# 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'&', line) line = re.sub(r'\|', r'|', line) line = re.sub(r'\<', r'<', line) line = re.sub(r'\>', r'>', line) line = re.sub(r'\'', r''', line) line = re.sub(r'\"', r'"', line) line = re.sub(r'\[', r'[', line) line = re.sub(r'\]', r']', line) # ensure final line breaks # if line[-1] is not '\n': # line += '\n' return line