tokenization.py

# code adapted from https://github.com/google-research/bert

# modification of tokenization.py for GEC

"""Tokenization classes."""

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import collections
import unicodedata
import six
import tensorflow as tf

from autocorrect import spell
from spellcheck_utils import can_spellcheck
import re


special_tokens = {"n't":"not", "'m":"am", "ca":"can", "Ca":"Can", "wo":"would", "Wo":"Would",
                  "'ll":"will", "'ve":"have"} 
def containsNumber(text):
  reg_ex = re.compile(r".*[0-9].*")
  if reg_ex.match(text):
    #print("{} contains numbers".format(text))
    return True
  else:
    return False

def containsMultiCapital(text):
  reg_ex=re.compile(r".*[A-Z].*[A-Z].*")
  if reg_ex.match(text):
    #print("{} conatains multiple capitals".format(text))
    return True
  else:
    return False


def checkAlternateDots(text):
  if text[0]==".":
    return False
  alt = text[1::2]
  if set(alt) == {'.'}:
    #print("{} contains alternate dots".format(text))
    return True
  else:
    return False

def end_with_dotcom(text):
  if len(text)>=4 and text[-4:]==".com":
    #print("{} contains .com in the end".format(text))
    return True
  else:
    return False

def starts_with_www(text):
  reg_ex = re.compile(r"^www\..*")
  if reg_ex.match(text):
    #print("{} starts with www.".format(text))
    return True
  else:
    return False

def contains_slash(text):
  if "/" in text:
    #print("{} contains /".format(text))
    return True
  else:
    return False

def contains_percent(text):
  if "%" in text:
    #print("{} contains %".format(text))
    return True  
  else:
    return False

def contains_ampersand(text):
  if "&" in text:
    #print("{} contains &".format(text))
    return True
  else:
    return False

def contains_at_rate(text):
  if "@" in text:
    #print("{} contains @".format(text))
    return True
  else:
    return False

def contains_square_brackets(text):
  if "[" in text or "]" in text:
    #print("{} contains ] or [".format(text))
    return True
  else:
    return False

def last_dot_first_capital(text):
  if len(text) > 1 and text[-1]=="." and text[0].upper()==text[0]:
    #print("{} has dot as last letter and it's first letter is capital".format(text))
    return True
  else:
    return False

def check_smilies(text):
  if text in [":)",":(",";)",":/",":|"]:
    #print("{} is a smiley".format(text))
    return True
  else:
    return False

def do_not_split(text, mode="test"):

  if mode == "train":
    #print("************************* SPLIT IS ON *************************************")
    return False

  if containsNumber(text) or containsMultiCapital(text) or checkAlternateDots(text) \
  or end_with_dotcom(text) or starts_with_www(text) or contains_at_rate(text) \
  or contains_slash(text) or contains_percent(text) or contains_ampersand(text) \
  or contains_square_brackets(text) \
  or last_dot_first_capital(text) \
  or check_smilies(text):
    return True
  else:
    return False

'''
def contains_round(text):
  if ")" in text or "(" in text:
    print("contains_right_round firing on {}".format(text))
    return True
  else:
    return False
'''

def spell_check(text):
  if not can_spellcheck(text):
    return None
  result = spell(text)
  return result
  '''
  if (text[0].isupper() == result[0].isupper()): #avoid case change due to spelling correction
    return result
  else:
    return None
  '''

def check_alternate_in_vocab(word,vocab):
  assert word not in vocab

  if word == word.lower():
    tmp = word[0].upper() + word[1:]
  else:
    tmp = word.lower()

  if tmp in vocab:
    #print("replacing {} with its alternate {}".format(word, tmp))
    return tmp
  else:
    return None


def convert_to_unicode(text):
  """Converts `text` to Unicode (if it's not already), assuming utf-8 input."""
  if six.PY3:
    if isinstance(text, str):
      return text
    elif isinstance(text, bytes):
      return text.decode("utf-8", "ignore")
    else:
      raise ValueError("Unsupported string type: %s" % (type(text)))
  elif six.PY2:
    if isinstance(text, str):
      return text.decode("utf-8", "ignore")
    elif isinstance(text, unicode):
      return text
    else:
      raise ValueError("Unsupported string type: %s" % (type(text)))
  else:
    raise ValueError("Not running on Python2 or Python 3?")


def printable_text(text):
  """Returns text encoded in a way suitable for print or `tf.logging`."""

