How to use the megnet.utils.general.fast_label_binarize function in megnet

def _create_atom_feature_vector(self, atom: dict) -> List[int]:
        """Generate the feature vector from the atomic feature dictionary

        Handles the binarization of categorical variables, and transforming the ring_sizes to a list

        Args:
            atom (dict): Dictionary of atomic features
        Returns:
            ([int]): Atomic feature vector
        """
        atom_temp = []
        for i in self.atom_features:
            if i == 'chirality':
                atom_temp.extend(fast_label_binarize(atom[i], [0, 1, 2]))
            elif i == 'element':
                atom_temp.extend(fast_label_binarize(atom[i], self.known_elements))
            elif i in ['aromatic', 'donor', 'acceptor']:
                atom_temp.append(int(atom[i]))
            elif i == 'hybridization':
                atom_temp.extend(fast_label_binarize(atom[i], [1, 2, 3, 4, 5, 6]))
            elif i == 'ring_sizes':
                atom_temp.extend(ring_to_vector(atom[i]))
            else:  # It is a scalar
                atom_temp.append(atom[i])
        return atom_temp

def _create_atom_feature_vector(self, atom: dict) -> List[int]:
        """Generate the feature vector from the atomic feature dictionary

        Handles the binarization of categorical variables, and transforming the ring_sizes to a list

        Args:
            atom (dict): Dictionary of atomic features
        Returns:
            ([int]): Atomic feature vector
        """
        atom_temp = []
        for i in self.atom_features:
            if i == 'chirality':
                atom_temp.extend(fast_label_binarize(atom[i], [0, 1, 2]))
            elif i == 'element':
                atom_temp.extend(fast_label_binarize(atom[i], self.known_elements))
            elif i in ['aromatic', 'donor', 'acceptor']:
                atom_temp.append(int(atom[i]))
            elif i == 'hybridization':
                atom_temp.extend(fast_label_binarize(atom[i], [1, 2, 3, 4, 5, 6]))
            elif i == 'ring_sizes':
                atom_temp.extend(ring_to_vector(atom[i]))
            else:  # It is a scalar
                atom_temp.append(atom[i])
        return atom_temp

Args:
            atom (dict): Dictionary of atomic features
        Returns:
            ([int]): Atomic feature vector
        """
        atom_temp = []
        for i in self.atom_features:
            if i == 'chirality':
                atom_temp.extend(fast_label_binarize(atom[i], [0, 1, 2]))
            elif i == 'element':
                atom_temp.extend(fast_label_binarize(atom[i], self.known_elements))
            elif i in ['aromatic', 'donor', 'acceptor']:
                atom_temp.append(int(atom[i]))
            elif i == 'hybridization':
                atom_temp.extend(fast_label_binarize(atom[i], [1, 2, 3, 4, 5, 6]))
            elif i == 'ring_sizes':
                atom_temp.extend(ring_to_vector(atom[i]))
            else:  # It is a scalar
                atom_temp.append(atom[i])
        return atom_temp

def _create_pair_feature_vector(self, bond: dict) -> List[float]:
        """Generate the feature vector from the bond feature dictionary

        Handles the binarization of categorical variables, and performing the distance conversion

        Args:
            bond (dict): Features for a certain pair of atoms
        Returns:
            ([float]) Values converted to a vector
            """
        bond_temp = []
        for i in self.bond_features:
            # Some features require conversion (e.g., binarization)
            if i in bond:
                if i == "bond_type":
                    bond_temp.extend(fast_label_binarize(bond[i], [0, 1, 2, 3, 4]))
                elif i == "same_ring":
                    bond_temp.append(int(bond[i]))
                elif i == "spatial_distance":
                    expanded = self.distance_converter.convert([bond[i]])[0]
                    if isinstance(expanded, np.ndarray):
                        # If we use a distance expansion
                        bond_temp.extend(expanded.tolist())
                    else:
                        # If not
                        bond_temp.append(expanded)
                else:
                    bond_temp.append(bond[i])
        return bond_temp