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# -*- coding:utf-8 -*-
from __future__ import annotations
import re
import evaluate
import pandas as pd
print(f"loading: {__file__}")
bleu = evaluate.load("bleu")
rouge = evaluate.load("rouge")
bert_score = evaluate.load("bertscore")
# pattern_non_word_char_repetition = re.compile(r"\s{5,}")
# pattern_text_repetitions = re.compile(r"(.{5}.*)\s*((\1)\s*)+", re.M | re.DOTALL)
# final version
pattern_non_word_char_repetition = re.compile(r"[\s\W]{5,}")
pattern_text_repetitions = re.compile(
r"(?P<repeat>.{5}.*?)(?:[\s\W]*(?P=repeat))+", re.M | re.DOTALL | re.IGNORECASE
)
# Explanation of the Regex Pattern:
# (?P<repeat>.{5}.*?): Captures any sequence of characters with minimal length of 5 and names this group repeat.
# .*?: Matches zero or more characters, non-greedily (as few as possible).
# (?:[\s\W]+(?P=repeat))+: A non-capturing group that matches one or more repetitions of:
# [\s\W]+: One or more whitespace or non-word characters (spaces, punctuation, etc.).
# (?P=repeat): A backreference to the named group repeat.
def del_non_word_char_repetition(text, debug=False):
count = 0
if isinstance(text, str):
if debug:
print("----detect non-word characters repetition----")
count = len(text)
text = pattern_non_word_char_repetition.sub("\t", text)
count -= len(text)
if debug and count:
print(f"removed non-word characters repetition: {count}")
return text, count
# final version for repetition detection
def detect_text_repetitions(text, debug=False):
count = 0
if isinstance(text, str):
if debug:
print("----detect text repetitions----")
matches = pattern_text_repetitions.finditer(text)
for match in matches:
if debug:
print(match)
for groupNum in range(0, len(match.groups())):
groupNum = groupNum + 1
print(
"Group {groupNum} found at {start}-{end}: `{group}`".format(
groupNum=groupNum,
start=match.start(groupNum),
end=match.end(groupNum),
group=match.group(groupNum),
)
)
start, end = match.span()
count += end - start - len(match.group(1))
return count
def detect_repetitions(text, debug=False):
if isinstance(text, str) is False:
return 0, 0, 0
text, count_non_word_char_repetition = del_non_word_char_repetition(
text, debug=debug
)
count_text_repetitions = detect_text_repetitions(text, debug=debug)
total_repetitions = count_non_word_char_repetition + count_text_repetitions
result = (count_non_word_char_repetition, count_text_repetitions, total_repetitions)
if debug:
print(result)
return result
def calc_perf_scores(predictions, references, debug=False):
if debug:
print("predictions:", predictions)
print("references:", references)
bleu_scores = bleu.compute(
predictions=predictions, references=references, max_order=1
)
rouge_scores = rouge.compute(predictions=predictions, references=references)
bert_scores = bert_score.compute(
predictions=predictions,
references=references,
lang="en",
model_type="microsoft/deberta-large-mnli",
)
result = {
"bleu_scores": bleu_scores,
"rouge_scores": rouge_scores,
"bert_scores": bert_scores,
}
if debug:
print("result:", result)
return result
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