code: def __init__(
      self, num_state: int = 128, num_node: int = 64, bias=False
  ):
      super().__init__()
      self.conv1 = nn.Conv1D(
          num_node,
          num_node,
          kernel_size=1,
          padding=0,
          stride=1,
          groups=1,
      )
      self.relu = nn.ReLU()
      self.conv2 = nn.Conv1D(
          num_state,
          num_state,
          kernel_size=1,
          padding=0,
          stride=1,
          groups=1,
          bias_attr=bias,
      )
  
imports: import os
  from typing import Union, List, Tuple
  import paddle
  from paddle import nn
  import paddle.nn.functional
  import numpy
  from paddlehub.module.module import moduleinfo
  import paddlehub.vision.segmentation_transforms
  from paddlehub.module.cv_module import ImageSegmentationModule
  from paddleseg.utils import utils
  from paddleseg.models import layers
  from ginet_resnet101vd_cityscapes.resnet import ResNet101_vd
label_desc: Use image node_id 1 to create a new GCN object from inherited base classes: nn with example: obj = GCN(num_state, num_node, bias)