code: def __init__(
      self,
      gnn_model: GraphNeuralNetworkModel,
      max_num_classes: int = 100,
      try_simplify_unks: bool = True,
  ):
      super().__init__()
      self.__gnn_model = gnn_model
      self.max_num_classes = max_num_classes
      self.__try_simplify_unks = try_simplify_unks
      self.__tensorize_samples_with_no_annotation = False
      self.__tensorize_keep_original_supernode_idx = False
  
imports: from typing_extensions import TypedDict
  import numpy
  import torch
  from dpu_utils.mlutils import Vocabulary
  from torch import nn
  from typing import Any, Counter, Dict, Iterator, List, NamedTuple, Optional, Tuple, Union
  from ptgnn.baseneuralmodel import AbstractNeuralModel, ModuleWithMetrics
  from ptgnn.baseneuralmodel.utils.data import enforce_not_None
  from ptgnn.neuralmodels.gnn import GnnOutput, GraphData, TensorizedGraphData
  from ptgnn.neuralmodels.gnn.graphneuralnetwork import GraphNeuralNetwork, GraphNeuralNetworkModel
label_desc: Use image node_id 1 to create a new Graph2Class object from inherited base classes: AbstractNeuralModel with example: obj = Graph2Class(gnn_model, max_num_classes, try_simplify_unks)