Nothing
library(kerasR)
context("Testing regularizers")
check_keras_available <- function() {
if (!keras_available(silent = TRUE)) {
skip("Keras is not available on this system.")
}
}
test_that("regularizers", {
skip_on_cran()
check_keras_available()
X_train <- matrix(rnorm(100 * 10), nrow = 100)
Y_train <- to_categorical(matrix(sample(0:2, 100, TRUE), ncol = 1), 3)
mod <- Sequential()
mod$add(Dense(units = 50, input_shape = dim(X_train)[2]))
mod$add(Activation("relu"))
mod$add(Dense(units = 3, kernel_regularizer = l1(l = 0.05),
bias_regularizer = l2(l = 0.05)))
mod$add(Dense(units = 3, kernel_regularizer = l1_l2(l1 = 0.05, l2 = 0.1)))
mod$add(Activation("softmax"))
keras_compile(mod, loss = 'categorical_crossentropy', optimizer = RMSprop())
keras_fit(mod, X_train, Y_train, batch_size = 32, epochs = 5, verbose = 0)
testthat::expect_false(mod$stateful)
})
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