keras (version 2.2.4)

freeze_weights: Freeze and unfreeze weights

Description

Freeze weights in a model or layer so that they are no longer trainable.

Usage

freeze_weights(object, from = NULL, to = NULL)
unfreeze_weights(object, from = NULL, to = NULL)

Arguments

object

Keras model or layer object

from

Layer instance, layer name, or layer index within model

to

Layer instance, layer name, or layer index within model

Examples

# NOT RUN {
# instantiate a VGG16 model
conv_base <- application_vgg16(
  weights = "imagenet",
  include_top = FALSE,
  input_shape = c(150, 150, 3)
)

# freeze it's weights
freeze_weights(conv_base)

# create a composite model that includes the base + more layers
model <- keras_model_sequential() %>%
  conv_base %>%
  layer_flatten() %>%
  layer_dense(units = 256, activation = "relu") %>%
  layer_dense(units = 1, activation = "sigmoid")

# compile
model %>% compile(
  loss = "binary_crossentropy",
  optimizer = optimizer_rmsprop(lr = 2e-5),
  metrics = c("accuracy")
)

# unfreeze weights from "block5_conv1" on
unfreeze_weights(conv_base, from = "block5_conv1")

# compile again since we froze or unfroze weights
model %>% compile(
  loss = "binary_crossentropy",
  optimizer = optimizer_rmsprop(lr = 2e-5),
  metrics = c("accuracy")
)

# }
# NOT RUN {
# }