code: def get_atom_type(atom):
      elem = atom.GetAtomicNum()
      hyb = str(atom.GetHybridization).lower()
      if elem == 1:
          return 0
      if elem == 4:
          return 1
      if elem == 5:
          return 2
      if elem == 6:
          if "sp2" in hyb:
              return 3
          elif "sp3" in hyb:
              return 4
          else:
              return 5
      if elem == 7:
          if "sp2" in hyb:
              return 6
          elif "sp3" in hyb:
              return 7
          else:
              return 8
      if elem == 8:
          if "sp2" in hyb:
              return 9
          elif "sp3" in hyb:
              return 10
          else:
              return 11
      if elem == 9:
          return 12
      if elem == 15:
          if "sp2" in hyb:
              return 13
          elif "sp3" in hyb:
              return 14
          else:
              return 15
      if elem == 16:
          if "sp2" in hyb:
              return 16
          elif "sp3" in hyb:
              return 17
          else:
              return 18
      if elem == 17:
          return 19
      if elem == 35:
          return 20
      if elem == 53:
          return 21
      return 22
  
file_path: deepchem/contrib/torch/adjacency_fingerprint.py
imports: from collections import deque
  import sys
  import tensorflow
  import pickle
  import os
  import fnmatch
  import numpy
  from scipy.spatial.distance import pdist, squareform
  import pandas
  from deepchem.feat.base_classes import Featurizer
  from deepchem.feat.graph_features import atom_features
  from scipy.sparse import csr_matrix
label_desc: Use image node_id 1 for calling a global function with example usage: get_atom_type(atom) and returns: int, int, int, int, int, int, int, int, int, int, int, int, int, int, int, int, int, int, int, int, int, int, int