diff --git a/NEWS.md b/NEWS.md
index 2f11ce35..2489bb09 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,6 +1,11 @@
 # mlr3tuning (development version)
 
-fix: The `as_data_table()` functions do not unnest the `x_domain` colum anymore by default.
+* fix: The `as_data_table()` functions do not unnest the `x_domain` colum anymore by default.
+* fix: `to_tune(internal = TRUE)` now also works if non-internal tuning parameters require have
+  an `.extra_trafo`
+* feat: It is now possible to pass an `internal_search_space` manually.
+  This allows to use parameter transformations on the primary search space in combination with
+  internal hyperparameter tuning.
 
 # mlr3tuning 1.0.2
 
diff --git a/R/AutoTuner.R b/R/AutoTuner.R
index 8956c255..5f90f705 100644
--- a/R/AutoTuner.R
+++ b/R/AutoTuner.R
@@ -46,6 +46,7 @@
 #' @template param_measure
 #' @template param_terminator
 #' @template param_search_space
+#' @template param_internal_search_space
 #' @template param_store_tuning_instance
 #' @template param_store_benchmark_result
 #' @template param_store_models
@@ -137,6 +138,7 @@ AutoTuner = R6Class("AutoTuner",
       measure = NULL,
       terminator,
       search_space = NULL,
+      internal_search_space = NULL,
       store_tuning_instance = TRUE,
       store_benchmark_result = TRUE,
       store_models = FALSE,
@@ -156,6 +158,7 @@ AutoTuner = R6Class("AutoTuner",
       ia$resampling = assert_resampling(resampling)$clone()
       if (!is.null(measure)) ia$measure = assert_measure(as_measure(measure), learner = learner)
       if (!is.null(search_space)) ia$search_space = assert_param_set(as_search_space(search_space))$clone()
+      if (!is.null(internal_search_space)) ia$search_space = assert_param_set(as_search_space(internal_search_space))$clone()
       ia$terminator = assert_terminator(terminator)$clone()
 
       ia$store_models = assert_flag(store_models)
diff --git a/R/TuningInstanceAsyncMulticrit.R b/R/TuningInstanceAsyncMulticrit.R
index 450b2971..1663b06d 100644
--- a/R/TuningInstanceAsyncMulticrit.R
+++ b/R/TuningInstanceAsyncMulticrit.R
@@ -16,6 +16,7 @@
 #' @template param_measures
 #' @template param_terminator
 #' @template param_search_space
+#' @template param_internal_search_space
 #' @template param_store_benchmark_result
 #' @template param_store_models
 #' @template param_check_values
@@ -44,6 +45,7 @@ TuningInstanceAsyncMultiCrit = R6Class("TuningInstanceAsyncMultiCrit",
       measures,
       terminator,
       search_space = NULL,
+      internal_search_space = NULL,
       store_benchmark_result = TRUE,
       store_models = FALSE,
       check_values = FALSE,
@@ -57,24 +59,52 @@ TuningInstanceAsyncMultiCrit = R6Class("TuningInstanceAsyncMultiCrit",
       if (!is.null(search_space) && length(learner$param_set$get_values(type = "only_token"))) {
         stop("If the values of the ParamSet of the Learner contain TuneTokens you cannot supply a search_space.")
       }
-      if (is.null(search_space)) {
-        search_space = as_search_space(learner)
-        learner$param_set$values = learner$param_set$get_values(type = "without_token")
+
+      search_space_from_tokens = is.null(search_space)
+
+      # convert tune token to search space
+      search_space = if (is.null(search_space)) {
+        learner$param_set$search_space()
       } else {
-        search_space = as_search_space(search_space)
+        as_search_space(search_space)
       }
 
-      # internal search space
-      internal_tune_ids = keep(names(search_space$tags), map_lgl(search_space$tags, function(tag) "internal_tuning" %in% tag))
+      # get ids of primary and internal hyperparameters
+      sids = search_space$ids()
+      internal_tune_ids = search_space$ids(any_tags = "internal_tuning")
+
+      # subset search space to primary hyperparameters
       if (length(internal_tune_ids)) {
-        self$internal_search_space = search_space$subset(internal_tune_ids)
+        search_space = search_space$subset(setdiff(sids, internal_tune_ids))
+      }
 
-        if (self$internal_search_space$has_trafo) {
-          stopf("Inner tuning and parameter transformations are currently not supported.")
+      # get internal search space
+      self$internal_search_space = if (is.null(internal_search_space)) {
+        # We DO NOT subset the search space because there we might keep an extra_trafo which is not allowed
+        # for the internal tuning search space
+        if (length(internal_tune_ids)) {
+          learner$param_set$subset(internal_tune_ids)$search_space()
+        }
+      } else {
+        if (length(internal_tune_ids)) {
+          stopf("Either tag parameters in the `search_space` with 'internal_tuning' OR provide an `internal_search_space`.")
         }
+        as_search_space(internal_search_space)
+      }
+
+      # set learner parameter values
+      if (search_space_from_tokens) {
+        learner$param_set$values = learner$param_set$get_values(type = "without_token")
+      }
 
