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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 | |