class_docstr: The original paper refers to:
      Chen, Yunpeng, et al. "Graph-Based Global Reasoning Networks" (https://arxiv.org/abs/1811.12814)
code: def forward(
      self, x: paddle.Tensor, inp: paddle.Tensor
  ) -> List[paddle.Tensor]:
      B = self.conv_theta(x)
      sizeB = B.shape
      B = B.reshape((sizeB[0], sizeB[1], -1))
  
      sizex = x.shape
      x_reduce = self.conv_phi(x)
      x_reduce = x_reduce.reshape(
          (sizex[0], -1, sizex[2] * sizex[3])
      ).transpose((0, 2, 1))
  
      V = paddle.bmm(B, x_reduce).transpose((0, 2, 1))
      V = paddle.divide(
          V, paddle.to_tensor([sizex[2] * sizex[3]], dtype="float32")
      )
  
      class_node, new_V = self.graph(inp, V)
      D = B.reshape((sizeB[0], -1, sizeB[2] * sizeB[3])).transpose(
          (0, 2, 1)
      )
      Y = paddle.bmm(D, new_V.transpose((0, 2, 1)))
      Y = Y.transpose((0, 2, 1)).reshape(
          (sizex[0], self.num_state, sizex[2], -1)
      )
      Y = self.extend_dim(Y)
      Y = self.bn(Y)
      out = Y + x
  
      return out, class_node
  
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_voc.resnet import ResNet101_vd
label_desc: Use image node_id 2 for calling the GlobalReasonUnit obj's underlying member method code with example usage: obj.forward(x, inp) and returns: out,  class_node