-        search_space = search_space$subset(setdiff(search_space$ids(), internal_tune_ids))
+      if (!is.null(self$internal_search_space) && self$internal_search_space$has_trafo) {
+        stopf("Internal tuning and parameter transformations are currently not supported.
+          If you manually provided a search space that has a trafo and parameters tagged with 'internal_tuning',
+          please pass the latter separately via the argument `internal_search_space`.")
+      }
 
+      # set internal search space
+      if (!is.null(self$internal_search_space)) {
         # the learner dictates how to interpret the to_tune(..., inner)
         learner$param_set$set_values(.values = learner$param_set$convert_internal_search_space(self$internal_search_space))
       }
diff --git a/R/TuningInstanceAsyncSingleCrit.R b/R/TuningInstanceAsyncSingleCrit.R
index 351667e1..da173d2d 100644
--- a/R/TuningInstanceAsyncSingleCrit.R
+++ b/R/TuningInstanceAsyncSingleCrit.R
@@ -25,6 +25,7 @@
 #' @template param_measure
 #' @template param_terminator
 #' @template param_search_space
+#' @template param_internal_search_space
 #' @template param_store_benchmark_result
 #' @template param_store_models
 #' @template param_check_values
@@ -54,6 +55,7 @@ TuningInstanceAsyncSingleCrit = R6Class("TuningInstanceAsyncSingleCrit",
       measure = NULL,
       terminator,
       search_space = NULL,
+      internal_search_space = NULL,
       store_benchmark_result = TRUE,
       store_models = FALSE,
       check_values = FALSE,
@@ -67,24 +69,52 @@ TuningInstanceAsyncSingleCrit = R6Class("TuningInstanceAsyncSingleCrit",
       if (!is.null(search_space) && length(learner$param_set$get_values(type = "only_token"))) {
         stop("If the values of the ParamSet of the Learner contain TuneTokens you cannot supply a search_space.")
       }
-      if (is.null(search_space)) {
-        search_space = as_search_space(learner)
-        learner$param_set$values = learner$param_set$get_values(type = "without_token")
+
+      search_space_from_tokens = is.null(search_space)
+
+      # convert tune token to search space
+      search_space = if (is.null(search_space)) {
+        learner$param_set$search_space()
       } else {
-        search_space = as_search_space(search_space)
+        as_search_space(search_space)
       }
 
-      # internal search space
-      internal_tune_ids = keep(names(search_space$tags), map_lgl(search_space$tags, function(tag) "internal_tuning" %in% tag))
+      # get ids of primary and internal hyperparameters
+      sids = search_space$ids()
+      internal_tune_ids = search_space$ids(any_tags = "internal_tuning")
+
+      # subset search space to primary hyperparameters
       if (length(internal_tune_ids)) {
-        self$internal_search_space = search_space$subset(internal_tune_ids)
+        search_space = search_space$subset(setdiff(sids, internal_tune_ids))
+      }
 
-        if (self$internal_search_space$has_trafo) {
-          stopf("Inner tuning and parameter transformations are currently not supported.")
+      # get internal search space
+      self$internal_search_space = if (is.null(internal_search_space)) {
+        # We DO NOT subset the search space because there we might keep an extra_trafo which is not allowed
+        # for the internal tuning search space
+        if (length(internal_tune_ids)) {
+          learner$param_set$subset(internal_tune_ids)$search_space()
         }
+      } else {
+        if (length(internal_tune_ids)) {
+          stopf("Either tag parameters in the `search_space` with 'internal_tuning' OR provide an `internal_search_space`.")
+        }
+        as_search_space(internal_search_space)
+      }
+
+      # set learner parameter values
+      if (search_space_from_tokens) {
+        learner$param_set$values = learner$param_set$get_values(type = "without_token")
+      }
 
-        search_space = search_space$subset(setdiff(search_space$ids(), internal_tune_ids))
+      if (!is.null(self$internal_search_space) && self$internal_search_space$has_trafo) {
+        stopf("Internal tuning and parameter transformations are currently not supported.
+          If you manually provided a search space that has a trafo and parameters tagged with 'internal_tuning',
+          please pass the latter separately via the argument `internal_search_space`.")
+      }
 
+      # set internal search space
+      if (!is.null(self$internal_search_space)) {
         # the learner dictates how to interpret the to_tune(..., inner)
         learner$param_set$set_values(.values = learner$param_set$convert_internal_search_space(self$internal_search_space))
       }
diff --git a/R/TuningInstanceBatchMulticrit.R b/R/TuningInstanceBatchMulticrit.R
index b6079dc8..540a98b9 100644
--- a/R/TuningInstanceBatchMulticrit.R
+++ b/R/TuningInstanceBatchMulticrit.R
@@ -23,6 +23,7 @@
 #' @template param_measures
 #' @template param_terminator
 #' @template param_search_space
+#' @template param_internal_search_space
 #' @template param_store_benchmark_result
 #' @template param_store_models
 #' @template param_check_values
@@ -81,6 +82,7 @@ TuningInstanceBatchMultiCrit = R6Class("TuningInstanceBatchMultiCrit",
       measures,
       terminator,
       search_space = NULL,
+      internal_search_space = NULL,
       store_benchmark_result = TRUE,
       store_models = FALSE,
       check_values = FALSE,
@@ -92,24 +94,52 @@ TuningInstanceBatchMultiCrit = R6Class("TuningInstanceBatchMultiCrit",
       if (!is.null(search_space) && length(learner$param_set$get_values(type = "only_token"))) {
         stop("If the values of the ParamSet of the Learner contain TuneTokens you cannot supply a search_space.")
       }
-      if (is.null(search_space)) {
-        search_space = as_search_space(learner)
-        learner$param_set$values = learner$param_set$get_values(type = "without_token")
+
+      search_space_from_tokens = is.null(search_space)
+
+      # convert tune token to search space
+      search_space = if (is.null(search_space)) {
+        learner$param_set$search_space()
       } else {
-        search_space = as_search_space(search_space)
+        as_search_space(search_space)
       }
 
