library(keras)
library(caress)
data(iris)
x <- as.matrix(iris[,1:4])
y <- to_categorical(as.numeric(iris[,5])-1)
input <- from_input(x, name = "input")
output <- input %>%
layer_dense(units = 2, activation = "linear", name = "middle") %>%
to_output(y, name = "output")
model <- prepare(input, output)
build(model, x, y, epochs = 10, batch_size = 8)
model2 <- prepare(input, output)
model_mirror(model2, reference = model, freeze = TRUE)
test_that("model_mirror correctly sets weights for each layer", {
expect_equal(
get_layer_weights(model, "input"),
get_layer_weights(model2, "input")
)
})
build(model2, x, y, epochs = 10, batch_size = 8)
test_that("model_mirror correctly freezes weights for each layer", {
expect_equal(
get_layer_weights(model, "input"),
get_layer_weights(model2, "input")
)
})
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