target y of size (N, C).
nnf_multilabel_soft_margin_loss( input, target, weight = NULL, reduction = "mean" )
input |
tensor (N,*) where ** means, any number of additional dimensions |
target |
tensor (N,*) , same shape as the input |
weight |
weight tensor to apply on the loss. |
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' |
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