






import argparse
import json
from typing import List

from ltp import LTP

from transformers import BertTokenizer





def 					lowercase_ (    __snake_case     :							Optional[int]      )     -> Optional[int]:





				'''simple docstring'''


				if (
				    (cp >= 0X4_e00 and cp <= 0X9_fff)
				    or (cp >= 0X3_400 and cp <= 0X4_dbf)  #
				    or (cp >= 0X20_000 and cp <= 0X2a_6df)  #
				    or (cp >= 0X2a_700 and cp <= 0X2b_73f)  #
				    or (cp >= 0X2b_740 and cp <= 0X2b_81f)  #
				    or (cp >= 0X2b_820 and cp <= 0X2c_eaf)  #
				    or (cp >= 0Xf_900 and cp <= 0Xf_aff)
				    or (cp >= 0X2f_800 and cp <= 0X2f_a1f)  #
				):  #
								return True

				return False





def 					lowercase_ (    __snake_case     :							str      )     -> Union[str, Any]:





				'''simple docstring'''


				for char in word:
								snake_case__      :Optional[Any]         =   ord(__snake_case      )
								if not _is_chinese_char(__snake_case      ):
												return 0
				return 1





def 					lowercase_ (    __snake_case     :							List[str]      )     -> Any:





				'''simple docstring'''


				snake_case__      :List[Any]         =   set()

				for token in tokens:
								snake_case__      :Optional[Any]         =   len(__snake_case      ) > 1 and is_chinese(__snake_case      )
								if chinese_word:
												word_set.add(__snake_case      )
				snake_case__      :List[str]         =   list(__snake_case      )
				return word_list





def 					lowercase_ (    __snake_case     :							List[str]	,	__snake_case     :							set()      )     -> Dict:





				'''simple docstring'''


				if not chinese_word_set:
								return bert_tokens
				snake_case__      :Dict         =   max([len(__snake_case      ) for w in chinese_word_set]      )

				snake_case__      :int         =   bert_tokens
				snake_case__    ,						snake_case__      :Optional[Any]         =   0, len(__snake_case      )
				while start < end:
								snake_case__      :int         =   True
								if is_chinese(bert_word[start]      ):
												snake_case__      :Any         =   min(end - start	,	__snake_case      )
												for i in range(__snake_case	,	1	,	-1      ):
																snake_case__      :List[Any]         =   "".join(bert_word[start : start + i]      )
																if whole_word in chinese_word_set:
																				for j in range(start + 1	,	start + i      ):
																								snake_case__      :int         =   "##" + bert_word[j]
																				snake_case__      :Optional[int]         =   start + i
																				snake_case__      :Tuple         =   False
																				break
								if single_word:
												start += 1
				return bert_word





def 					lowercase_ (    __snake_case     :							List[str]	,	__snake_case     :							LTP	,	__snake_case     :							BertTokenizer      )     -> Optional[Any]:





				'''simple docstring'''


				snake_case__      :List[str]         =   []

				for i in range(0	,	len(__snake_case      )	,	1_00      ):
								snake_case__      :Dict         =   ltp_tokenizer.seg(lines[i : i + 1_00]      )[0]
								snake_case__      :Dict         =   [get_chinese_word(__snake_case      ) for r in res]
								ltp_res.extend(__snake_case      )
				assert len(__snake_case      ) == len(__snake_case      )

				snake_case__      :List[Any]         =   []
				for i in range(0	,	len(__snake_case      )	,	1_00      ):
								snake_case__      :List[str]         =   bert_tokenizer(lines[i : i + 1_00]	,	add_special_tokens=__snake_case	,	truncation=__snake_case	,	max_length=5_12      )
								bert_res.extend(res["input_ids"]      )
				assert len(__snake_case      ) == len(__snake_case      )

