skip_if_no_pycox()
set.seed(1)
np <- reticulate::import("numpy")
np$random$seed(1L)
torch <- reticulate::import("torch")
torch$manual_seed(1L)
test_that("silent", {
expect_silent({fit <- coxtime(Surv(time, status) ~ ., data = rats[1:50, ],
verbose = FALSE, frac = 0.3)})
expect_silent({predict(fit, newdata = rats[51:100, ])})
})
test_that("early_stopping", {
expect_true("EarlyStopping" %in% names(coxtime(Surv(time, status) ~ ., data = rats[1:50, ],
verbose = FALSE,
early_stopping = TRUE)$model$callbacks$callbacks))
expect_true("BestWeights" %in% names(coxtime(Surv(time, status) ~ ., data = rats[1:50, ],
verbose = FALSE,
best_weights = TRUE)$model$callbacks$callbacks))
expect_true("EarlyStopping" %in% names(coxtime(Surv(time, status) ~ ., data = rats[1:50, ],
verbose = FALSE, early_stopping = TRUE,
best_weights = TRUE)$model$callbacks$callbacks))
})
test_that("auto sanity", {
sanity_check(model = "coxtime",
pars = list(frac = 0.3, activation = "relu", num_nodes = c(2L, 2L),
dropout = 0.1, early_stopping = TRUE, epochs = 100L, batch_size = 32L))
})
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