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test with new paradox #109

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merged 7 commits into from
Feb 29, 2024
Merged

test with new paradox #109

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test with new paradox
mb706 Jan 14, 2024
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test with new paradox
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3 changes: 2 additions & 1 deletion .github/workflows/dev-cmd-check.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -27,6 +27,7 @@ jobs:
- {os: ubuntu-latest, r: 'release', dev-package: 'mlr-org/bbotk'}
- {os: ubuntu-latest, r: 'release', dev-package: 'mlr-org/mlr3'}
- {os: ubuntu-latest, r: 'release', dev-package: 'mlr-org/mlr3tuning'}
- {os: ubuntu-latest, r: 'release', dev-package: "mlr-org/mlr3tuning', 'mlr-org/mlr3learners', 'mlr-org/mlr3pipelines', 'mlr-org/bbotk', 'mlr-org/paradox"}

steps:
- uses: actions/checkout@v3
Expand All @@ -41,7 +42,7 @@ jobs:
needs: check

- name: Install dev versions
run: pak::pkg_install('${{ matrix.config.dev-package }}')
run: pak::pkg_install(c('${{ matrix.config.dev-package }}'))
shell: Rscript {0}

- uses: r-lib/actions/check-r-package@v2
2 changes: 2 additions & 0 deletions NEWS.md
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@@ -1,5 +1,7 @@
# mlr3hyperband (development version)

* Compatibility with upcoming 'paradox' release.

# mlr3hyperband 0.4.5

* fix: Unloading `mlr3hyperband` removes optimizers and tuners from the dictionaries.
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2 changes: 1 addition & 1 deletion R/OptimizerHyperband.R
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Expand Up @@ -80,7 +80,7 @@ OptimizerHyperband = R6Class("OptimizerHyperband",
#' Creates a new instance of this [R6][R6::R6Class] class.
initialize = function() {
param_set = ps(
eta = p_dbl(lower = 1.0001, tags = "required", default = 2),
eta = p_dbl(lower = 1.0001, tags = "required"),
sampler = p_uty(custom_check = function(x) check_r6(x, "Sampler", null.ok = TRUE)),
repetitions = p_int(lower = 1L, default = 1, special_vals = list(Inf))
)
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8 changes: 4 additions & 4 deletions tests/testthat/test_TunerHyperband.R
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Expand Up @@ -74,7 +74,7 @@ test_that("TunerHyperband works with custom sampler", {
iter = to_tune(p_int(1, 4, tags = "budget"))
)

sampler = Sampler1DRfun$new(learner$param_set$search_space()$params[["x"]], function(n) rbeta(n, 2, 5))
sampler = Sampler1DRfun$new(learner$param_set$search_space()$params[["x"]] %??% learner$param_set$search_space()$subset("x"), function(n) rbeta(n, 2, 5))

test_tuner_hyperband(eta = 2, learner, sampler = sampler)
})
Expand All @@ -86,7 +86,7 @@ test_that("TunerHyperband errors if not enough parameters are sampled", {
iter = to_tune(p_int(1, 4, tags = "budget"))
)

sampler = Sampler1DRfun$new(learner$param_set$search_space()$params[["x"]], function(n) rbeta(n, 2, 5))
sampler = Sampler1DRfun$new(learner$param_set$search_space()$params[["x"]] %??% learner$param_set$search_space()$subset("x"), function(n) rbeta(n, 2, 5))

expect_error(tune(
tnr( "hyperband", sampler = sampler),
Expand All @@ -106,8 +106,8 @@ test_that("TunerHyperband errors if budget parameter is sampled", {
)

sampler = SamplerJointIndep$new(list(
Sampler1DRfun$new(learner$param_set$search_space()$params[["x"]], function(n) rbeta(n, 2, 5)),
Sampler1D$new(learner$param_set$search_space()$params[["iter"]])
Sampler1DRfun$new(learner$param_set$search_space()$params[["x"]] %??% learner$param_set$search_space()$subset("x"), function(n) rbeta(n, 2, 5)),
Sampler1D$new(learner$param_set$search_space()$params[["iter"]] %??% learner$param_set$search_space()$subset("iter"))
))

expect_error(tune(
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8 changes: 4 additions & 4 deletions tests/testthat/test_TunerSuccessiveHalving.R
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Expand Up @@ -91,7 +91,7 @@ test_that("TunerSuccessiveHalving works with custom sampler", {
iter = to_tune(p_int(1, 4, tags = "budget"))
)

sampler = Sampler1DRfun$new(learner$param_set$search_space()$params[["x"]], function(n) rbeta(n, 2, 5))
sampler = Sampler1DRfun$new(learner$param_set$search_space()$params[["x"]] %??% learner$param_set$search_space()$subset("x"), function(n) rbeta(n, 2, 5))

test_tuner_successive_halving(n = 16, eta = 2, learner, sampler = sampler)
})
Expand All @@ -103,7 +103,7 @@ test_that("TunerSuccessiveHalving errors if not enough parameters are sampled",
iter = to_tune(p_int(1, 4, tags = "budget"))
)

sampler = Sampler1DRfun$new(learner$param_set$search_space()$params[["x"]], function(n) rbeta(n, 2, 5))
sampler = Sampler1DRfun$new(learner$param_set$search_space()$params[["x"]] %??% learner$param_set$search_space()$subset("x"), function(n) rbeta(n, 2, 5))

expect_error(tune(
tnr( "successive_halving", sampler = sampler),
Expand All @@ -123,8 +123,8 @@ test_that("TunerSuccessiveHalving errors if budget parameter is sampled", {
)

sampler = SamplerJointIndep$new(list(
Sampler1DRfun$new(learner$param_set$search_space()$params[["x"]], function(n) rbeta(n, 2, 5)),
Sampler1D$new(learner$param_set$search_space()$params[["iter"]])
Sampler1DRfun$new(learner$param_set$search_space()$params[["x"]] %??% learner$param_set$search_space()$subset("x"), function(n) rbeta(n, 2, 5)),
Sampler1D$new(learner$param_set$search_space()$params[["iter"]] %??% learner$param_set$search_space()$subset("iter"))
))

expect_error(tune(
Expand Down
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