code: def feature_importance_(self):
      return (
          self.gflus.feature_mask_function(self.gflus.feature_masks)
          .sum(dim=0)
          .detach()
          .cpu()
          .numpy()
      )
  
imports: import torch
  import torch.nn
  from omegaconf import DictConfig
  from pytorch_tabular.models.common.heads import blocks
  from pytorch_tabular.models.common.layers import Add, Embedding1dLayer, GatedFeatureLearningUnit, NeuralDecisionTree
  from pytorch_tabular.models.common.layers.activations import entmax15, entmoid15, sparsemax, sparsemoid, t_softmax
  from pytorch_tabular.utils import get_logger
  from ..base_model import BaseModel
label_desc: Use image node_id 5 for calling the GatedAdditiveTreesBackbone obj's underlying member method code with example usage: obj.feature_importance_() and returns: self