code: def __init__(
      self,
      conv,
      group_flow,
      dims,
      group_fanouts,
      group_metapath,
      add_self_loops=True,
  ):
      conv_class = utils.get_conv_class(conv)
      self.convs = []
      for dim in dims[:-1]:
          self.convs.append(self.get_conv(conv_class, dim))
      group_flow_class = [
          utils.get_flow_class(flow) for flow in group_flow
      ]
      self.fc = tf.layers.Dense(dims[-1])
      if "whole" in group_flow:
          raise ValueError("Group GNN does not support whole dataflow")
      self.group_sampler = [
          flow_class(fanouts, metapath, add_self_loops)
          for flow_class, fanouts, metapath in zip(
              group_flow_class, group_fanouts, group_metapath
          )
      ]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  import tf_euler
  from tf_euler.python.euler_ops import mp_ops
  from tf_euler.python.mp_utils import utils
  from tf_euler.python.mp_utils.base_gnn import BaseGNNNet
  from tf_euler.python.utils.encoders import ShallowEncoder
label_desc: Use image node_id 1 to create a new SharedGroupGNNNet object from inherited base classes: object with example: obj = SharedGroupGNNNet(conv, group_flow, dims, group_fanouts, group_metapath, add__loops)