          vectors, vectors.300.d.bin for 300d float64 (double) vectors, etc.
          By default GloVe outputs 64-bit vectors.
  
          path (unicode / Path): The path to load the GloVe vectors from.
  
          RETURNS: A StringStore object, holding the key-to-string mapping.
          """
          path = util.ensure_path(path)
          width = None
          for name in path.iterdir():
              if name.parts[-1].startswith('vectors'):
 
</s> remove         key (unicode / int): The key to add.
        vector (numpy.ndarray / None): A vector to add for the key.
        row (int / None): The row-number of a vector to map the key to.
 </s> add         key (int): The key to add.
        vector (ndarray / None): A vector to add for the key.
        row (int / None): The row number of a vector to map the key to.
        RETURNS (int): The row the vector was added to. </s> remove         if return_rows and return_scores:
            return (keys, best_rows, scores)
        elif return_rows:
            return (keys, best_rows)
        elif return_scores:
            return (keys, scores)
        else:
            return keys
 </s> add         return (keys, best_rows, scores) </s> remove         Queries are by vector. Results are returned as an array of keys,
        or a tuple of (keys, scores) if return_scores=True. If `queries` is
        large, the calculations are performed in chunks, to avoid consuming
        too much memory. You can set the `batch_size` to control the size/space
        trade-off during the calculations.
        '''
 </s> add         Queries are by vector. Results are returned as a `(keys, best_rows,
        scores)` tuple. If `queries` is large, the calculations are performed in
        chunks, to avoid consuming too much memory. You can set the `batch_size`
        to control the size/space trade-off during the calculations.

        queries (ndarray): An array with one or more vectors.
        batch_size (int): The batch size to use.
        RETURNS (tuple): The most similar entry as a `(keys, best_rows, scores)`
            tuple.
        """ </s> remove     def most_similar(self, queries, *, return_scores=False, return_rows=False,
            batch_size=1024):
        '''For each of the given vectors, find the single entry most similar
 </s> add     def most_similar(self, queries, *, batch_size=1024):
        """For each of the given vectors, find the single entry most similar </s> remove         """Returns True if no keys are available for new keys."""
 </s> add         """RETURNS (int) The number of keys in the table. Note that this is the
        number of all keys, not just unique vectors."""
        RETURNS: A `StringStore` object, holding the key-to-string mapping.
          vectors, vectors.300.d.bin for 300d float64 (double) vectors, etc.
          By default GloVe outputs 64-bit vectors.
  
          path (unicode / Path): The path to load the GloVe vectors from.
        RETURNS: A `StringStore` object, holding the key-to-string mapping.
        RETURNS: A `StringStore` object, holding the key-to-string mapping.
          """
          path = util.ensure_path(path)
          width = None
          for name in path.iterdir():
              if name.parts[-1].startswith('vectors'):
keep keep keep keep replace replace keep keep keep keep keep
 Update docstrings and simplify most_similar 
spacy/vectors.pyx