skip_if_not_installed("caret")
skip_if_not_installed("ranger")
skip_if_not_installed("plumber")
library(caret)
library(plumber)
predictors <- mtcars[, c("cyl", "disp", "hp")]
set.seed(1)
rf_fit <-
train(
x = predictors,
y = mtcars$mpg,
method = "ranger",
tuneLength = 2,
trControl = trainControl(method = "cv")
)
v <- vetiver_model(rf_fit, "cars_rf")
test_that("can print caret model", {
expect_snapshot(v)
})
test_that("can pin a caret model", {
b <- board_temp()
vetiver_pin_write(b, v)
expect_equal(
pin_read(b, "cars_rf"),
list(
model = bundle::bundle(butcher::butcher(rf_fit)),
prototype = vctrs::vec_slice(tibble::as_tibble(mtcars[,2:4]), 0)
)
)
expect_equal(
pin_meta(b, "cars_rf")$user$required_pkgs,
c("caret", "dplyr", "e1071", "ranger")
)
})
test_that("default endpoint for caret", {
p <- pr() %>% vetiver_api(v)
p_routes <- p$routes[-1]
expect_api_routes(p_routes)
})
test_that("default OpenAPI spec", {
v$metadata <- list(url = "potatoes")
p <- pr() %>% vetiver_api(v)
car_spec <- p$getApiSpec()
expect_equal(car_spec$info$description,
"A random forest regression model")
post_spec <- car_spec$paths$`/predict`$post
expect_equal(names(post_spec), c("summary", "requestBody", "responses"))
expect_equal(as.character(post_spec$summary),
"Return predictions from model using 3 features")
get_spec <- car_spec$paths$`/pin-url`$get
expect_equal(as.character(get_spec$summary),
"Get URL of pinned vetiver model")
})
test_that("create plumber.R for xgboost", {
skip_on_cran()
b <- board_folder(path = tmp_dir)
vetiver_pin_write(b, v)
tmp <- tempfile()
vetiver_write_plumber(b, "cars_rf", file = tmp)
expect_snapshot(
cat(readr::read_lines(tmp), sep = "\n"),
transform = redact_vetiver
)
})
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.