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H2Retrieval.py

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+import pandas as pd
+import os
+import gzip
+import random
+import re
+from tqdm import tqdm
+def get_all_files_in_directory(directory):
+    all_files = []
+    for root, dirs, files in os.walk(directory):
+        root = root[len(directory):]
+        if root.startswith('\\') or root.startswith('/'):
+            root = root[1:]
+        for file in files:
+            file_path = os.path.join(root, file)
+            all_files.append(file_path)
+    return all_files
+
+class Fileset(list):
+    def __init__(self, path, ext='', _read=None):
+        if isinstance(path, str):
+            self.root = path
+            self.extend(f for f in get_all_files_in_directory(self.root) if f.endswith(ext))
+            self._read = _read
+
+    def __getitem__(self, index):
+        if isinstance(index, int):  # index是索引
+            if self._read:
+                return self._read(os.path.join(self.root, super().__getitem__(index)))
+            else:
+                return os.path.join(self.root, super().__getitem__(index))
+        else:  # index是切片
+            fileset = Fileset(None)
+            fileset.root = self.root
+            fileset._read = self._read
+            fileset.extend(super().__getitem__(index))
+            return fileset
+
+def readOne(filePath):
+    with gzip.open(filePath, 'rt', encoding='utf-8') if filePath.endswith('.gz') else open(filePath, encoding='utf-8') as f:
+        retn = [line.strip() for line in f]
+    return retn
+
+rawcorpus = Fileset(r'D:\datasets\h-corpus\h-ss-corpus','.txt.gz', _read=readOne)
+corpus = []
+queries = []
+qrels = []
+
+reg_4 = re.compile(r'(.)\1{3,}')  # 匹配四个或更多连续相同的字符
+def has_four_or_more_repeated_chars(text):
+    return bool(reg_4.search(text))
+
+def randsqidx(tmp):
+    for i in range(20):  # 尝试20次
+        sqidx = random.randint(10, len(tmp) - 10)
+        if any(len(tmp[i]) < 20 or len(tmp[i]) > 512 or has_four_or_more_repeated_chars(tmp[i]) for i in range(sqidx-2, sqidx+3)):
+            continue
+        return sqidx
+    return -1
+
+def appendqrels(tmp, sqidx, _range, sr):
+    qidx = len(queries)
+    queries.append((qidx, tmp[sqidx]))
+    if corpus:
+        cidx = corpus[-1][0] + 3
+    else:
+        cidx = 2
+    for k in _range:
+        corpus.append((cidx+k, tmp[sqidx+k]))
+        qrels.append((qidx, cidx+k, sr[k+2]))
+
+def split3(s):
+    retn = []
+    cache = ''
+    for one in s:
+        cache += one
+        if len(cache) < 64:
+            continue
+        if one in ('?', '!', '。', '？', '！'):
+            retn.append(cache)
+            cache = ''
+    # print(retn)
+    return retn
+
+def main():
+    for i in tqdm(range(len(rawcorpus)), desc="Converting"):
+        tmp = rawcorpus[i]
+        if len(tmp) < 30:
+            continue
+        if random.randint(0, 3):
+            sqidx = randsqidx(tmp)
+            if sqidx > 2:
+                appendqrels(tmp, sqidx, (-2, -1, 1, 2), (0.95, 0.97, 1, 0.97, 0.95))
+                continue
+        for s in tmp:
+            if len(s) <= 512:
+                continue
+            s = split3(s)
+            if len(s) < 3:
+                continue
+            sqidx = random.randint(1, len(s)-2)
+            appendqrels(s, sqidx, (-1, 1), (0.95, 1, 1, 1, 0.95))
+            break
+
+main()
+
+corpus_pd = pd.DataFrame(corpus, columns=['cid', 'text'])
+queries_pd = pd.DataFrame(queries, columns=['qid', 'text'])
+qrels_pd = pd.DataFrame(qrels, columns=['qid', 'cid', 'score'])
+
+corpus_pd.to_parquet(
+    r"D:\datasets\H2Retrieval\data\corpus.parquet.gz",
+    engine="pyarrow",
+    compression="gzip",
+)
+queries_pd.to_parquet(
+    r"D:\datasets\H2Retrieval\data\queries.parquet.gz",
+    engine="pyarrow",
+    compression="gzip",
+)
+qrels_pd.to_parquet(
+    r"D:\datasets\H2Retrieval\data\qrels.parquet.gz",
+    engine="pyarrow",
+    compression="gzip",
+)

data/corpus.parquet.gz

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2d91eb565e7fb2179f208351550888e70a048129c96ef15b5797a828d18d4ea7
+size 62677530

data/qrels.parquet.gz

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+version https://git-lfs.github.com/spec/v1
+oid sha256:23e25ecd898b92614c846bb744db41789cb9a163f0c413e77cf716ca00092eb9
+size 2247573

data/queries.parquet.gz

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+version https://git-lfs.github.com/spec/v1
+oid sha256:60bdc6f49f2c553f448f23ab67b2f2f69e1cf186cb68f82fdf7f9bd109495646
+size 16975525