Nothing
library(kerasR)
context("Testing advanced activations")
check_keras_available <- function() {
if (!keras_available(silent = TRUE)) {
skip("Keras is not available on this system.")
}
}
test_that("advanced activations", {
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(LeakyReLU(alpha = 0.4))
mod$add(Dense(units = 50))
mod$add(ELU(alpha = 0.5))
mod$add(Dense(units = 50))
mod$add(ThresholdedReLU(theta = 1.1))
mod$add(Dense(units = 3))
mod$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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