code: def _initialize(self) -> _typing.Optional[bool]:
      dimensions = list(self.hyper_parameters["hidden"])
      if (
          self.final_dimension not in (Ellipsis, None)
          and isinstance(self.final_dimension, int)
          and self.final_dimension > 0
      ):
          dimensions.append(self.final_dimension)
      self._encoder = _GIN(
          self.input_dimension,
          dimensions,
          self.hyper_parameters["mlp_layers"],
          self.hyper_parameters["act"],
          self.hyper_parameters["eps"],
          self.hyper_parameters["neighbor_pooling_type"],
      ).to(self.device)
      return True
  
imports: import dgl
  import torch.nn.functional
  import typing
  from dgl.nn.pytorch.conv import GINConv
  from ..None import base_encoder, encoder_registry
  from ...None import _utils
label_desc: Use image node_id 2 for calling the GINEncoderMaintainer obj's underlying member method code with example usage: obj._initialize() and returns: True