To help you get started, we've collected the most common ways that sacremoses is being used within popular public projects.

Findus23 / se-simulator / markov.py View on Github

import markovify
from sacremoses import MosesDetokenizer, MosesTokenizer

tokenizer = MosesTokenizer()
detokenizer = MosesDetokenizer()


class MarkovText(markovify.Text):
    def word_split(self, sentence):
        return tokenizer.tokenize(sentence)

    def word_join(self, words):
        return detokenizer.detokenize(words, return_str=True)


class MarkovUserName(markovify.Text):
    def word_split(self, word):
        return list(word)

    def word_join(self, characters):

View more ways to use sacremoses

Sacremoses

License

MIT License.

Install

pip install -U sacremoses

NOTE: Sacremoses only supports Python 3 now (sacremoses>=0.0.41). If you're using Python 2, the last possible version is sacremoses==0.0.40.

Usage (Python)

Tokenizer and Detokenizer

>>> from sacremoses import MosesTokenizer, MosesDetokenizer
>>> mt = MosesTokenizer(lang='en')
>>> text = 'This, is a sentence with weird\xbb symbols\u2026 appearing everywhere\xbf'
>>> expected_tokenized = 'This , is a sentence with weird \xbb symbols \u2026 appearing everywhere \xbf'
>>> tokenized_text = mt.tokenize(text, return_str=True)
>>> tokenized_text == expected_tokenized
True


>>> mt, md = MosesTokenizer(lang='en'), MosesDetokenizer(lang='en')
>>> sent = "This ain't funny. It's actually hillarious, yet double Ls. | [] < > [ ] & You're gonna shake it off? Don't?"
>>> expected_tokens = ['This', 'ain', ''t', 'funny', '.', 'It', ''s', 'actually', 'hillarious', ',', 'yet', 'double', 'Ls', '.', '|', '[', ']', '<', '>', '[', ']', '&', 'You', ''re', 'gonna', 'shake', 'it', 'off', '?', 'Don', ''t', '?']
>>> expected_detokens = "This ain't funny. It's actually hillarious, yet double Ls. | [] < > [] & You're gonna shake it off? Don't?"
>>> mt.tokenize(sent) == expected_tokens
True
>>> md.detokenize(tokens) == expected_detokens
True

Truecaser

>>> from sacremoses import MosesTruecaser, MosesTokenizer

# Train a new truecaser from a 'big.txt' file.
>>> mtr = MosesTruecaser()
>>> mtok = MosesTokenizer(lang='en')

# Save the truecase model to 'big.truecasemodel' using `save_to`
>> tokenized_docs = [mtok.tokenize(line) for line in open('big.txt')]
>>> mtr.train(tokenized_docs, save_to='big.truecasemodel')

# Save the truecase model to 'big.truecasemodel' after training
# (just in case you forgot to use `save_to`)
>>> mtr = MosesTruecaser()
>>> mtr.train('big.txt')
>>> mtr.save_model('big.truecasemodel')

# Truecase a string after training a model.
>>> mtr = MosesTruecaser()
>>> mtr.train('big.txt')
>>> mtr.truecase("THE ADVENTURES OF SHERLOCK HOLMES")
['the', 'adventures', 'of', 'Sherlock', 'Holmes']

# Loads a model and truecase a string using trained model.
>>> mtr = MosesTruecaser('big.truecasemodel')
>>> mtr.truecase("THE ADVENTURES OF SHERLOCK HOLMES")
['the', 'adventures', 'of', 'Sherlock', 'Holmes']
>>> mtr.truecase("THE ADVENTURES OF SHERLOCK HOLMES", use_known=True)
['the', 'ADVENTURES', 'OF', 'SHERLOCK', 'HOLMES']
>>> mtr.truecase("THE ADVENTURES OF SHERLOCK HOLMES", return_str=True)
'the adventures of Sherlock Holmes'

Normalizer

>>> from sacremoses import MosesPunctNormalizer
>>> mpn = MosesPunctNormalizer()
>>> mpn.normalize('THIS EBOOK IS OTHERWISE PROVIDED TO YOU "AS-IS."')
'THIS EBOOK IS OTHERWISE PROVIDED TO YOU "AS-IS."'

