code: def atom_features(
      atom, bool_id_feat=False, explicit_H=False, use_chirality=False
  ):
      """Helper method used to compute per-atom feature vectors.
  
      Many different featurization methods compute per-atom features such as ConvMolFeaturizer, WeaveFeaturizer. This method computes such features.
  
      Parameters
      ----------
      atom: RDKit.Chem.rdchem.Atom
          Atom to compute features on.
      bool_id_feat: bool, optional
          Return an array of unique identifiers corresponding to atom type.
      explicit_H: bool, optional
          If true, model hydrogens explicitly
      use_chirality: bool, optional
          If true, use chirality information.
  
      Returns
      -------
      features: np.ndarray
          An array of per-atom features.
  
      Examples
      --------
      >>> from rdkit import Chem
      >>> mol = Chem.MolFromSmiles('CCC')
      >>> atom = mol.GetAtoms()[0]
      >>> features = dc.feat.graph_features.atom_features(atom)
      >>> type(features)
      <class 'numpy.ndarray'>
      >>> features.shape
      (75,)
  
      """
      if bool_id_feat:
          return np.array([atom_to_id(atom)])
      else:
          from rdkit import Chem
  
          results = (
              one_of_k_encoding_unk(
                  atom.GetSymbol(),
                  [
                      "C",
                      "N",
                      "O",
                      "S",
                      "F",
                      "Si",
                      "P",
                      "Cl",
                      "Br",
                      "Mg",
                      "Na",
                      "Ca",
                      "Fe",
                      "As",
                      "Al",
                      "I",
                      "B",
                      "V",
                      "K",
                      "Tl",
                      "Yb",
                      "Sb",
                      "Sn",
                      "Ag",
                      "Pd",
                      "Co",
                      "Se",
                      "Ti",
                      "Zn",
                      "H",  # H?
                      "Li",
                      "Ge",
                      "Cu",
                      "Au",
                      "Ni",
                      "Cd",
                      "In",
                      "Mn",
                      "Zr",
                      "Cr",
                      "Pt",
                      "Hg",
                      "Pb",
                      "Unknown",
                  ],
              )
              + one_of_k_encoding(
                  atom.GetDegree(), [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
              )
              + one_of_k_encoding_unk(
                  atom.GetImplicitValence(), [0, 1, 2, 3, 4, 5, 6]
              )
              + [atom.GetFormalCharge(), atom.GetNumRadicalElectrons()]
              + one_of_k_encoding_unk(
                  atom.GetHybridization(),
                  [
                      Chem.rdchem.HybridizationType.SP,
                      Chem.rdchem.HybridizationType.SP2,
                      Chem.rdchem.HybridizationType.SP3,
                      Chem.rdchem.HybridizationType.SP3D,
                      Chem.rdchem.HybridizationType.SP3D2,
                  ],
              )
              + [atom.GetIsAromatic()]
          )
          # In case of explicit hydrogen(QM8, QM9), avoid calling `GetTotalNumHs`
          if not explicit_H:
              results = results + one_of_k_encoding_unk(
                  atom.GetTotalNumHs(), [0, 1, 2, 3, 4]
              )
          if use_chirality:
              try:
                  results = (
                      results
                      + one_of_k_encoding_unk(
                          atom.GetProp("_CIPCode"), ["R", "S"]
                      )
                      + [atom.HasProp("_ChiralityPossible")]
                  )
              except:
                  results = (
                      results
                      + [False, False]
                      + [atom.HasProp("_ChiralityPossible")]
                  )
  
          return np.array(results)
  
imports: import numpy
  import deepchem
  from deepchem.feat.base_classes import MolecularFeaturizer
  from deepchem.feat.mol_graphs import ConvMol, WeaveMol
  from deepchem.data import DiskDataset
  import logging
  from typing import Optional, List, Tuple, Union, Iterable
  from deepchem.utils.typing import RDKitMol, RDKitAtom
  from deepchem.utils.molecule_feature_utils import one_hot_encode
label_desc: Use image node_id 9 for calling a global function with example usage: atom_features(atom, bool_id_feat, explicit_H, use_chirality) and returns: np, np