Change charset and max_length handling

  learning tasks.

  """

  def __init__(self, featurizer = OneHotFeaturizer, charset: Optional[str] = "ATCGN", max_length: Optional[int] = None):

  def __init__(self, featurizer = OneHotFeaturizer, charset: Union[str, tuple, None] = "ATCGN", max_length: Optional[int] = None):

    """Initialize FASTALoader.

    Parameters

      Whether or not the sequence passed in is a protein sequence. If False,

      it is treated as a nucleic acid sequence.

    charset: Optional[str] (default: "ATCGN")

      The charset used in the loaded FASTA file. Currently, we support ATCGN,

      full FASTA-format protein sequences, and full FASTA format nucleic acid

      sequences.

      Currently acceptable charsets are: "protein", "nucleic", and "ATCGN".

    charset: Union[str, tuple, None] (default: "ATCGN")

      The charset used in the loaded FASTA file.

      str arguments "protein", "nucleic", and "ATCGN" will respectively load

      a FASTA format protein sequence character set, FASTA format nucleic acid

      sequence character set, and ATCG character set.

      If you choose to pass in a tuple, the tuple will be directly used as the

      charset during featurization.

      If charset is None, no charset will be passed to your featurizer. This

      is not recommended unless your featurizer doesn't have a charset parameter.

    max_length: Optional[int] (default: None)

      max_length is only used if featurizer = OneHotFeaturizer.

      The length that all strings are padded to before featurization.

      max_length must be larger than the length of the longest string that is

      being featurized.

      max_length should be equal to or larger than the length of the longest

      string that is being featurized. max_length is passed to the featurizer.

      OneHotFeaturizer pads all strings to max_length with spaces.

      If max_length is None, it is not passed to the featurizer.

    """

    charsets = {

      "protein": ('A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L',

                  'B', 'D', 'H', 'V', 'N', '-'),

      "ATCGN": ('A', 'T', 'C', 'G')

    }

    # Initialize self.max_length and self.charset

    self.max_length = max_length

    if isinstance(charset, str):

      try:

        self.charset = charsets[charset]

      except KeyError:

      if (featurizer == OneHotFeaturizer): # TODO EXPLICITLY CHECK IF FEATURIZER USES CHARSET

        logger.exception("charset is invalid. charset must be 'protein', 'nucleic', or 'ATCGN'.")

        logger.warning("Charset is invalid. Treating as None...")

        self.charset = None

    elif isinstance(charset, tuple):

      self.charset = charset

    else:

        logger.warning("charset is invalid, ignoring...")

      self.charset = None

    # Set user defined featurizer

    self.user_specified_features = None

    if isinstance(featurizer, UserDefinedFeaturizer):

      self.user_specified_features = featurizer.feature_fields

    featurizer = featurizer(charset = self.charset, max_length = max_length) # TODO EXPLICITLY CHECK IF MAX_LENGTH IS DESIRED

    # Initialize featurizer

    try:

      if self.charset is None and self.max_length is None:

        featurizer = featurizer()

      elif self.charset is not None and self.max_length is None:

        featurizer = featurizer(charset = self.charset)

      elif self.charset is None and self.max_length is not None:

        featurizer = featurizer(max_length = self.max_length)

      else:

        featurizer = featurizer(charset = self.charset, max_length = self.max_length)

    except:

      logger.exception("Sorry! Your featurizer may not be supported yet.")

    self.featurizer = featurizer

  def create_dataset(self,