code: def sample_neighbor_layerwise(
      nodes, edge_types, count, default_node=-1, weight_func=""
  ):
      edge_types = type_ops.get_edge_type_id(edge_types)
      res = _sample_neighbor_layerwise_with_adj(
          nodes, edge_types, count, weight_func, default_node
      )
      return res[0], tf.SparseTensor(*res[1:4])
  
file_path: euler/tf_euler/python/euler_ops/neighbor_ops.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  from tf_euler.python.euler_ops import base
  from tf_euler.python.euler_ops import type_ops
label_desc: Use image node_id 5 for calling a global function with example usage: sample_neighbor_layerwise(nodes, edge_types, count, default_node, weight_func) and returns: res,  tf