code: def __call__(self, group_n_id):
      group_x = []
      for sampler, n_id in zip(self.group_sampler, group_n_id):
          data_flow = sampler(n_id)
          num_layers = len(self.convs)
          x = self.to_x(data_flow[0].n_id)
          for i, conv, block in zip(
              range(num_layers), self.convs, data_flow
          ):
              if block.e_id is None:
                  edge_attr = None
              else:
                  edge_attr = self.get_edge_attr(block)
              if block.edge_weight is None:
                  edge_weight = None
              else:
                  edge_weight = block.edge_weight
              x_src = mp_ops.gather(x, block.res_n_id)
              x_dst = x
              x = self.calculate_conv(
                  conv,
                  (x_src, x_dst),
                  block.edge_index,
                  size=block.size,
                  edge_attr=edge_attr,
                  edge_weight=edge_weight,
              )
              x = tf.nn.relu(x)
          x = self.fc(x)
          group_x.append(x)
      return group_x
  
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 7 for calling the SharedGroupGNNNet obj's underlying member method code with example usage: obj.__call__(group_n_id) and returns: group_x