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# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# 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.
# Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
""" Code from
https://github.com/NVIDIA/DeepLearningExamples/blob/
master/PyTorch/Translation/Transformer/fairseq/tokenizer.py
"""
import re
import sys
import unicodedata
from collections import defaultdict
__all__ = ['get_unicode_categories', 'tokenize_en']
def get_unicode_categories():
cats = defaultdict(list)
for c in map(chr, range(sys.maxunicode + 1)):
cats[unicodedata.category(c)].append(c)
return cats
NUMERICS = ''.join(get_unicode_categories()['No'])
def tokenize_en(line):
line = line.strip()
line = ' ' + line + ' '
# remove ASCII junk
line = re.sub(r'\s+', ' ', line)
line = re.sub(r'[\x00-\x1F]', '', line)
# fix whitespaces
line = re.sub(r'\ +', ' ', line)
line = re.sub('^ ', '', line)
line = re.sub(' $', '', line)
# separate other special characters
line = re.sub(r'([^\s\.\'\`\,\-\w]|[_' + NUMERICS + '])', r' \g<1> ', line)
line = re.sub(r'(\w)\-(?=\w)', r'\g<1> @-@ ', line)
# multidots stay together
line = re.sub(r'\.([\.]+)', r' DOTMULTI\g<1>', line)
while re.search(r'DOTMULTI\.', line):
line = re.sub(r'DOTMULTI\.([^\.])', r'DOTDOTMULTI \g<1>', line)
line = re.sub(r'DOTMULTI\.', r'DOTDOTMULTI', line)
# separate out "," except if within numbers (5,300)
line = re.sub(r'([\D])[,]', r'\g<1> , ', line)
line = re.sub(r'[,]([\D])', r' , \g<1>', line)
# separate "," after a number if it's the end of sentence
line = re.sub(r'(\d)[,]$', r'\g<1> ,', line)
# split contractions right
line = re.sub(r'([\W\d])[\']([\W\d])', r'\g<1> \' \g<2>', line)
line = re.sub(r'(\W)[\']([\w\D])', r'\g<1> \' \g<2>', line)
line = re.sub(r'([\w\D])[\']([\W\d])', r'\g<1> \' \g<2>', line)
line = re.sub(r'([\w\D])[\']([\w\D])', r'\g<1> \'\g<2>', line)
# special case for "1990's"
line = re.sub(r'([\W\d])[\']([s])', r'\g<1> \'\g<2>', line)
# apply nonbreaking prefixes
words = line.split()
line = ''
for i in range(len(words)):
word = words[i]
match = re.search(r'^(\S+)\.$', word)
if match:
pre = match.group(1)
if i == len(words) - 1:
"""split last words independently as they are unlikely
to be non-breaking prefixes"""
word = pre + ' .'
else:
word = pre + ' .'
word += ' '
line += word
# clean up extraneous spaces
line = re.sub(' +', ' ', line)
line = re.sub('^ ', '', line)
line = re.sub(' $', '', line)
# .' at end of sentence is missed
line = re.sub(r'\.\' ?$', ' . \' ', line)
# restore multi-dots
while re.search('DOTDOTMULTI', line):
line = re.sub('DOTDOTMULTI', 'DOTMULTI.', line)
line = re.sub('DOTMULTI', '.', line)
# escape special characters
line = re.sub(r'\&', r'&amp;', line)
line = re.sub(r'\|', r'&#124;', line)
line = re.sub(r'\<', r'&lt;', line)
line = re.sub(r'\>', r'&gt;', line)
line = re.sub(r'\'', r'&apos;', line)
line = re.sub(r'\"', r'&quot;', line)
line = re.sub(r'\[', r'&#91;', line)
line = re.sub(r'\]', r'&#93;', line)
# ensure final line breaks
# if line[-1] is not '\n':
# line += '\n'
return line