-      # internal search space
-      internal_tune_ids = keep(names(search_space$tags), map_lgl(search_space$tags, function(tag) "internal_tuning" %in% tag))
+      # get ids of primary and internal hyperparameters
+      sids = search_space$ids()
+      internal_tune_ids = search_space$ids(any_tags = "internal_tuning")
+
+      # subset search space to primary hyperparameters
       if (length(internal_tune_ids)) {
-        self$internal_search_space = search_space$subset(internal_tune_ids)
+        search_space = search_space$subset(setdiff(sids, internal_tune_ids))
+      }
 
-        if (self$internal_search_space$has_trafo) {
-          stopf("Inner tuning and parameter transformations are currently not supported.")
+      # get internal search space
+      self$internal_search_space = if (is.null(internal_search_space)) {
+        # We DO NOT subset the search space because there we might keep an extra_trafo which is not allowed
+        # for the internal tuning search space
+        if (length(internal_tune_ids)) {
+          learner$param_set$subset(internal_tune_ids)$search_space()
         }
+      } else {
+        if (length(internal_tune_ids)) {
+          stopf("Either tag parameters in the `search_space` with 'internal_tuning' OR provide an `internal_search_space`.")
+        }
+        as_search_space(internal_search_space)
+      }
+
+      # set learner parameter values
+      if (search_space_from_tokens) {
+        learner$param_set$values = learner$param_set$get_values(type = "without_token")
+      }
 
-        search_space = search_space$subset(setdiff(search_space$ids(), internal_tune_ids))
+      if (!is.null(self$internal_search_space) && self$internal_search_space$has_trafo) {
+        stopf("Internal tuning and parameter transformations are currently not supported.
+          If you manually provided a search space that has a trafo and parameters tagged with 'internal_tuning',
+          please pass the latter separately via the argument `internal_search_space`.")
+      }
 
+      # set internal search space
+      if (!is.null(self$internal_search_space)) {
         # the learner dictates how to interpret the to_tune(..., inner)
         learner$param_set$set_values(.values = learner$param_set$convert_internal_search_space(self$internal_search_space))
       }
diff --git a/R/TuningInstanceBatchSingleCrit.R b/R/TuningInstanceBatchSingleCrit.R
index 6343986e..91d3216c 100644
--- a/R/TuningInstanceBatchSingleCrit.R
+++ b/R/TuningInstanceBatchSingleCrit.R
@@ -59,11 +59,11 @@
 #' @template param_measure
 #' @template param_terminator
 #' @template param_search_space
+#' @template param_internal_search_space
 #' @template param_store_benchmark_result
 #' @template param_store_models
 #' @template param_check_values
 #' @template param_callbacks
-#' @template param_internal_search_space
 #'
 #' @template param_xdt
 #' @template param_learner_param_vals
@@ -120,6 +120,7 @@ TuningInstanceBatchSingleCrit = R6Class("TuningInstanceBatchSingleCrit",
       measure = NULL,
       terminator,
       search_space = NULL,
+      internal_search_space = NULL,
       store_benchmark_result = TRUE,
       store_models = FALSE,
       check_values = FALSE,
@@ -131,24 +132,52 @@ TuningInstanceBatchSingleCrit = R6Class("TuningInstanceBatchSingleCrit",
       if (!is.null(search_space) && length(learner$param_set$get_values(type = "only_token"))) {
         stop("If the values of the ParamSet of the Learner contain TuneTokens you cannot supply a search_space.")
       }
-      if (is.null(search_space)) {
-        search_space = as_search_space(learner)
-        learner$param_set$values = learner$param_set$get_values(type = "without_token")
+
+      search_space_from_tokens = is.null(search_space)
+
+      # convert tune token to search space
+      search_space = if (is.null(search_space)) {
+        learner$param_set$search_space()
       } else {
-        search_space = as_search_space(search_space)
+        as_search_space(search_space)
       }
 
-      # internal search space
-      internal_tune_ids = keep(names(search_space$tags), map_lgl(search_space$tags, function(tag) "internal_tuning" %in% tag))
+      # get ids of primary and internal hyperparameters
+      sids = search_space$ids()
+      internal_tune_ids = search_space$ids(any_tags = "internal_tuning")
+
+      # subset search space to primary hyperparameters
       if (length(internal_tune_ids)) {
-        self$internal_search_space = search_space$subset(internal_tune_ids)
+        search_space = search_space$subset(setdiff(sids, internal_tune_ids))
+      }
 
