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@topepo topepo commented Sep 13, 2024

# ------------------------------------------------------------------------------

is_torch_working <- function() {
res <- try(torch::torch_tensor(1), silent = TRUE)
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This is causing a warning in R CMD check as an undeclared dependency, can we not just add torch to Suggests?

Comment on lines +1 to +30
library(modeldata)
library(rsample)

set.seed(392)
binary_tr <- sim_logistic(200, ~ .1 + 2 * A - 3 * B + 1 * A *B, corr = .7)
binary_rs <- vfold_cv(binary_tr)
binary_te <- sim_logistic(2, ~ .1 + 2 * A - 3 * B + 1 * A *B, corr = .7)

###

set.seed(392)
three_class_tr <-
sim_multinomial(
500,
~ -0.5 + 0.6 * abs(A),
~ ifelse(A > 0 & B > 0, 1.0 + 0.2 * A / B, - 2),
~ -0.6 * A + 0.50 * B - A * B)
three_class_rs <- vfold_cv(three_class_tr)
three_class_te <-
sim_multinomial(
2,
~ -0.5 + 0.6 * abs(A),
~ ifelse(A > 0 & B > 0, 1.0 + 0.2 * A / B, - 2),
~ -0.6 * A + 0.50 * B - A * B)

###

num_tr <- sim_regression(200)
num_rs <- vfold_cv(num_tr)
num_te <- sim_regression(2)
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This runs really fast, can we move all of this into functions?

@@ -0,0 +1,43 @@
test_that("linear regression via brulee", {
skip_if_not_installed("torch")
skip_if_not(any(get_from_env("linear_reg")$engine == "brulee"))
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Can these require a specific version of parsnip instead?

expect_true(nrow(ols_pred) == 2)
expect_named(ols_pred, ".pred")

# ------------------------------------------------------------------------------
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Can you split these into two separate tests with more specific test descriptions, please? Applies to all tests with the # ---- separation header.

@hfrick hfrick marked this pull request as ready for review September 17, 2024 19:33
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2 participants