feat: support english

preprocessing.py

@@ -1,10 +1,11 @@
 
 
+import argparse
+import os
 import sys
-from read_data import TagIdConverter, make_long_namedEntity, readKoreanDataAll, Sentence
-from typing import Any, NamedTuple, List, Sequence, TypeVar
+from read_data import TagIdConverter, make_long_namedEntity, readEnglishDataAll, readKoreanDataAll, Sentence
+from typing import Any, List
 import json
-import os.path as path
 import tqdm
 from transformers import PreTrainedTokenizer
 
@@ -35,27 +36,44 @@ def readPreprocessedData(path: str):
     with open(path,"r", encoding="utf-8") as fp:
         return json.load(fp)
 
-def readPreporcssedDataAll():
-    train = readPreprocessedData(path.join(PRE_BASE_PATH,"train.json"))
-    dev = readPreprocessedData(path.join(PRE_BASE_PATH,"dev.json"))
-    test = readPreprocessedData(path.join(PRE_BASE_PATH,"test.json"))
+def readPreporcssedDataAll(path = PRE_BASE_PATH):
+    train = readPreprocessedData(os.path.join(path,"train.json"))
+    dev = readPreprocessedData(os.path.join(path,"dev.json"))
+    test = readPreprocessedData(os.path.join(path,"test.json"))
     return train, dev, test
 
 if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--kind", default="korean")
+    parser.add_argument("path",default=PRE_BASE_PATH,help="directory path of processed data")
+    parser.add_argument("--tag", default="tags.json",help="path of tag description")
+
+    args = parser.parse_args()
+    dirPath = args.path
+    
+    if args.kind == "korean":
+        rawTrain, rawDev, rawTest = readKoreanDataAll()
+    elif args.kind == "english":
+        rawTrain, rawDev, rawTest = readEnglishDataAll()
+    else:
+        print("unknown language",file=sys.stderr)
+        exit(1)
+
+    converter = TagIdConverter(args.tag)
+    os.makedirs(dirPath)
+
     from transformers import BertTokenizer
     PRETAINED_MODEL_NAME = 'bert-base-multilingual-cased'
 
-    rawTrain, rawDev, rawTest = readKoreanDataAll()
     print("load tokenzier...",file=sys.stderr)
     tokenizer = BertTokenizer.from_pretrained(PRETAINED_MODEL_NAME)
-    converter = TagIdConverter()
 
     print("process train...",file=sys.stderr)
     train = preprocessing(tokenizer,converter,rawTrain)
-    saveObject(path.join(PRE_BASE_PATH,"train.json"),train)
+    saveObject(path.join(dirPath,"train.json"),train)
     print("process dev...",file=sys.stderr)
     dev = preprocessing(tokenizer,converter,rawDev)
-    saveObject(path.join(PRE_BASE_PATH,"dev.json"),dev)
+    saveObject(path.join(dirPath,"dev.json"),dev)
     print("process test...",file=sys.stderr)
     test = preprocessing(tokenizer,converter,rawTest)
-    saveObject(path.join(PRE_BASE_PATH,"test.json"),test)
+    saveObject(path.join(dirPath,"test.json"),test)