code: def register_nx(cls):
      NX_EXTRACTORS.append(cls)
      register_feature(cls.__name__)(cls)
      return cls
  
imports: from networkx.algorithms.euler import is_eulerian
  from networkx.algorithms.efficiency_measures import global_efficiency
  from networkx.algorithms.efficiency_measures import local_efficiency
  from networkx.algorithms.distance_regular import is_distance_regular
  from networkx.algorithms.components import number_connected_components
  from networkx.algorithms.components import is_connected
  from networkx.algorithms.cluster import average_clustering
  from networkx.algorithms.cluster import transitivity
  from networkx.algorithms.clique import graph_number_of_cliques
  from networkx.algorithms.clique import graph_clique_number
  from networkx.algorithms.bridges import has_bridges
  from networkx.algorithms.assortativity import degree_pearson_correlation_coefficient
  from networkx.algorithms.assortativity import degree_assortativity_coefficient
  from networkx.algorithms.approximation.clustering_coefficient import average_clustering
  from networkx.algorithms.approximation.clique import large_clique_size
  import netlsd
  from .base import BaseGraph
  import numpy
  import torch
  from functools import wraps
  from ..None import register_feature
label_desc: Use image node_id 1 for calling a global function with example usage: register_nx(cls) and returns: cls