Nothing
test_that('updating', {
expect_snapshot(
mlp(mode = "classification", hidden_units = 2) %>%
set_engine("nnet", Hess = FALSE) %>%
update(hidden_units = tune(), Hess = tune())
)
})
test_that('bad input', {
expect_error(mlp(mode = "time series"))
expect_error(translate(mlp(mode = "classification") %>% set_engine("wat?")))
expect_warning(translate(mlp(mode = "regression") %>% set_engine("nnet", formula = y ~ x)))
expect_error(translate(mlp(mode = "classification", x = x, y = y) %>% set_engine("keras")))
expect_error(translate(mlp(mode = "regression", formula = y ~ x) %>% set_engine()))
})
test_that("nnet_softmax", {
obj <- mlp(mode = 'classification')
obj$lvls <- c("a", "b")
res <- nnet_softmax(matrix(c(.8, .2)), obj)
expect_equal(names(res), obj$lvls)
expect_equal(res$b, 1 - res$a)
})
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