Usage (CLI)

Since version 0.0.42, the pipeline feature for CLI is introduced, thus there are global options that should be set first before calling the commands:

• language
• processes
• encoding
• quiet

$ pip install -U sacremoses>=0.1

$ sacremoses --help
Usage: sacremoses [OPTIONS] COMMAND1 [ARGS]... [COMMAND2 [ARGS]...]...

Options:
  -l, --language TEXT      Use language specific rules when tokenizing
  -j, --processes INTEGER  No. of processes.
  -e, --encoding TEXT      Specify encoding of file.
  -q, --quiet              Disable progress bar.
  --version                Show the version and exit.
  -h, --help               Show this message and exit.

Commands:
  detokenize
  detruecase
  normalize
  tokenize
  train-truecase
  truecase

Pipeline

Example to chain the following commands:

• normalize with -c option to remove control characters.
• tokenize with -a option for aggressive dash split rules.
• truecase with -a option to indicate that model is for ASR
  • if big.truemodel exists, load the model with -m option,
  • otherwise train a model and save it with -m option to big.truemodel file.
• save the output to console to the big.txt.norm.tok.true file.

cat big.txt | sacremoses -l en -j 4 \
    normalize -c tokenize -a truecase -a -m big.truemodel \
    > big.txt.norm.tok.true

Tokenizer

$ sacremoses tokenize --help
Usage: sacremoses tokenize [OPTIONS]

Options:
  -a, --aggressive-dash-splits   Triggers dash split rules.
  -x, --xml-escape               Escape special characters for XML.
  -p, --protected-patterns TEXT  Specify file with patters to be protected in
                                 tokenisation.
  -c, --custom-nb-prefixes TEXT  Specify a custom non-breaking prefixes file,
                                 add prefixes to the default ones from the
                                 specified language.
  -h, --help                     Show this message and exit.


 $ sacremoses -l en -j 4 tokenize  < big.txt > big.txt.tok
100%|██████████████████████████████████| 128457/128457 [00:05<00:00, 24363.39it/s

 $ wget https://raw.githubusercontent.com/moses-smt/mosesdecoder/master/scripts/tokenizer/basic-protected-patterns
 $ sacremoses -l en -j 4 tokenize -p basic-protected-patterns < big.txt > big.txt.tok
100%|██████████████████████████████████| 128457/128457 [00:05<00:00, 22183.94it/s

Detokenizer

$ sacremoses detokenize --help
Usage: sacremoses detokenize [OPTIONS]

Options:
  -x, --xml-unescape  Unescape special characters for XML.
  -h, --help          Show this message and exit.

 $ sacremoses -l en -j 4 detokenize < big.txt.tok > big.txt.tok.detok
100%|██████████████████████████████████| 128457/128457 [00:16<00:00, 7931.26it/s]

Truecase

$ sacremoses truecase --help
Usage: sacremoses truecase [OPTIONS]

Options:
  -m, --modelfile TEXT            Filename to save/load the modelfile.
                                  [required]
  -a, --is-asr                    A flag to indicate that model is for ASR.
  -p, --possibly-use-first-token  Use the first token as part of truecase
                                  training.
  -h, --help                      Show this message and exit.

$ sacremoses -j 4 truecase -m big.model < big.txt.tok > big.txt.tok.true
100%|██████████████████████████████████| 128457/128457 [00:09<00:00, 14257.27it/s]

Detruecase

$ sacremoses detruecase --help
Usage: sacremoses detruecase [OPTIONS]

Options:
  -j, --processes INTEGER  No. of processes.
  -a, --is-headline        Whether the file are headlines.
  -e, --encoding TEXT      Specify encoding of file.
  -h, --help               Show this message and exit.

$ sacremoses -j 4 detruecase  < big.txt.tok.true > big.txt.tok.true.detrue
100%|█████████████████████████████████| 128457/128457 [00:04<00:00, 26945.16it/s]

Normalize

$ sacremoses normalize --help
Usage: sacremoses normalize [OPTIONS]

Options:
  -q, --normalize-quote-commas  Normalize quotations and commas.
  -d, --normalize-numbers       Normalize number.
  -p, --replace-unicode-puncts  Replace unicode punctuations BEFORE
                                normalization.
  -c, --remove-control-chars    Remove control characters AFTER normalization.
  -h, --help                    Show this message and exit.

$ sacremoses -j 4 normalize < big.txt > big.txt.norm
100%|██████████████████████████████████| 128457/128457 [00:09<00:00, 13096.23it/s]