Upload finetune_data.py with huggingface_hub

finetune_data.py

@@ -0,0 +1,130 @@
+# coding=utf-8
+
+import argparse
+import json
+import random
+from ltp import LTP
+from tqdm import tqdm
+
+def parse_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--input", type=str, required=True)
+    parser.add_argument("--output", type=str, required=True)
+    parser.add_argument("--ltp_model", type=str, required=True)
+    parser.add_argument("--basic_hanzi", type=str, default="confusion/basic_hanzi_2500.txt")
+    parser.add_argument("--sound_confusion", type=str, default="confusion/sound_confusion.txt")
+    parser.add_argument("--shape_confusion", type=str, default="confusion/shape_confusion.txt")
+    parser.add_argument("--same_ratio", type=float, default=0.1)
+    parser.add_argument("--repeat_ratio", type=float, default=0.2)
+    parser.add_argument("--delete_ratio", type=float, default=0.2)
+    parser.add_argument("--sound_ratio", type=float, default=0.4)
+    parser.add_argument("--shape_ratio", type=float, default=0.1)
+    parser.add_argument("--whitelist", type=str, default="一二三四五六七八九十")
+    parser.add_argument("--seed", type=int, default=42)
+    args = parser.parse_args()
+    return args
+
+def isChinese(word):
+    for ch in word:
+        cp = ord(ch)
+        if cp >= 0x4E00 and cp <= 0x9FA5:
+            continue
+        return False
+    return True
+
+def load_hanzi(path):
+    hanzi = set()
+    with open(path, mode="r", encoding="utf-8") as handle:
+        for line in handle:
+            line = line.strip()
+            assert len(line) == 1
+            hanzi.update(line)
+    return hanzi
+
+def load_confusion_set(path, hanzi):
+    confusion_set = {}
+    with open(path, mode="r", encoding="utf-8") as handle:
+        for line in handle:
+            line = line.strip().split()
+            if len(line) < 2:   continue
+            key, val = line[0], []
+            for c in line[1]:
+                if c in hanzi and c not in val and c != key:
+                    val.append(c)
+            if val:
+                confusion_set[key] = val
+    return confusion_set
+
+def do_mask(sent, args):
+    # 分词和词性标注
+    cws, pos = args.ltp.pipeline(sent, tasks=["cws", "pos"], return_dict=False)
+    
+    n = len(cws)
+    i = random.choice(range(n))
+    word = cws[i]
+    if not isChinese(word):
+        i = random.choice(range(n))
+        word = cws[i]
+    if not isChinese(word):
+        return sent
+
+    p = random.random()
+    p1 = args.same_ratio
+    p2 = p1 + args.repeat_ratio
+    p3 = p2 + args.delete_ratio
+    p4 = p3 + args.sound_ratio
+    p5 = p4 + args.shape_ratio
+    assert abs(p5 - 1) < 0.001
+    if p < p1:
+        return sent
+    if p < p2:
+        # 字词冗余
+        cws[i] += word
+        return ''.join(cws)
+    if pos[i] in ['nh', 'ns']:
+        # 不修改人名地名
+        return sent
+    chars = list(word)
+    k = random.choice(range(len(word)))
+    c = chars[k]
+    if c in args.whitelist:
+        return sent
+    if p < p3:
+        if len(word) < 2:
+            return sent
+        chars[k] = ''
+        cws[i] = ''.join(chars)
+        return ''.join(cws)
+    if p < p4:
+        if c in args.sound_set:
+            chars[k] = random.choice(args.sound_set[c])
+    else:
+        if c in args.shape_set:
+            chars[k] = random.choice(args.shape_set[c])
+    cws[i] = ''.join(chars)
+    return ''.join(cws)
+
+if __name__ == "__main__":
+    args = parse_args()
+    random.seed(args.seed)
+    # 常用汉字集合
+    hanzi = load_hanzi(args.basic_hanzi)
+
+    # 混淆集
+    args.sound_set = load_confusion_set(args.sound_confusion, hanzi)
+    args.shape_set = load_confusion_set(args.shape_confusion, hanzi)
+    args.hanzi = list(hanzi)
+
+    # ltp中文分词模型
+    args.ltp = LTP(args.ltp_model)
+
+    output = open(args.output, mode="w")
+    with open(args.input, mode="r", encoding="utf-8") as handle:
+        for line in tqdm(handle):
+            sent = line.strip()
+            if len(sent) < 4:
+                continue
+            source = do_mask(sent, args)
+            output.write(json.dumps({"source": source, "target": sent}, ensure_ascii=False))
+            output.write("\n")
+