  # These functions want `str` for both Python2 and Python3, but in one case
  # it's a Unicode string and in the other it's a byte string.
  if six.PY3:
    if isinstance(text, str):
      return text
    elif isinstance(text, bytes):
      return text.decode("utf-8", "ignore")
    else:
      raise ValueError("Unsupported string type: %s" % (type(text)))
  elif six.PY2:
    if isinstance(text, str):
      return text
    elif isinstance(text, unicode):
      return text.encode("utf-8")
    else:
      raise ValueError("Unsupported string type: %s" % (type(text)))
  else:
    raise ValueError("Not running on Python2 or Python 3?")


def load_vocab(vocab_file):
  """Loads a vocabulary file into a dictionary."""
  vocab = collections.OrderedDict()
  index = 0
  with tf.gfile.GFile(vocab_file, "r") as reader:
    while True:
      token = convert_to_unicode(reader.readline())
      if not token:
        break
      token = token.strip()
      vocab[token] = index
      index += 1
  return vocab


def convert_by_vocab(vocab, items):
  """Converts a sequence of [tokens|ids] using the vocab."""
  output = []
  for item in items:
    output.append(vocab[item])
  return output


def convert_tokens_to_ids(vocab, tokens):
  return convert_by_vocab(vocab, tokens)


def convert_ids_to_tokens(inv_vocab, ids):
  return convert_by_vocab(inv_vocab, ids)


def whitespace_tokenize(text):
  """Runs basic whitespace cleaning and splitting on a piece of text."""
  text = text.strip()
  if not text:
    return []
  tokens = text.split()
  return tokens


class FullTokenizer(object):
  """Runs end-to-end tokenziation."""

  def __init__(self, vocab_file, do_lower_case=True):
    self.vocab = load_vocab(vocab_file)
    self.inv_vocab = {v: k for k, v in self.vocab.items()}
    self.basic_tokenizer = BasicTokenizer(do_lower_case=do_lower_case, vocab=self.vocab)
    self.wordpiece_tokenizer = WordpieceTokenizer(vocab=self.vocab)

  def tokenize(self, text, mode="test"):
    split_tokens = []
    for token in self.basic_tokenizer.tokenize(text,mode):
      #print("Hello")
      if (len(token) > 1 and do_not_split(token,mode)) or (token in special_tokens):
        split_tokens.append(token)
      else:
        wordpiece_tokens = self.wordpiece_tokenizer.tokenize(token)
        if len(wordpiece_tokens) > 1:
          if token.capitalize() in self.vocab:
            split_tokens.append(token.capitalize())
          elif token.lower() in self.vocab:
            split_tokens.append(token.lower())
          elif token.upper() in self.vocab:
            split_tokens.append(token.upper())
          elif len(wordpiece_tokens) <=3:
            split_tokens.extend(wordpiece_tokens)
          else:
            split_tokens.append(token)
        else:
          split_tokens.append(token)
    return split_tokens

  def convert_tokens_to_ids(self,items):
    output = []
    for item in items:
      if item in special_tokens:
        output.append(self.vocab[special_tokens[item]])
      elif item in self.vocab:
        output.append(self.vocab[item])
      else:
        if item.capitalize() in self.vocab:
          output.append(self.vocab[item.capitalize()])
        elif item.lower() in self.vocab:
          output.append(self.vocab[item.lower()])
        elif item.upper() in self.vocab:
          output.append(self.vocab[item.upper()])
        else:
          output.append(self.vocab["[UNK]"])
    return output

  #def convert_tokens_to_ids(self, tokens):
  #  return convert_by_vocab(self.vocab, tokens)

  def convert_ids_to_tokens(self, ids):
    return convert_by_vocab(self.inv_vocab, ids)


class BasicTokenizer(object):
  """Runs basic tokenization (punctuation splitting, lower casing, etc.)."""

  def __init__(self, do_lower_case=True, vocab=None):
    """Constructs a BasicTokenizer.

