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'