torch: nnf_triplet_margin_with_distance_loss – R documentation

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torch

nnf_triplet_margin_with_distance_loss

Triplet margin with distance loss

Description

See nn_triplet_margin_with_distance_loss()

Usage

nnf_triplet_margin_with_distance_loss(
  anchor,
  positive,
  negative,
  distance_function = NULL,
  margin = 1,
  swap = FALSE,
  reduction = "mean"
)

Arguments

`anchor`	the anchor input tensor
`positive`	the positive input tensor
`negative`	the negative input tensor
`distance_function`	(callable, optional): A nonnegative, real-valued function that quantifies the closeness of two tensors. If not specified, `nn_pairwise_distance()` will be used. Default: `None`
`margin`	Default: 1.
`swap`	The distance swap is described in detail in the paper Learning shallow convolutional feature descriptors with triplet losses by V. Balntas, E. Riba et al. Default: `FALSE`.
`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

Tensors and Neural Networks with 'GPU' Acceleration

v0.3.0

MIT + file LICENSE

Authors

Daniel Falbel [aut, cre, cph], Javier Luraschi [aut], Dmitriy Selivanov [ctb], Athos Damiani [ctb], Christophe Regouby [ctb], Krzysztof Joachimiak [ctb], RStudio [cph]

Initial release

nnf_triplet_margin_with_distance_loss

Description

Usage

Arguments

torch

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