    Args:
      do_lower_case: Whether to lower case the input.
    """
    self.do_lower_case = do_lower_case
    self.vocab = vocab

  def tokenize(self, text, mode="test"):
    """Tokenizes a piece of text."""
    text = convert_to_unicode(text)
    text = self._clean_text(text)

    # This was added on November 1st, 2018 for the multilingual and Chinese
    # models. This is also applied to the English models now, but it doesn't
    # matter since the English models were not trained on any Chinese data
    # and generally don't have any Chinese data in them (there are Chinese
    # characters in the vocabulary because Wikipedia does have some Chinese
    # words in the English Wikipedia.).
    text = self._tokenize_chinese_chars(text)

    orig_tokens = whitespace_tokenize(text)
    split_tokens = []
    for token in orig_tokens:
      if self.do_lower_case:
        token = token.lower()
        token = self._run_strip_accents(token)

      if len(token)==1 or do_not_split(token,mode) or (token in special_tokens):
        split_tokens.append(token)
      else:
        split_tokens.extend(self._run_split_on_punc(token))

    use_spell_check=False
    if use_spell_check:
     split_tokens = self._run_spell_check(split_tokens)

    output_tokens = whitespace_tokenize(" ".join(split_tokens))
    return output_tokens

  def _run_spell_check(self, tokens):
    corrected_tokens = []
    for word in tokens:
      output_word = None
      if (word in self.vocab) or (word.lower() in self.vocab) or (word.capitalize() in self.vocab) or (word.upper() in self.vocab) or do_not_split(word,"test"):
        output_word = word
      else:
        spell_checked_word = spell_check(word)
        if spell_checked_word:
          if (spell_checked_word in self.vocab):
            #print("spell check FINDS word in VOCAB --- {} --> {}".format(word, spell(word)))
            output_word=spell_checked_word
          else:
            if word[0].isupper(): 
              # "this case should never be encountered because spell_checked_word is None for cased words
              print("Error this should not be encountered")
              exit(1)
            else:
              output_word=spell_checked_word
              #print("Spell check DID NOT FIND WORD in VOCAB --- {} --> {}".format(word, spell(word)))
            #corrected_tokens.append(spell_checked_word)
            #print("{} not in vocab and COULD NOT BE SPELL CHECKED".format(word))
            #corrected_tokens.append(word)
        else:
          output_word=word

      assert output_word!=None
      #if output_word != word:
        #print("{} --------------------------------> {}".format(word,output_word))
      corrected_tokens.append(output_word)        
    return corrected_tokens
      


  def _run_strip_accents(self, text):
    """Strips accents from a piece of text."""
    text = unicodedata.normalize("NFD", text)
    output = []
    for char in text:
      cat = unicodedata.category(char)
      if cat == "Mn":
        continue
      output.append(char)
    return "".join(output)

  def _run_split_on_punc(self, text):
    """Splits punctuation on a piece of text."""

    chars = list(text)
    i = 0
    start_new_word = True
    output = []
    while i < len(chars):
      char = chars[i]
      if _is_punctuation(char):
        output.append([char])
        start_new_word = True
      else:
        if start_new_word:
          output.append([])
        start_new_word = False
        output[-1].append(char)
      i += 1

    return ["".join(x) for x in output]

  def _tokenize_chinese_chars(self, text):
    """Adds whitespace around any CJK character."""
    output = []
    for char in text:
      cp = ord(char)
      if self._is_chinese_char(cp):
        output.append(" ")
        output.append(char)
        output.append(" ")
      else:
        output.append(char)
    return "".join(output)

