nnf_multilabel_margin_loss: Multilabel_margin_loss

In torch: Tensors and Neural Networks with 'GPU' Acceleration

Multilabel_margin_loss

Description

Creates a criterion that optimizes a multi-class multi-classification hinge loss (margin-based loss) between input x (a 2D mini-batch Tensor) and output y (which is a 2D Tensor of target class indices).

Usage

nnf_multilabel_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'

torch documentation built on May 29, 2024, 9:54 a.m.