gpt2-persian / normalizer.py
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import hazm
import re
from regexes.currency import CURRENCY_REGEX
from regexes.email import EMAIL_REGEX
from regexes.latin import LATIN_REGEX
from regexes.number import NUMBERS_REGEX
from regexes.phone import PHONE_REGEX
from regexes.quote import DOUBLE_QUOTE_REGEX, SINGLE_QUOTE_REGEX
from regexes.url import URL_REGEX
from regexes.persian import PERSIAN_REGEX
import dictionary
def make_trans(list_a, list_b):
return dict((ord(a), b) for a, b in zip(list_a, list_b))
def multiple_replace(text, chars_to_mapping):
pattern = "|".join(map(re.escape, chars_to_mapping.keys()))
return re.sub(pattern, lambda m: chars_to_mapping[m.group()], str(text))
ar2fa_digits = make_trans("٠١٢٣٤٥٦٧٨٩٪", "۰۱۲۳۴۵۶۷۸۹٪")
fa2en_digits = make_trans("۰۱۲۳۴۵۶۷۸۹٪", "0123456789%")
normalizer = hazm.Normalizer(persian_numbers=True, punctuation_spacing=False)
def normalize(text, zwnj="\u200c", tokenized=False):
text = text.replace("\n", " ").replace("\t", " ")
text = re.sub(r"\u200c+", "\u200c", text)
text = text.replace('ـ', '')
text = normalizer.normalize(text)
if len(dictionary.characters) > 0:
text = multiple_replace(text, dictionary.characters)
if len(dictionary.words_map) > 0:
text = multiple_replace(text, dictionary.words_map)
text = text.translate(ar2fa_digits)
text = text.translate(fa2en_digits)
text = SINGLE_QUOTE_REGEX.sub("'", text)
text = DOUBLE_QUOTE_REGEX.sub('"', text)
text = CURRENCY_REGEX.sub(r" \1 ", text)
text = URL_REGEX.sub(" ", text)
text = EMAIL_REGEX.sub(" ", text)
text = PHONE_REGEX.sub(r" \1 ", text)
text = NUMBERS_REGEX.sub(r" \1 ", text)
text = LATIN_REGEX.sub(r" \1 ", text)
# Allow only english and persian characters
text = re.sub(PERSIAN_REGEX, " ", text)
text = text.replace(f" {zwnj} ", f"{zwnj}")
text = text.replace(f"{zwnj} ", f"{zwnj}")
text = text.replace(f" {zwnj}", f"{zwnj}")
if len(dictionary.special_tokens) > 0:
text = multiple_replace(text, dictionary.special_tokens)
tokens = []
for token in text.split():
token = token.strip()
if token:
if token.startswith(zwnj) and token.endswith(zwnj):
token = token[1:-1]
if token.startswith(zwnj):
token = token[1:]
elif token.endswith(zwnj):
token = token[:-1]
else:
token = token
tokens.append(token)
if tokenized:
return tokens
return " ".join(tokens)