switching to moses tokenizer

transformers/tokenization_ctrl.py

@@ -22,8 +22,9 @@ import os
 import regex as re
 from io import open
 
-from .tokenization_bert import BasicTokenizer
+import sacremoses as sm
 
+from .tokenization_xlm import replace_unicode_punct, remove_non_printing_char
 from .tokenization_utils import PreTrainedTokenizer
 
 logger = logging.getLogger(__name__)
@@ -48,39 +49,11 @@ PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES = {
     'ctrl': 256,
 }
 
-def text_standardize(text):
-    """
-    fixes some issues the spacy tokenizer had on books corpus
-    also does some whitespace standardization
-    """
-    text = text.replace('—', '-')
-    text = text.replace('–', '-')
-    text = text.replace('―', '-')
-    text = text.replace('…', '...')
-    text = text.replace('´', "'")
-    text = re.sub(r'''(-+|~+|!+|"+|;+|\?+|\++|,+|\)+|\(+|\\+|\/+|\*+|\[+|\]+|}+|{+|\|+|_+)''', r' \1 ', text)
-    text = re.sub(r'\s*\n\s*', ' \n ', text)
-    text = re.sub(r'[^\S\n]+', ' ', text)
-    return text.strip()
-
-
 def get_pairs(word):
     """Return set of symbol pairs in a word.
 
     Word is represented as tuple of symbols (symbols being variable-length strings).
     """
-    # pairs = []
-    # prev_char = word[0]
-    # for i, char in enumerate(word[1:]):
-    #     #_i = i + 1
-    #     #if word[_i+1:] == tuple('</w>'):
-    #     #    pairs.append((prev_char, char+'</w>'))
-    #     #    break
-    #     #else:
-    #     if True:
-    #         pairs.append((prev_char, char))
-    #         prev_char = char
-
     pairs = set()
     prev_char = word[0]
     for char in word[1:]:
@@ -108,6 +81,9 @@ class CTRLTokenizer(PreTrainedTokenizer):
         self.max_len_single_sentence = self.max_len # no default special tokens - you can update this value if you add special tokens
         self.max_len_sentences_pair = self.max_len # no default special tokens - you can update this value if you add special tokens
 
+        self.punct_normalizer = sm.MosesPunctNormalizer(lang='en')
+        self.moses_tokenizer = sm.MosesTokenizer(lang='en')
+
         self.encoder = json.load(open(vocab_file, encoding="utf-8"))
         self.decoder = {v:k for k,v in self.encoder.items()}
         merges = open(merges_file, encoding='utf-8').read().split('\n')[1:-1]
@@ -162,11 +138,23 @@ class CTRLTokenizer(PreTrainedTokenizer):
         self.cache[token] = word
         return word
 
-    def _tokenize(self, text):
+    def moses_pipeline(self, text):
+        text = replace_unicode_punct(text)
+        text = self.punct_normalizer.normalize(text)
+        text = remove_non_printing_char(text)
+        return text
+
+    def _tokenize(self, text, bypass_tokenizer=False):
         """ Tokenize a string.
         """
         split_tokens = []
-        text = text.split(' ')
+
+        if bypass_tokenizer:
+            text = text.split()
+        else:
+            text = self.moses_pipeline(text)
+            text = self.moses_tokenizer.tokenize(text, return_str=False, escape=False)
+
         for token in text:
             split_tokens.extend([t for t in self.bpe(token).split(' ')])
         return split_tokens