Spaces:
Runtime error
Runtime error
File size: 3,839 Bytes
1f30dbc 0def03f 1f30dbc 0def03f 1f30dbc 0def03f 1f30dbc 9ec7b19 ab7449f 9ec7b19 1f30dbc 0def03f 1f30dbc 0def03f 1f30dbc |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 |
import os
import re
import unicodedata
import urllib.request
from typing import Dict
import kenlm
class KenlmModel:
digit_re: re.Pattern = re.compile(r"\d")
unicode_punct: Dict[str, str] = {
"，": ",",
"。": ".",
"、": ",",
"„": '"',
"”": '"',
"“": '"',
"«": '"',
"»": '"',
"１": '"',
"」": '"',
"「": '"',
"《": '"',
"》": '"',
"´": "'",
"∶": ":",
"：": ":",
"？": "?",
"！": "!",
"（": "(",
"）": ")",
"；": ";",
"–": "-",
"—": " - ",
"．": ". ",
"～": "~",
"’": "'",
"…": "...",
"━": "-",
"〈": "<",
"〉": ">",
"【": "[",
"】": "]",
"％": "%",
"►": "-",
}
unicode_punct_re = re.compile(f"[{''.join(unicode_punct.keys())}]")
non_printing_chars_re = re.compile(f"[{''.join(map(chr, list(range(0,32)) + list(range(127,160))))}]")
def __init__(self, language):
download_kenlm_model(language)
try:
self.model = kenlm.Model(f"{language}.arpa.bin")
except OSError:
os.remove(f"{language}.arpa.bin")
if os.path.exists(f"{language}.sp.model"):
os.remove(f"{language}.sp.model")
raise OSError("File was corrupt and should have been removed. Please, retry.")
@classmethod
def from_pretrained(cls, language: str):
return cls(language)
def get_perplexity(self, doc: str, normalize_cc_net: bool = True):
if normalize_cc_net:
doc = self.normalize(doc)
doc_log_score, doc_length = 0, 0
for line in doc.split("\n"):
log_score = self.model.score(line)
length = len(line.split()) + 1
doc_log_score += log_score
doc_length += length
return 10.0 ** (-doc_log_score / doc_length)
def normalize(
self,
line: str,
accent: bool = True,
case: bool = True,
numbers: bool = True,
punct: int = 1,
) -> str:
line = line.strip()
if not line:
return line
if case:
line = line.lower()
if accent:
line = self.strip_accents(line)
if numbers:
line = self.digit_re.sub("0", line)
if punct == 1:
line = self.replace_unicode_punct(line)
elif punct == 2:
line = self.remove_unicode_punct(line)
line = self.remove_non_printing_char(line)
return line
def strip_accents(self, line: str) -> str:
"""Strips accents from a piece of text."""
nfd = unicodedata.normalize("NFD", line)
output = [c for c in nfd if unicodedata.category(c) != "Mn"]
if len(output) == line:
return line
return "".join(output)
def replace_unicode_punct(self, text: str) -> str:
return "".join((self.unicode_punct.get(c, c) for c in text))
def remove_unicode_punct(self, text: str) -> str:
"""More aggressive version of replace_unicode_punct but also faster."""
return self.unicode_punct_re.sub("", text)
def remove_non_printing_char(self, text: str) -> str:
return self.non_printing_chars_re.sub("", text)
def download_kenlm_model(language: str):
root_url = "http://dl.fbaipublicfiles.com/cc_net/lm"
bin_name = f"{language}.arpa.bin"
model_name = f"{language}.sp.model"
bin_url = f"{root_url}/{bin_name}"
model_url = f"{root_url}/{model_name}"
if not os.path.isfile(bin_name):
urllib.request.urlretrieve(bin_url, bin_name)
if not os.path.isfile(model_name):
urllib.request.urlretrieve(model_url, model_name)
|