class_docstr: AutoHeteroRGCN.
  The model used in this automodel is HeteroRGCN, i.e., the relational graph convolutional network from the
  `"Modeling Relational Data with Graph Convolutional Networks"
  <https://arxiv.org/abs/1703.06103>`_ paper
  
      
  Parameters
  ----------
  num_features: `int`.
      The dimension of features.
  
  num_classes: `int`.
      The number of classes.
  
  device: `torch.device` or `str`.
      The device where model will be running on.
  
  init: `bool`.
      If True(False), the model will (not) be initialized.
  
  dataset: `autogl.datasets`.
      Hetero Graph Dataset in autogl.
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code: def _initialize(self):
      # """Initialize model."""
      self._model = HeteroRGCN(
          dict(
              features_num=self.input_dimension,
              num_class=self.output_dimension,
              edge_type=self.edge_type,
              out_key=self.out_key,
              **self.hyper_parameters,
          )
      ).to(self.device)
  
file_path: AutoGL/autogl/module/model/dgl/hetero/HeteroRGCN.py
imports: import torch.nn
  import dgl.function
  from ..None import register_model
  from .base import BaseHeteroModelMaintainer
  from ..base import activate_func
  from .....utils import get_logger
label_desc: Use image node_id 2 for calling the AutoHeteroRGCN obj's underlying member method code with example usage: obj._initialize() without return types