-        if (self$internal_search_space$has_trafo) {
-          stopf("Inner tuning and parameter transformations are currently not supported.")
+      # get internal search space
+      self$internal_search_space = if (is.null(internal_search_space)) {
+        # We DO NOT subset the search space because there we might keep an extra_trafo which is not allowed
+        # for the internal tuning search space
+        if (length(internal_tune_ids)) {
+          learner$param_set$subset(internal_tune_ids)$search_space()
         }
+      } else {
+        if (length(internal_tune_ids)) {
+          stopf("Either tag parameters in the `search_space` with 'internal_tuning' OR provide an `internal_search_space`.")
+        }
+        as_search_space(internal_search_space)
+      }
 
-        search_space = search_space$subset(setdiff(search_space$ids(), internal_tune_ids))
+      # set learner parameter values
+      if (search_space_from_tokens) {
+        learner$param_set$values = learner$param_set$get_values(type = "without_token")
+      }
+
+      if (!is.null(self$internal_search_space) && self$internal_search_space$has_trafo) {
+        stopf("Internal tuning and parameter transformations are currently not supported.
+          If you manually provided a search space that has a trafo and parameters tagged with 'internal_tuning',
+          please pass the latter separately via the argument `internal_search_space`.")
+      }
 
+      # set internal search space
+      if (!is.null(self$internal_search_space)) {
         # the learner dictates how to interpret the to_tune(..., inner)
         learner$param_set$set_values(.values = learner$param_set$convert_internal_search_space(self$internal_search_space))
       }
diff --git a/R/helper.R b/R/helper.R
index 646d901b..dde0d77f 100644
--- a/R/helper.R
+++ b/R/helper.R
@@ -24,42 +24,3 @@ extract_inner_tuned_values = function(resample_result, internal_search_space) {
   internal_tuned_values = transpose_list(map(get_private(resample_result)$.data$learner_states(get_private(resample_result)$.view), "internal_tuned_values"))
   internal_search_space$aggr_internal_tuned_values(internal_tuned_values)
 }
-
-# init_internal_search_space = function(self, private, super, search_space, store_benchmark_result, learner, callbacks, batch) {
-#   assert_flag(store_benchmark_result)
-#   internal_search_space = NULL
-#   internal_tune_ids = keep(names(search_space$tags), map_lgl(search_space$tags, function(t) "internal_tuning" %in% t))
-
-#   if (length(internal_tune_ids)) {
-#     internal_search_space = search_space$subset(internal_tune_ids)
-#     if (internal_search_space$has_trafo) {
-#       stopf("Inner Tuning and Parameter Transformations are currently not supported.")
-#     }
-#     search_space = search_space$subset(setdiff(search_space$ids(), internal_tune_ids))
-
-#     # the learner dictates how to interprete the to_tune(..., inner)
-
-#     learner$param_set$set_values(
-#       .values = learner$param_set$convert_internal_search_space(internal_search_space)
-#     )
-
-#     # we need to use a callback to change how the Optimizer writes the result to the ArchiveTuning
-#     # This is because overwriting the Tuner's .assign_result method has no effect, as it is not called.helper
-#     callbacks = c(load_callback_internal_tuning(batch), callbacks)
-#   }
-
-#   list(
-#     search_space = search_space,
-#     callbacks = callbacks,
-#     internal_search_space = internal_search_space %??% ps()
-#   )
-# }
-
-# init_internal_search_space_archive = function(self, private, super, search_space, internal_search_space) {
-#   if (!is.null(internal_search_space)) {
-#     private$.internal_search_space = as_search_space(internal_search_space)
-#     assert_disjunct(search_space$ids(), internal_search_space$ids())
-#   } else {
-#     private$.internal_search_space = ps()
-#   }
-# }
diff --git a/R/sugar.R b/R/sugar.R
index 8b517b0f..e09eb259 100644
--- a/R/sugar.R
+++ b/R/sugar.R
@@ -44,6 +44,7 @@ tnrs = function(.keys, ...) {
 #' @template param_resampling
 #' @template param_terminator
 #' @template param_search_space
+#' @template param_internal_search_space
 #' @template param_store_benchmark_result
 #' @template param_store_models
 #' @template param_check_values
@@ -61,6 +62,7 @@ ti = function(
   measures = NULL,
   terminator,
   search_space = NULL,
+  internal_search_space = NULL,
   store_benchmark_result = TRUE,
   store_models = FALSE,
   check_values = FALSE,
@@ -75,6 +77,7 @@ ti = function(
     measures,
     terminator = terminator,
     search_space = search_space,
+    internal_search_space = internal_search_space,
     store_benchmark_result = store_benchmark_result,
     store_models = store_models,
     check_values = check_values,
@@ -95,6 +98,7 @@ ti = function(
 #' @template param_resampling
 #' @template param_terminator
 #' @template param_search_space
+#' @template param_internal_search_space
 #' @template param_store_benchmark_result
 #' @template param_store_models
 #' @template param_check_values
@@ -113,6 +117,7 @@ ti_async = function(
   measures = NULL,
   terminator,
   search_space = NULL,
+  internal_search_space = NULL,
   store_benchmark_result = TRUE,
   store_models = FALSE,
   check_values = FALSE,
@@ -128,6 +133,7 @@ ti_async = function(
     measures,
     terminator = terminator,
     search_space = search_space,
+    internal_search_space = internal_search_space,
     store_benchmark_result = store_benchmark_result,
     store_models = store_models,
     check_values = check_values,
diff --git a/R/tune.R b/R/tune.R
index 3a14b478..4516ae17 100644
--- a/R/tune.R
+++ b/R/tune.R
@@ -54,6 +54,7 @@
 #' @template param_term_evals
 #' @template param_term_time
 #' @template param_search_space
+#' @template param_internal_search_space
 #' @template param_store_benchmark_result
 #' @template param_store_models
 #' @template param_check_values
@@ -99,6 +100,7 @@ tune = function(
   terminator = NULL,
   search_space = NULL,
   store_benchmark_result = TRUE,
+  internal_search_space = NULL,
   store_models = FALSE,
   check_values = FALSE,
   callbacks = NULL,
@@ -116,11 +118,13 @@ tune = function(
       measures,
       terminator = terminator,
       search_space = search_space,
+      internal_search_space = internal_search_space,
       store_benchmark_result = store_benchmark_result,
       store_models = store_models,
       check_values = check_values,
       callbacks = callbacks,
-      rush = rush)
+      rush = rush
+      )
   } else {
     TuningInstance = if (is.null(measures) || inherits(measures, "Measure")) TuningInstanceBatchSingleCrit else TuningInstanceBatchMultiCrit
     TuningInstance$new(
@@ -130,6 +134,7 @@ tune = function(
       measures,
       terminator = terminator,
       search_space = search_space,
+      internal_search_space = internal_search_space,
       store_benchmark_result = store_benchmark_result,
       store_models = store_models,
       check_values = check_values,
diff --git a/man-roxygen/param_internal_search_space.R b/man-roxygen/param_internal_search_space.R
index ef541af9..b7af7b49 100644
--- a/man-roxygen/param_internal_search_space.R
+++ b/man-roxygen/param_internal_search_space.R
@@ -1,3 +1,2 @@
 #' @param internal_search_space ([paradox::ParamSet] or `NULL`)\cr
-#'   The internal search space of the tuner. This includes parameters that the learner can optimize internally
-#'   durign `$train()`, such as the number of epochs via early stopping.
+#'   The internal search space.
diff --git a/man/ArchiveAsyncTuning.Rd b/man/ArchiveAsyncTuning.Rd
index 00d40afc..4f9e4da2 100644
--- a/man/ArchiveAsyncTuning.Rd
+++ b/man/ArchiveAsyncTuning.Rd
@@ -128,8 +128,7 @@ Internally created from provided \link[mlr3:Measure]{mlr3::Measure}s.}
 If a rush instance is supplied, the tuning runs without batches.}
 
