class_docstr: Setup the MOGONET model via the config file.
  
  Args:
      cfg (CfgNode): A YACS config object.
      dataset (SparseMultiomicsDataset): The input dataset created in form of :class:`~torch_geometric.data.Dataset`.
docstr: Returns a string representation of the model object.
  
  Returns:
      str: The string representation of the model object.
code: def __str__(self) -> str:
      r"""Returns a string representation of the model object.
  
      Returns:
          str: The string representation of the model object.
      """
      return self.get_model().__str__()
  
file_path: pykale/examples/multiomics_mogonet/model.py
imports: from typing import List, Optional
  from torch.nn import CrossEntropyLoss
  from yacs.config import CfgNode
  from kale.embed.mogonet import MogonetGCN
  from kale.loaddata.multiomics_datasets import SparseMultiomicsDataset
  from kale.pipeline.multiomics_trainer import MultiomicsTrainer
  from kale.predict.decode import LinearClassifier, VCDN
label_desc: Use image node_id 4 for calling the MogonetModel obj's underlying member method code with example usage: obj.__str__() and returns: self