class_docstr: Transform molecules from one hot encoding into a latent vector
  representation.
  https://arxiv.org/abs/1610.02415
class_docstr_tok: ["Transform","molecules","from","one","hot","encoding","into","a","latent","vector","representation",".","https",":","\/\/arxiv.org\/abs\/1610.02415"]
docstr: Parameters
  ----------
  model_dir: str
    Folder to store cached weights
  weights_file: str
    File to store cached weights in model_dir
  verbose: bool
    True for more logging
  charset_length: int
    Length of one_hot_encoded vectors
  latent_rep_size: int
    How large a 1D Vector for latent representation
docstr_tok: ["Parameters","--","--","--","--","--","model_dir",":","str","Folder","to","store","cached","weights","weights_file",":","str","File","to","store","cached","weights","in","model_dir","verbose",":","bool","True","for","more","logging","charset_length",":","int","Length","of","one_hot_encoded","vectors","latent_rep_size",":","int","How","large","a","1D","Vector","for","latent","representation"]
code: def __init__(
      self,
      model_dir=None,
      weights_file="model.h5",
      verbose=True,
      charset_length=len(zinc_charset),
      latent_rep_size=292,
  ):
      """
  
      Parameters
      ----------
      model_dir: str
        Folder to store cached weights
      weights_file: str
        File to store cached weights in model_dir
      verbose: bool
        True for more logging
      charset_length: int
        Length of one_hot_encoded vectors
      latent_rep_size: int
        How large a 1D Vector for latent representation
      """
      warnings.warn(
          "TensorflowMoleculeEncoder Deprecated. "
          "Will be removed in DeepChem 1.4.",
          DeprecationWarning,
      )
      super(TensorflowMoleculeEncoder, self).__init__(
          model_dir=model_dir, verbose=verbose
      )
      weights_file = os.path.join(model_dir, weights_file)
      if os.path.isfile(weights_file):
          m = MoleculeVAE()
          m.load(
              charset_length,
              weights_file,
              latent_rep_size=latent_rep_size,
          )
          self.model = m
      else:
          # TODO (LESWING) Lazy Load
          raise ValueError("Model file %s doesn't exist" % weights_file)
  
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 1 to create a new TensorflowMoleculeEncoder object from inherited base classes: Model with example: obj = TensorflowMoleculeEncoder(model_dir, weights_file, verbose, charset_length, latent_rep_size)