(self, extractive_types: List[Text])
Initializes a new ExtractiveScorer.

    Valid extractive types that can be computed are:
      coverage: Extractive fragment coverage is the percentage of words in
        the summary that are from the source article, measuring the extent to
        which a summary is derivative of a text.
      density: Extractive density is defined as the average length of the
       extractive fragment to which each summary word belongs.
      normalized_density: density is normalized by |S|^2 instead of |S|.

    Args:
      extractive_types: A list of extractive types to calculate.

    Returns:
      A dict mapping regs types to Score tuples.
Initializes a new ExtractiveScorer.
Initializes a new ExtractiveScorer .
def __init__(self, extractive_types: List[Text]):
    """Initializes a new ExtractiveScorer.

    Valid extractive types that can be computed are:
      coverage: Extractive fragment coverage is the percentage of words in
        the summary that are from the source article, measuring the extent to
        which a summary is derivative of a text.
      density: Extractive density is defined as the average length of the
       extractive fragment to which each summary word belongs.
      normalized_density: density is normalized by |S|^2 instead of |S|.

    Args:
      extractive_types: A list of extractive types to calculate.

    Returns:
      A dict mapping regs types to Score tuples.
    """
    self._tokenize = lambda s: tokenize.tokenize(s, None)
    self.extractive_types = extractive_types
def __init__ ( self , extractive_types : List [ Text ] ) : self . _tokenize = lambda s : tokenize . tokenize ( s , None ) self . extractive_types = extractive_types