 \item{\code{internal_search_space}}{(\link[paradox:ParamSet]{paradox::ParamSet} or \code{NULL})\cr
-The internal search space of the tuner. This includes parameters that the learner can optimize internally
-durign \verb{$train()}, such as the number of epochs via early stopping.}
+The internal search space.}
 
 \item{\code{check_values}}{(\code{logical(1)})\cr
 If \code{TRUE} (default), hyperparameter configurations are check for validity.}
diff --git a/man/ArchiveBatchTuning.Rd b/man/ArchiveBatchTuning.Rd
index efda1e0c..b5e4d924 100644
--- a/man/ArchiveBatchTuning.Rd
+++ b/man/ArchiveBatchTuning.Rd
@@ -145,8 +145,7 @@ Internally created from provided \link[mlr3:Measure]{mlr3::Measure}s.}
 If \code{TRUE} (default), hyperparameter configurations are check for validity.}
 
 \item{\code{internal_search_space}}{(\link[paradox:ParamSet]{paradox::ParamSet} or \code{NULL})\cr
-The internal search space of the tuner. This includes parameters that the learner can optimize internally
-durign \verb{$train()}, such as the number of epochs via early stopping.}
+The internal search space.}
 }
 \if{html}{\out{</div>}}
 }
diff --git a/man/AutoTuner.Rd b/man/AutoTuner.Rd
index 0798116e..47f8387e 100644
--- a/man/AutoTuner.Rd
+++ b/man/AutoTuner.Rd
@@ -209,6 +209,7 @@ Creates a new instance of this \link[R6:R6Class]{R6} class.
   measure = NULL,
   terminator,
   search_space = NULL,
+  internal_search_space = NULL,
   store_tuning_instance = TRUE,
   store_benchmark_result = TRUE,
   store_models = FALSE,
@@ -245,6 +246,9 @@ Hyperparameter search space. If \code{NULL} (default), the search space is
 constructed from the \link[paradox:to_tune]{paradox::TuneToken} of the learner's parameter set
 (learner$param_set).}
 
