          return len(self._unset) == 0
  
      @property
      def n_keys(self):
          """Returns True if no keys are available for new keys."""
          return len(self.key2row)
  
      def __reduce__(self):
          keys_and_rows = self.key2row.items()
          return (unpickle_vectors, (keys_and_rows, self.data))
 
</s> remove         """Returns True if no keys are available for new keys."""
 </s> add         """RETURNS (bool): `True` if no slots are available for new keys.""" </s> remove         """Return rows*dims"""
 </s> add         """RETURNS (int): rows*dims""" </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     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         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.
        """RETURNS (int) The number of keys in the table. Note that this is the
        number of all keys, not just unique vectors."""
          return len(self._unset) == 0
  
      @property
      def n_keys(self):
        """RETURNS (int) The number of keys in the table. Note that this is the
        number of all keys, not just unique vectors."""
          return len(self.key2row)
  
      def __reduce__(self):
          keys_and_rows = self.key2row.items()
          return (unpickle_vectors, (keys_and_rows, self.data))
keep keep keep keep replace keep keep keep keep keep
 Update docstrings and simplify most_similar 
spacy/vectors.pyx