loss_triplet_semihard: Triplet semihard loss

In tfaddons: Interface to 'TensorFlow SIG Addons'

Description

Computes the triplet loss with semi-hard negative mining.

Usage

loss_triplet_semihard(margin = 1, name = NULL, ...)

Arguments

margin	Float, margin term in the loss definition. Default value is 1.0.
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_semihard())

## End(Not run)

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