nn_soft_margin_loss function

Soft margin loss

Creates a criterion that optimizes a two-class classification logistic loss between input tensor $x$ and target tensor $y$

(containing 1 or -1).

nn_soft_margin_loss(reduction = "mean")

Arguments

• 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.

Details

Shape

• Input: $(*)$ where $*$ means, any number of additional dimensions
• Target: $(*)$, same shape as the input
• Output: scalar. If reduction is 'none', then same shape as the input