Nothing
source("utils.R")
testthat::test_that("summary", {
testthat::skip_on_cran()
testthat::skip_on_ci()
skip_if_no_torch()
set.seed(222)
model = dnn(Sepal.Length~., data = datasets::iris, epoch = 2, verbose = FALSE)
testthat::expect_error({summary(model)}, NA)
model = dnn(Species~., data = datasets::iris, epoch = 5, loss = "softmax", lr = 0.1, verbose = FALSE)
testthat::expect_error({summary(model)}, NA)
model = dnn(Species~., data = datasets::iris, epoch = 5, loss = "binomial", lr = 0.1, verbose = TRUE)
testthat::expect_error({summary(model)}, NA)
iris2 = iris
iris2 = iris2[iris2$Species %in% c("setosa", "versicolor"),]
iris2$Species = as.integer(iris2$Species) - 1
model = dnn(Species~., data = iris2, epoch = 5, loss = "binomial", lr = 0.1, verbose = TRUE)
testthat::expect_error({summary(model)}, NA)
})
testthat::test_that("PDP", {
testthat::skip_on_cran()
testthat::skip_on_ci()
skip_if_no_torch()
set.seed(222)
model = dnn(Sepal.Length~., data = datasets::iris, epoch = 2, verbose = FALSE, plot = FALSE)
# Build and train Network
suppressWarnings({
testthat::expect_error({.n = PDP(model)}, NA)
testthat::expect_error({.n = PDP(model, variable = "Sepal.Width")}, NA)
testthat::expect_error({.n = PDP(model, ice = 10)}, NA)
testthat::expect_error({.n = PDP(model, variable = c("Sepal.Width", "Petal.Length"), ice = 20)}, NA)
model = dnn(Species~., data = datasets::iris, epoch = 5, loss = "softmax", lr = 0.1, verbose = FALSE, plot = FALSE)
testthat::expect_error({.n = PDP(model)}, NA)
testthat::expect_error({.n = PDP(model, variable = "Sepal.Width")}, NA)
testthat::expect_error({.n = PDP(model, ice = TRUE)}, NA)
testthat::expect_error({.n = PDP(model, variable = c("Sepal.Width", "Petal.Length"), ice = TRUE, resolution.ice = 30)}, NA)
testthat::expect_error({.n = PDP(model, variable = c("Sepal.Width", "Petal.Length"), ice = TRUE, resolution.ice = 3)}, NA)
model = dnn(Species~., data = datasets::iris, epoch = 5, loss = "binomial", lr = 0.1, verbose = FALSE, plot = FALSE)
testthat::expect_error({.n = PDP(model)}, NA)
testthat::expect_error({.n = PDP(model, variable = "Sepal.Width")}, NA)
testthat::expect_error({.n = PDP(model, ice = TRUE)}, NA)
testthat::expect_error({.n = PDP(model, variable = c("Sepal.Width", "Petal.Length"), ice = TRUE, resolution.ice = 30)}, NA)
testthat::expect_error({.n = PDP(model, variable = c("Sepal.Width", "Petal.Length"), ice = TRUE, resolution.ice = 3)}, NA)
iris2 = iris
iris2 = iris2[iris2$Species %in% c("setosa", "versicolor"),]
iris2$Species = as.integer(iris2$Species) - 1
model = dnn(Species~., data = iris2, epoch = 5, loss = "binomial", lr = 0.1, verbose = TRUE, plot = FALSE)
testthat::expect_error({.n = PDP(model)}, NA)
testthat::expect_error({.n = PDP(model, variable = "Sepal.Width")}, NA)
testthat::expect_error({.n = PDP(model, ice = TRUE)}, NA)
testthat::expect_error({.n = PDP(model, variable = c("Sepal.Width", "Petal.Length"), ice = TRUE, resolution.ice = 30)}, NA)
testthat::expect_error({.n = PDP(model, variable = c("Sepal.Width", "Petal.Length"), ice = TRUE, resolution.ice = 3)}, NA)
})
})
testthat::test_that("ALE", {
testthat::skip_on_cran()
testthat::skip_on_ci()
skip_if_no_torch()
set.seed(222)
model = dnn(Sepal.Length~., data = datasets::iris, epoch = 2, verbose = FALSE, plot = FALSE)
suppressWarnings({
# Build and train Network
testthat::expect_error({.n = ALE(model)}, NA)
testthat::expect_error({.n = ALE(model, variable = "Sepal.Width")}, NA)
testthat::expect_error({.n = ALE(model, variable = c("Sepal.Width", "Petal.Length"))}, NA)
testthat::expect_error({.n = ALE(model, variable = c("Sepal.Width", "Petal.Length"), K = 4)}, NA)
model = dnn(Species~., data = datasets::iris, epoch = 5, loss = "softmax", lr = 0.1, verbose = FALSE, plot = FALSE)
testthat::expect_error({.n = ALE(model)}, NA)
testthat::expect_error({.n = ALE(model, variable = "Sepal.Width")}, NA)
testthat::expect_error({.n = ALE(model, variable = c("Sepal.Width", "Petal.Length"))}, NA)
testthat::expect_error({.n = ALE(model, variable = c("Sepal.Width", "Petal.Length"), K = 4)}, NA)
model = dnn(Species~., data = datasets::iris, epoch = 5, loss = "binomial", lr = 0.1, verbose = FALSE, plot = FALSE)
testthat::expect_error({.n = ALE(model)}, NA)
testthat::expect_error({.n = ALE(model, variable = "Sepal.Width")}, NA)
testthat::expect_error({.n = ALE(model, variable = c("Sepal.Width", "Petal.Length"))}, NA)
testthat::expect_error({.n = ALE(model, variable = c("Sepal.Width", "Petal.Length"), K = 4)}, NA)
iris2 = iris
iris2 = iris2[iris2$Species %in% c("setosa", "versicolor"),]
iris2$Species = as.integer(iris2$Species) - 1
model = dnn(Species~., data = iris2, epoch = 5, loss = "binomial", lr = 0.1, verbose = TRUE, plot = FALSE)
testthat::expect_error({.n = ALE(model)}, NA)
testthat::expect_error({.n = ALE(model, variable = "Sepal.Width")}, NA)
testthat::expect_error({.n = ALE(model, variable = c("Sepal.Width", "Petal.Length"))}, NA)
testthat::expect_error({.n = ALE(model, variable = c("Sepal.Width", "Petal.Length"), K = 4)}, NA)
})
})
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