nnf_binary_cross_entropy_with_logits: Binary_cross_entropy_with_logits

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

Binary_cross_entropy_with_logits

Description

Function that measures Binary Cross Entropy between target and output logits.

Usage

nnf_binary_cross_entropy_with_logits(
  input,
  target,
  weight = NULL,
  reduction = c("mean", "sum", "none"),
  pos_weight = NULL
)

Arguments

input	Tensor of arbitrary shape
target	Tensor of the same shape as input
weight	(Tensor, optional) a manual rescaling weight if provided it's repeated to match input tensor shape.
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'
pos_weight	(Tensor, optional) a weight of positive examples. Must be a vector with length equal to the number of classes.

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