class_docstr: The Graph Interaction Network head.
code: def __init__(self, in_channels: int, nclass: int):
      super().__init__()
      self.nclass = nclass
      inter_channels = in_channels // 4
      self.inp = paddle.zeros(shape=(nclass, 300), dtype="float32")
      self.inp = paddle.create_parameter(
          shape=self.inp.shape,
          dtype=str(self.inp.numpy().dtype),
          default_initializer=paddle.nn.initializer.Assign(self.inp),
      )
  
      self.fc1 = nn.Sequential(
          nn.Linear(300, 128), nn.BatchNorm1D(128), nn.ReLU()
      )
      self.fc2 = nn.Sequential(
          nn.Linear(128, 256), nn.BatchNorm1D(256), nn.ReLU()
      )
      self.conv5 = layers.ConvBNReLU(
          in_channels,
          inter_channels,
          3,
          padding=1,
          bias_attr=False,
          stride=1,
      )
  
      self.gloru = GlobalReasonUnit(
          in_channels=inter_channels,
          num_state=256,
          num_node=84,
          nclass=nclass,
      )
      self.conv6 = nn.Sequential(
          nn.Dropout(0.1), nn.Conv2D(inter_channels, nclass, 1)
      )
  
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 1 to create a new GIHead object from inherited base classes: nn with example: obj = GIHead(in_channels, nclass)