# Copyright 2021-2023 Cambridge Quantum Computing Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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from __future__ import annotations
__all__ = ['Tokeniser']
from abc import ABC, abstractmethod
from collections.abc import Iterable
[docs]class Tokeniser(ABC):
"""Base Class for all tokenisers"""
[docs] @abstractmethod
def split_sentences(self, text: str) -> list[str]:
"""Split input text into a list of sentences.
Parameters
----------
text : str
A single string that contains one or multiple sentences.
Returns
-------
list of str
List of sentences, one sentence in each string.
"""
[docs] @abstractmethod
def tokenise_sentences(self, sentences: Iterable[str]) -> list[list[str]]:
"""Tokenise a list of sentences.
Parameters
----------
sentences : list of str
A list of untokenised sentences.
Returns
-------
list of list of str
A list of tokenised sentences, where each sentence is a list
of tokens - strings
"""
[docs] def tokenise_sentence(self, sentence: str) -> list[str]:
"""Tokenise a sentence.
Parameters
----------
sentence : str
An untokenised sentence.
Returns
-------
list of str
A tokenised sentence given as a list of tokens - strings.
"""
return self.tokenise_sentences([sentence])[0]