disappearing dependencies when cloning

[be-marc]

When a graph learner is deep cloned, the dependencies in the parameter set disappear in the original and cloned learner.

library("mlr3")
library("mlr3pipelines")
library("paradox")

graph_learner = GraphLearner$new( lrn("classif.rpart"))
graph_learner$param_set$add_dep("classif.rpart.cp", "classif.rpart.keep_model", CondEqual$new(TRUE))

graph_learner$param_set$deps
# >                 id                       on           cond
# > 1: classif.rpart.cp classif.rpart.keep_model <CondEqual[9]>

graph_learner_2 = graph_learner$clone(deep = TRUE)

graph_learner_2$param_set$deps                                                                                      
# > Empty data.table (0 rows and 3 cols): id,on,cond

graph_learner$param_set$deps                                                                                         
# > Empty data.table (0 rows and 3 cols): id,on,cond

Normal learners are not affected.

library("mlr3")
library("mlr3pipelines")
library("paradox")

learner = lrn("classif.rpart")
learner$param_set$add_dep("cp", "keep_model", CondEqual$new(TRUE))
learner$param_set$deps

# >    id         on           cond
#> 1: cp keep_model <CondEqual[9]>

learner_2 = learner$clone(deep = TRUE)

learner_2$param_set$deps

# >    id         on           cond
#> 1: cp keep_model <CondEqual[9]>

[pfistfl]

The reason seems to be the deep_clone() of the ParamSetCollection.
Marc and I debugged a similar thing in mlr3keras there the culprit seemed to be a fail in cloning ParamSetCollections.

A reproducible example might perhaps be resampling any learner that has a ParamSetCollection instead of a ParamSet, I think the problem is deep cloning of .values.

[be-marc]

@pfistfl We might have violated the rules of ParamSetCollections?

#' A collection of multiple [ParamSet] objects.
#' * The collection is basically a light-weight wrapper / container around references to multiple sets.
#' * In order to ensure unique param names, every param in the collection is referred to with
#'   "<set_id>.<param_id>". Parameters from ParamSets with empty (i.e. `""`) `$set_id` are referenced
#'   directly. Multiple ParamSets with `$set_id` `""` can be combined, but their parameter names
#'   must be unique.
#' * Operation `subset` is currently not allowed.
#' * Operation `add` currently only works when adding complete sets not single params.
#' * When you either ask for 'values' or set them, the operation is delegated to the individual,
#'   contained param set references. The collection itself does not maintain a `values` state.
#'   This also implies that if you directly change `values` in one of the referenced sets,
#'   this change is reflected in the collection.
#' * Dependencies: It is possible to currently handle dependencies
#'      * regarding parameters inside of the same set - in this case simply
#'        add the dependency to the set, best before adding the set to the collection
#'      * across sets, where a param from one set depends on the state
#'        of a param from another set - in this case add call `add_dep` on the collection.
#'
#'   If you call `deps` on the collection, you are returned a complete table of dependencies, from sets and across sets.

I should have added the dependency to the set before creating the graph learner.

[pfistfl]

I think in may case I do not have deps and the culprit seems to be the deep cloning