Following on the thread.
Background

OOB type variable importances are computed iff. compute_oob_variable_importances=True during training.
Prior to TF-DF 0.1.8, structural variable importances (e.g. NUM_AS_ROOT, MEAN_MIN_DEPTH, NUM_NODES, SUM_SCORE) were computed by the python model inspector (i.e. when looking at the model).
Starting with TF-DF 0.1.8 (released on Jul 29, 2021), structural variable importances are computed in c++ at the end of the model training.

I suspect you are using TF-DF <0.1.8. Make sure to update it and to re-train the model (as the feature importances are now part of the TF-DF model).