class_docstr: Transform molecules from a latent space feature vector into
  a one hot encoding.
  https://arxiv.org/abs/1610.02415
class_docstr_tok: ["Transform","molecules","from","a","latent","space","feature","vector","into","a","one","hot","encoding",".","https",":","\/\/arxiv.org\/abs\/1610.02415"]
code: def predict_on_batch(self, X):
      x_latent = self.model.decoder.predict(X)
      return x_latent
  
file_path: deepchem/contrib/autoencoder_models/autoencoder.py
imports: import warnings
  from deepchem.models import Model
  from deepchem.models.autoencoder_models.model import MoleculeVAE
  from deepchem.feat.one_hot import zinc_charset
  from deepchem.utils import download_url
  import os
  from subprocess import call
label_desc: Use image node_id 4 for calling the TensorflowMoleculeDecoder obj's underlying member method code with example usage: obj.predict_on_batch(X) and returns: x_latent