+\item{\code{internal_search_space}}{(\link[paradox:ParamSet]{paradox::ParamSet} or \code{NULL})\cr
+The internal search space.}
+
 \item{\code{store_tuning_instance}}{(\code{logical(1)})\cr
 If \code{TRUE} (default), stores the internally created \link{TuningInstanceBatchSingleCrit} with all intermediate results in slot \verb{$tuning_instance}.}
 
diff --git a/man/ObjectiveTuning.Rd b/man/ObjectiveTuning.Rd
index 05f7d87a..6c16ce34 100644
--- a/man/ObjectiveTuning.Rd
+++ b/man/ObjectiveTuning.Rd
@@ -110,8 +110,7 @@ computational overhead is reduced.}
 List of callbacks.}
 
 \item{\code{internal_search_space}}{(\link[paradox:ParamSet]{paradox::ParamSet} or \code{NULL})\cr
-The internal search space of the tuner. This includes parameters that the learner can optimize internally
-durign \verb{$train()}, such as the number of epochs via early stopping.}
+The internal search space.}
 }
 \if{html}{\out{</div>}}
 }
diff --git a/man/ObjectiveTuningBatch.Rd b/man/ObjectiveTuningBatch.Rd
index 9b87fc65..240fe8f7 100644
--- a/man/ObjectiveTuningBatch.Rd
+++ b/man/ObjectiveTuningBatch.Rd
@@ -98,8 +98,7 @@ If \code{NULL} (default), benchmark result and models cannot be stored.}
 List of callbacks.}
 
 \item{\code{internal_search_space}}{(\link[paradox:ParamSet]{paradox::ParamSet} or \code{NULL})\cr
-The internal search space of the tuner. This includes parameters that the learner can optimize internally
-durign \verb{$train()}, such as the number of epochs via early stopping.}
+The internal search space.}
 }
 \if{html}{\out{</div>}}
 }
diff --git a/man/TuningInstanceAsyncMultiCrit.Rd b/man/TuningInstanceAsyncMultiCrit.Rd
index b4ebc0f8..dc2997d2 100644
--- a/man/TuningInstanceAsyncMultiCrit.Rd
+++ b/man/TuningInstanceAsyncMultiCrit.Rd
@@ -82,6 +82,7 @@ Creates a new instance of this \link[R6:R6Class]{R6} class.
   measures,
   terminator,
   search_space = NULL,
+  internal_search_space = NULL,
   store_benchmark_result = TRUE,
   store_models = FALSE,
   check_values = FALSE,
@@ -117,6 +118,9 @@ Hyperparameter search space. If \code{NULL} (default), the search space is
 constructed from the \link[paradox:to_tune]{paradox::TuneToken} of the learner's parameter set
 (learner$param_set).}
 
+\item{\code{internal_search_space}}{(\link[paradox:ParamSet]{paradox::ParamSet} or \code{NULL})\cr
+The internal search space.}
+
 \item{\code{store_benchmark_result}}{(\code{logical(1)})\cr
 If \code{TRUE} (default), store resample result of evaluated hyperparameter
 configurations in archive as \link[mlr3:BenchmarkResult]{mlr3::BenchmarkResult}.}
diff --git a/man/TuningInstanceAsyncSingleCrit.Rd b/man/TuningInstanceAsyncSingleCrit.Rd
index 40808b71..7d0a7932 100644
--- a/man/TuningInstanceAsyncSingleCrit.Rd
+++ b/man/TuningInstanceAsyncSingleCrit.Rd
@@ -117,6 +117,7 @@ Creates a new instance of this \link[R6:R6Class]{R6} class.
   measure = NULL,
   terminator,
   search_space = NULL,
+  internal_search_space = NULL,
   store_benchmark_result = TRUE,
   store_models = FALSE,
   check_values = FALSE,
@@ -152,6 +153,12 @@ Hyperparameter search space. If \code{NULL} (default), the search space is
 constructed from the \link[paradox:to_tune]{paradox::TuneToken} of the learner's parameter set
 (learner$param_set).}
 
+\item{\code{internal_search_space}}{(\link[paradox:ParamSet]{paradox::ParamSet} or \code{NULL})\cr
+The internal search space.}
+
+\item{\code{internal_search_space}}{(\link[paradox:ParamSet]{paradox::ParamSet} or \code{NULL})\cr
+The internal search space.}
+
 \item{\code{store_benchmark_result}}{(\code{logical(1)})\cr
 If \code{TRUE} (default), store resample result of evaluated hyperparameter
 configurations in archive as \link[mlr3:BenchmarkResult]{mlr3::BenchmarkResult}.}
diff --git a/man/TuningInstanceBatchMultiCrit.Rd b/man/TuningInstanceBatchMultiCrit.Rd
index b38e7a14..ecf38ac6 100644
--- a/man/TuningInstanceBatchMultiCrit.Rd
+++ b/man/TuningInstanceBatchMultiCrit.Rd
@@ -123,6 +123,7 @@ Creates a new instance of this \link[R6:R6Class]{R6} class.
   measures,
   terminator,
   search_space = NULL,
+  internal_search_space = NULL,
   store_benchmark_result = TRUE,
   store_models = FALSE,
   check_values = FALSE,
@@ -157,6 +158,12 @@ Hyperparameter search space. If \code{NULL} (default), the search space is
 constructed from the \link[paradox:to_tune]{paradox::TuneToken} of the learner's parameter set
 (learner$param_set).}
 
