loss_triplet_hard: Triplet hard loss

In tfaddons: Interface to 'TensorFlow SIG Addons'

Description

Computes the triplet loss with hard negative and hard positive mining.

Usage

loss_triplet_hard(margin = 1, soft = FALSE, name = NULL, ...)

Arguments

margin	Float, margin term in the loss definition. Default value is 1.0.
soft	Boolean, if set, use the soft margin version. Default value is False.
name	Optional name for the op.
...	additional arguments to pass

Value

triplet_loss: float scalar with dtype of y_pred.

Examples

## Not run: 
model = keras_model_sequential() %>%
  layer_conv_2d(filters = 64, kernel_size = 2, padding='same', input_shape=c(28,28,1)) %>%
  layer_max_pooling_2d(pool_size=2) %>%
  layer_flatten() %>%
  layer_dense(256, activation= NULL) %>%
  layer_lambda(f = function(x) tf$math$l2_normalize(x, axis = 1L))

model %>% compile(
  optimizer = optimizer_lazy_adam(),
  # apply triplet semihard loss
  loss = loss_triplet_hard())

## End(Not run)

tfaddons documentation built on July 2, 2020, 2:12 a.m.