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tokenize.py
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/
tokenize.py
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# coding=utf-8
# Copyright 2024 The Google Research Authors.
#
# 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,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""A library for tokenizing text."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import re
import six
# Pre-compile regexes that are use often
NON_ALPHANUM_PATTERN = r"[^a-z0-9]+"
NON_ALPHANUM_RE = re.compile(NON_ALPHANUM_PATTERN)
SPACES_PATTERN = r"\s+"
SPACES_RE = re.compile(SPACES_PATTERN)
VALID_TOKEN_PATTERN = r"^[a-z0-9]+$"
VALID_TOKEN_RE = re.compile(VALID_TOKEN_PATTERN)
def tokenize(text, stemmer):
"""Tokenize input text into a list of tokens.
This approach aims to replicate the approach taken by Chin-Yew Lin in
the original ROUGE implementation.
Args:
text: A text blob to tokenize.
stemmer: An optional stemmer.
Returns:
A list of string tokens extracted from input text.
"""
# Convert everything to lowercase.
text = text.lower()
# Replace any non-alpha-numeric characters with spaces.
text = NON_ALPHANUM_RE.sub(" ", six.ensure_str(text))
tokens = SPACES_RE.split(text)
if stemmer:
# Only stem words more than 3 characters long.
tokens = [six.ensure_str(stemmer.stem(x)) if len(x) > 3 else x
for x in tokens]
# One final check to drop any empty or invalid tokens.
tokens = [x for x in tokens if VALID_TOKEN_RE.match(x)]
return tokens