code: def sparse2graph(x):
      G = defaultdict(lambda: set())
      cx = x.tocoo()
      for i, j, v in zip(cx.row, cx.col, cx.data):
          G[i].add(j)
      return {str(k): [str(x) for x in v] for k, v in iteritems(G)}
  
file_path: deepwalk/example_graphs/scoring.py
imports: import numpy
  import sys
  from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
  from collections import defaultdict
  from gensim.models import Word2Vec, KeyedVectors
  from six import iteritems
  from sklearn.multiclass import OneVsRestClassifier
  from sklearn.linear_model import LogisticRegression
  from sklearn.metrics import f1_score
  from scipy.io import loadmat
  from sklearn.utils import shuffle
  from sklearn.preprocessing import MultiLabelBinarizer
label_desc: Use image node_id 1 for calling a global function with example usage: sparse2graph(x) and returns: unknown