+\item{\code{internal_search_space}}{(\link[paradox:ParamSet]{paradox::ParamSet} or \code{NULL})\cr
+The internal search space.}
+
+\item{\code{internal_search_space}}{(\link[paradox:ParamSet]{paradox::ParamSet} or \code{NULL})\cr
+The internal search space.}
+
 \item{\code{store_benchmark_result}}{(\code{logical(1)})\cr
 If \code{TRUE} (default), store resample result of evaluated hyperparameter
 configurations in archive as \link[mlr3:BenchmarkResult]{mlr3::BenchmarkResult}.}
diff --git a/man/TuningInstanceBatchSingleCrit.Rd b/man/TuningInstanceBatchSingleCrit.Rd
index 09511144..c3644516 100644
--- a/man/TuningInstanceBatchSingleCrit.Rd
+++ b/man/TuningInstanceBatchSingleCrit.Rd
@@ -164,7 +164,8 @@ Creates a new instance of this \link[R6:R6Class]{R6} class.
   store_benchmark_result = TRUE,
   store_models = FALSE,
   check_values = FALSE,
-  callbacks = NULL
+  callbacks = NULL,
+  internal_search_space = NULL
 )}\if{html}{\out{</div>}}
 }
 
@@ -212,6 +213,9 @@ computational overhead is reduced.}
 
 \item{\code{callbacks}}{(list of \link[mlr3misc:Callback]{mlr3misc::Callback})\cr
 List of callbacks.}
+
+\item{\code{internal_search_space}}{(\link[paradox:ParamSet]{paradox::ParamSet} or \code{NULL})\cr
+The internal search space.}
 }
 \if{html}{\out{</div>}}
 }
diff --git a/man/mlr_tuners_cmaes.Rd b/man/mlr_tuners_cmaes.Rd
index 79a69f52..5df8f71c 100644
--- a/man/mlr_tuners_cmaes.Rd
+++ b/man/mlr_tuners_cmaes.Rd
@@ -11,7 +11,7 @@ Hansen N (2016).
 }
 \description{
 Subclass for Covariance Matrix Adaptation Evolution Strategy (CMA-ES).
-Calls \code{\link[adagio:cmaes]{adagio::pureCMAES()}} from package \CRANpkg{adagio}.
+Calls \code{\link[adagio:pureCMAES]{adagio::pureCMAES()}} from package \CRANpkg{adagio}.
 }
 \section{Dictionary}{
 
@@ -29,7 +29,7 @@ Create \code{random} start values or based on \code{center} of search space?
 In the latter case, it is the center of the parameters before a trafo is applied.}
 }
 
-For the meaning of the control parameters, see \code{\link[adagio:cmaes]{adagio::pureCMAES()}}.
+For the meaning of the control parameters, see \code{\link[adagio:pureCMAES]{adagio::pureCMAES()}}.
 Note that we have removed all control parameters which refer to the termination of the algorithm and where our terminators allow to obtain the same behavior.
 }
 
diff --git a/man/ti.Rd b/man/ti.Rd
index e939a1b1..45827d70 100644
--- a/man/ti.Rd
+++ b/man/ti.Rd
@@ -11,6 +11,7 @@ ti(
   measures = NULL,
   terminator,
   search_space = NULL,
+  internal_search_space = NULL,
   store_benchmark_result = TRUE,
   store_models = FALSE,
   check_values = FALSE,
@@ -43,6 +44,9 @@ Hyperparameter search space. If \code{NULL} (default), the search space is
 constructed from the \link[paradox:to_tune]{paradox::TuneToken} of the learner's parameter set
 (learner$param_set).}
 
+\item{internal_search_space}{(\link[paradox:ParamSet]{paradox::ParamSet} or \code{NULL})\cr
+The internal search space.}
+
 \item{store_benchmark_result}{(\code{logical(1)})\cr
 If \code{TRUE} (default), store resample result of evaluated hyperparameter
 configurations in archive as \link[mlr3:BenchmarkResult]{mlr3::BenchmarkResult}.}
diff --git a/man/ti_async.Rd b/man/ti_async.Rd
index 560d2e16..7986e7c6 100644
--- a/man/ti_async.Rd
+++ b/man/ti_async.Rd
@@ -11,6 +11,7 @@ ti_async(
   measures = NULL,
   terminator,
   search_space = NULL,
+  internal_search_space = NULL,
   store_benchmark_result = TRUE,
   store_models = FALSE,
   check_values = FALSE,
@@ -44,6 +45,9 @@ Hyperparameter search space. If \code{NULL} (default), the search space is
 constructed from the \link[paradox:to_tune]{paradox::TuneToken} of the learner's parameter set
 (learner$param_set).}
 
