nnf_margin_ranking_loss: Margin_ranking_loss

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

Margin_ranking_loss

Description

Creates a criterion that measures the loss given inputs x1 , x2 , two 1D mini-batch Tensors, and a label 1D mini-batch tensor y (containing 1 or -1).

Usage

nnf_margin_ranking_loss(input1, input2, target, margin = 0, reduction = "mean")

Arguments

input1	the first tensor
input2	the second input tensor
target	the target tensor
margin	Has a default value of 00 .
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.