  def _is_chinese_char(self, cp):
    """Checks whether CP is the codepoint of a CJK character."""
    # This defines a "chinese character" as anything in the CJK Unicode block:
    #   https://en.wikipedia.org/wiki/CJK_Unified_Ideographs_(Unicode_block)
    #
    # Note that the CJK Unicode block is NOT all Japanese and Korean characters,
    # despite its name. The modern Korean Hangul alphabet is a different block,
    # as is Japanese Hiragana and Katakana. Those alphabets are used to write
    # space-separated words, so they are not treated specially and handled
    # like the all of the other languages.
    if ((cp >= 0x4E00 and cp <= 0x9FFF) or  #
        (cp >= 0x3400 and cp <= 0x4DBF) or  #
        (cp >= 0x20000 and cp <= 0x2A6DF) or  #
        (cp >= 0x2A700 and cp <= 0x2B73F) or  #
        (cp >= 0x2B740 and cp <= 0x2B81F) or  #
        (cp >= 0x2B820 and cp <= 0x2CEAF) or
        (cp >= 0xF900 and cp <= 0xFAFF) or  #
        (cp >= 0x2F800 and cp <= 0x2FA1F)):  #
      return True

    return False

  def _clean_text(self, text):
    """Performs invalid character removal and whitespace cleanup on text."""
    output = []
    for char in text:
      cp = ord(char)
      if cp == 0 or cp == 0xfffd or _is_control(char):
        continue
      if _is_whitespace(char):
        output.append(" ")
      else:
        output.append(char)
    return "".join(output)


class WordpieceTokenizer(object):
  """Runs WordPiece tokenziation."""

  def __init__(self, vocab, unk_token="[UNK]", max_input_chars_per_word=200):
    self.vocab = vocab
    self.unk_token = unk_token
    self.max_input_chars_per_word = max_input_chars_per_word

  def tokenize(self, text):
    """Tokenizes a piece of text into its word pieces.

    This uses a greedy longest-match-first algorithm to perform tokenization
    using the given vocabulary.

    For example:
      input = "unaffable"
      output = ["un", "##aff", "##able"]

    Args:
      text: A single token or whitespace separated tokens. This should have
        already been passed through `BasicTokenizer.

    Returns:
      A list of wordpiece tokens.
    """

    text = convert_to_unicode(text)

    output_tokens = []
    for token in whitespace_tokenize(text):
      chars = list(token)
      if len(chars) > self.max_input_chars_per_word:
        output_tokens.append(self.unk_token)
        continue

      is_bad = False
      start = 0
      sub_tokens = []
      while start < len(chars):
        end = len(chars)
        cur_substr = None
        while start < end:
          substr = "".join(chars[start:end])
          if start > 0:
            substr = "##" + substr
          if substr in self.vocab:
            cur_substr = substr
            break
          end -= 1
        if cur_substr is None:
          is_bad = True
          break
        sub_tokens.append(cur_substr)
        start = end

      if is_bad:
        output_tokens.append(self.unk_token)
      else:
        output_tokens.extend(sub_tokens)
    return output_tokens


def _is_whitespace(char):
  """Checks whether `chars` is a whitespace character."""
  # \t, \n, and \r are technically contorl characters but we treat them
  # as whitespace since they are generally considered as such.
  if char == " " or char == "\t" or char == "\n" or char == "\r":
    return True
  cat = unicodedata.category(char)
  if cat == "Zs":
    return True
  return False


def _is_control(char):
  """Checks whether `chars` is a control character."""
  # These are technically control characters but we count them as whitespace
  # characters.
  if char == "\t" or char == "\n" or char == "\r":
    return False
  cat = unicodedata.category(char)
  if cat.startswith("C"):
    return True
  return False


def _is_punctuation(char):
  """Checks whether `chars` is a punctuation character."""
  cp = ord(char)
  # We treat all non-letter/number ASCII as punctuation.
  # Characters such as "^", "$", and "`" are not in the Unicode
  # Punctuation class but we treat them as punctuation anyways, for
  # consistency.
  if ((cp >= 33 and cp <= 47) or (cp >= 58 and cp <= 64) or
      (cp >= 91 and cp <= 96) or (cp >= 123 and cp <= 126)):
    return True
  cat = unicodedata.category(char)
  if cat.startswith("P"):
    return True
  return False