code: def reward_target_molecule_similarity(
      mol, target, radius=2, nBits=2048, useChirality=True
  ):
      """
      Calculate the similarity, based on tanimoto similarity
      between the ECFP fingerprints of the x molecule and target molecule.
  
      Args:
          mol: Rdkit mol object
          target: Rdkit mol object
  
      :rtype:
          :class:`float`, [0.0, 1.0]
      """
      x = rdMolDescriptors.GetMorganFingerprintAsBitVect(
          mol, radius=radius, nBits=nBits, useChirality=useChirality
      )
      target = rdMolDescriptors.GetMorganFingerprintAsBitVect(
          target, radius=radius, nBits=nBits, useChirality=useChirality
      )
      return DataStructs.TanimotoSimilarity(x, target)
  
file_path: DIG/dig/ggraph/utils/environment.py
imports: import copy
  import itertools
  import networkx
  from rdkit import Chem, DataStructs
  from rdkit.Chem import AllChem, rdMolDescriptors
  from rdkit.Chem.Descriptors import MolLogP, qed
  from rdkit.Chem.FilterCatalog import FilterCatalogParams, FilterCatalog
  from .sascorer import calculateScore
label_desc: Use image node_id 8 for calling a global function with example usage: reward_target_molecule_similarity(mol, target, radius, nBits, useChirality) and returns: DataStructs