mlr3pipelines
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Propagate PipeOp properties along graph
I think we need a generalized version of this: https://github.com/mlr-org/mlr3pipelines/issues/306 where we propagate things like input / output type or multiplicity status (and maybe other things?).
We should also think about how / where to represent the resulting information about pipeops and their edges.
related but also complicated: propagate properties of a Learner
to the GraphLearner