+\item{internal_search_space}{(\link[paradox:ParamSet]{paradox::ParamSet} or \code{NULL})\cr
+The internal search space.}
+
 \item{store_benchmark_result}{(\code{logical(1)})\cr
 If \code{TRUE} (default), store resample result of evaluated hyperparameter
 configurations in archive as \link[mlr3:BenchmarkResult]{mlr3::BenchmarkResult}.}
diff --git a/man/tune.Rd b/man/tune.Rd
index f6f9507f..75cc2395 100644
--- a/man/tune.Rd
+++ b/man/tune.Rd
@@ -15,6 +15,7 @@ tune(
   terminator = NULL,
   search_space = NULL,
   store_benchmark_result = TRUE,
+  internal_search_space = NULL,
   store_models = FALSE,
   check_values = FALSE,
   callbacks = NULL,
@@ -62,6 +63,9 @@ constructed from the \link[paradox:to_tune]{paradox::TuneToken} of the learner's
 If \code{TRUE} (default), store resample result of evaluated hyperparameter
 configurations in archive as \link[mlr3:BenchmarkResult]{mlr3::BenchmarkResult}.}
 
+\item{internal_search_space}{(\link[paradox:ParamSet]{paradox::ParamSet} or \code{NULL})\cr
+The internal search space.}
+
 \item{store_models}{(\code{logical(1)})\cr
 If \code{TRUE}, fitted models are stored in the benchmark result
 (\code{archive$benchmark_result}). If \code{store_benchmark_result = FALSE}, models
diff --git a/tests/testthat/test_Tuner.R b/tests/testthat/test_Tuner.R
index c08ef00d..7098a407 100644
--- a/tests/testthat/test_Tuner.R
+++ b/tests/testthat/test_Tuner.R
@@ -269,10 +269,9 @@ test_that("proper error when primary search space is empty", {
 test_that("internal tuning: branching", {
   skip_if_not_installed("mlr3pipelines")
   skip_if(packageVersion("mlr3pipelines") < "0.5.3")
-  requireNamespace("mlr3pipelines")
   # this case is special, because not all internally tuned parameters are present in every iteration, only those that
   # are in the active branch are
-  glrn = ppl("branch", graphs = list(
+  glrn = mlr3pipelines::ppl("branch", graphs = list(
     lrn("classif.debug", id = "lrn1", iter = to_tune(upper = 500, internal = TRUE, aggr = function(x) 1L), early_stopping = TRUE),
     lrn("classif.debug", id = "lrn2", iter = to_tune(upper = 1000, internal = TRUE, aggr = function(x) 2L), early_stopping = TRUE)
   ))
@@ -324,3 +323,70 @@ test_that("internal tuning: error message when primary search space is empty", {
   ), "tnr('internal')", fixed = TRUE)
 })
 
+test_that("parameter transformations can be used with internal tuning", {
+  ti = tune(
+    tuner = tnr("random_search"),
+    learner = lrn("classif.debug",
+      iter = to_tune(upper = 1000, internal = TRUE),
+      x = to_tune(ps(a = p_dbl(0, 0.5), b = p_dbl(0, 0.5), .extra_trafo = function(x, param_set) {
+        list(x = x$a + x$b)
+      })),
+      early_stopping = TRUE, validate = 0.2),
+    task = tsk("iris"),
+    resampling = rsmp("holdout"),
+    term_evals = 2
+  )
+  expect_set_equal(
+    names(ti$result_learner_param_vals),
+    c("x", "iter", "early_stopping")
+  )
+})
+
+test_that("either provide internal_search_space OR tag params with 'internal_tuning'", {
+  expect_error(
+    tune(
+      tuner = tnr("random_search"),
+      learner = lrn("classif.debug",
+        iter = to_tune(upper = 1000, internal = TRUE),
+        x = to_tune(),
+        early_stopping = TRUE, validate = 0.2),
+      task = tsk("iris"),
+      internal_search_space = ps(iter = p_int(upper = 100, aggr = function(x) round(mean(unlist(x))))),
+      resampling = rsmp("holdout"),
+      term_evals = 2
+    ),
+    "Either tag parameters in the `search_space`"
+  )
+})
+
+test_that("Can pass internal_search_space separately", {
+  # 1. primary search space is passed manually
+  ti = tune(
+    tuner = tnr("random_search"),
+    learner = lrn("classif.debug",
+      x = to_tune(),
+      early_stopping = TRUE, validate = 0.2),
+    task = tsk("iris"),
+    internal_search_space = ps(iter = p_int(upper = 100, aggr = function(x) as.integer(mean(unlist(x))))),
+    resampling = rsmp("holdout"),
+    term_evals = 2
+  )
+  expect_true("iter" %in% ti$internal_search_space$ids())
+  expect_true(is.integer(ti$result$internal_tuned_values[[1]]$iter))
+  expect_double(ti$result$x)
+
+  # 2. primary search space is passed via to_tune
+  ti = tune(
+    tuner = tnr("random_search"),
+    learner = lrn("classif.debug",
+      early_stopping = TRUE, validate = 0.2),
+    task = tsk("iris"),
+    search_space = ps(x = p_dbl(0, 1)),
+    internal_search_space = ps(iter = p_int(upper = 100, aggr = function(x) as.integer(mean(unlist(x))))),
+    resampling = rsmp("holdout"),
+    term_evals = 2
+  )
+  expect_true("iter" %in% ti$internal_search_space$ids())
+  expect_true(is.integer(ti$result$internal_tuned_values[[1]]$iter))
+  expect_double(ti$result$x)
+})
diff --git a/tests/testthat/test_TunerBatch.R b/tests/testthat/test_TunerBatch.R
deleted file mode 100644
index e69de29b..00000000