				snake_case__      :Optional[Any]         =   []
				for input_ids, chinese_word in zip(__snake_case	,	__snake_case      ):
								snake_case__      :str         =   []
								for id in input_ids:
												snake_case__      :List[Any]         =   bert_tokenizer._convert_id_to_token(__snake_case      )
												input_tokens.append(__snake_case      )
								snake_case__      :Union[str, Any]         =   add_sub_symbol(__snake_case	,	__snake_case      )
								snake_case__      :Optional[int]         =   []
								# We only save pos of chinese subwords start with ##, which mean is part of a whole word.
								for i, token in enumerate(__snake_case      ):
												if token[:2] == "##":
																snake_case__      :Dict         =   token[2:]
																# save chinese tokens' pos
																if len(__snake_case      ) == 1 and _is_chinese_char(ord(__snake_case      )      ):
																				ref_id.append(__snake_case      )
								ref_ids.append(__snake_case      )

				assert len(__snake_case      ) == len(__snake_case      )

				return ref_ids





def 					lowercase_ (    __snake_case     :							List[Any]      )     -> List[str]:





				'''simple docstring'''


				with open(args.file_name	,	"r"	,	encoding="utf-8"      ) as f:
								snake_case__      :Dict         =   f.readlines()
				snake_case__      :Dict         =   [line.strip() for line in data if len(__snake_case      ) > 0 and not line.isspace()]  # avoid delimiter like '\u2029'
				snake_case__      :str         =   LTP(args.ltp      )  # faster in GPU device
				snake_case__      :List[str]         =   BertTokenizer.from_pretrained(args.bert      )

				snake_case__      :List[Any]         =   prepare_ref(__snake_case	,	__snake_case	,	__snake_case      )

				with open(args.save_path	,	"w"	,	encoding="utf-8"      ) as f:
								snake_case__      :int         =   [json.dumps(__snake_case      ) + "\n" for ref in ref_ids]
								f.writelines(__snake_case      )


if __name__ == "__main__":
	__UpperCAmelCase							:   Optional[int]							=  argparse.ArgumentParser(description="prepare_chinese_ref")
	parser.add_argument(
	    "--file_name",
	    type=str,
	    default="./resources/chinese-demo.txt",
	    help="file need process, same as training data in lm",
	)
	parser.add_argument(
	    "--ltp", type=str, default="./resources/ltp", help="resources for LTP tokenizer, usually a path"
	)
	parser.add_argument("--bert", type=str, default="./resources/robert", help="resources for Bert tokenizer")
	parser.add_argument("--save_path", type=str, default="./resources/ref.txt", help="path to save res")

	__UpperCAmelCase							:   List[Any]							=  parser.parse_args()
	main(args)







__UpperCAmelCase							:   int							=  {"a": ["c", "b"], "b": ["d", "e"], "c": [], "d": [], "e": []}
__UpperCAmelCase							:   List[str]							=  ["a", "b", "c", "d", "e"]





def 					lowercase_ (    __snake_case     :							Optional[Any]	,	__snake_case     :							List[Any]	,	__snake_case     :							Tuple      )     -> Optional[int]:





				'''simple docstring'''


				snake_case__      :List[Any]         =   start
				# add current to visited
				visited.append(__snake_case      )
				snake_case__      :List[str]         =   edges[current]
				for neighbor in neighbors:
								# if neighbor not in visited, visit
								if neighbor not in visited:
												snake_case__      :Any         =   topological_sort(__snake_case	,	__snake_case	,	__snake_case      )
    # if all neighbors visited add current to sort
				sort.append(__snake_case      )
				# if all vertices haven't been visited select a new one to visit
				if len(__snake_case      ) != len(__snake_case      ):
								for vertice in vertices:
												if vertice not in visited:
																snake_case__      :Any         =   topological_sort(__snake_case	,	__snake_case	,	__snake_case      )
    # return sort
				return sort


if __name__ == "__main__":
	__UpperCAmelCase							:   Tuple							=  topological_sort("a", [], [])
	print(sort)