code: def __init__(
      self,
      conv,
      flow,
      dims,
      fanouts,
      metapath,
      add_self_loops=True,
      max_id=-1,
      **kwargs,
  ):
      conv_class = utils.get_conv_class(conv)
      flow_class = utils.get_flow_class(flow)
      if flow_class == "whole":
          self.whole_graph = True
      else:
          self.whole_graph = False
      self.convs = []
      for dim in dims[:-1]:
          self.convs.append(self.get_conv(conv_class, dim))
      self.fc = tf.layers.Dense(dims[-1])
      self.sampler = flow_class(
          fanouts, metapath, add_self_loops, max_id=max_id
      )
  
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
label_desc: Use image node_id 1 to create a new BaseGNNNet object from inherited base classes: object with example: obj = BaseGNNNet(conv, flow, dims, fanouts, metapath, add__loops, max_id)