
'''simple docstring'''







import argparse
import json
from typing import List

from ltp import LTP

from transformers.models.bert.tokenization_bert import BertTokenizer
def  snake_case_		(    __SCREAMING_SNAKE_CASE :			Any							):



						"""simple docstring"""





						if (
						    (cp >= 0x4E00 and cp <= 0x9FFF)
						    or (cp >= 0x3400 and cp <= 0x4DBF)  #
						    or (cp >= 0x20000 and cp <= 0x2A6DF)  #
						    or (cp >= 0x2A700 and cp <= 0x2B73F)  #
						    or (cp >= 0x2B740 and cp <= 0x2B81F)  #
						    or (cp >= 0x2B820 and cp <= 0x2CEAF)  #
						    or (cp >= 0xF900 and cp <= 0xFAFF)
						    or (cp >= 0x2F800 and cp <= 0x2FA1F)  #
						):  #
												return True

						return False
def  snake_case_		(    __SCREAMING_SNAKE_CASE :			str							):



						"""simple docstring"""





						for char in word:
												lowercase_     :					Dict													=	ord(__SCREAMING_SNAKE_CASE							)
												if not _is_chinese_char(__SCREAMING_SNAKE_CASE							):
																		return 0
						return 1
def  snake_case_		(    __SCREAMING_SNAKE_CASE :			List[str]							):



						"""simple docstring"""





						lowercase_     :					str													=	set()

						for token in tokens:
												lowercase_     :					List[Any]													=	len(__SCREAMING_SNAKE_CASE							) > 1 and is_chinese(__SCREAMING_SNAKE_CASE							)
												if chinese_word:
																		word_set.add(__SCREAMING_SNAKE_CASE							)
						lowercase_     :					Optional[Any]													=	list(__SCREAMING_SNAKE_CASE							)
						return word_list
def  snake_case_		(    __SCREAMING_SNAKE_CASE :			List[str]				,				__SCREAMING_SNAKE_CASE :			set()							):



						"""simple docstring"""





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

						lowercase_     :					int													=	bert_tokens
						lowercase_						,			lowercase_     :					Tuple													=	0, len(__SCREAMING_SNAKE_CASE							)
						while start < end:
												lowercase_     :					Dict													=	True
												if is_chinese(bert_word[start]							):
																		lowercase_     :					str													=	min(end - start				,				__SCREAMING_SNAKE_CASE							)
																		for i in range(__SCREAMING_SNAKE_CASE				,				1				,				-1							):
																								lowercase_     :					Any													=	''''''.join(bert_word[start : start + i]							)
																								if whole_word in chinese_word_set:
																														for j in range(start + 1				,				start + i							):
																																				lowercase_     :					Tuple													=	'''##''' + bert_word[j]
																														lowercase_     :					List[Any]													=	start + i
																														lowercase_     :					Optional[int]													=	False
																														break
												if single_word:
																		start += 1
						return bert_word
def  snake_case_		(    __SCREAMING_SNAKE_CASE :			List[str]				,				__SCREAMING_SNAKE_CASE :			LTP				,				__SCREAMING_SNAKE_CASE :			BertTokenizer							):



						"""simple docstring"""





						lowercase_     :					Union[str, Any]													=	[]

						for i in range(0				,				len(__SCREAMING_SNAKE_CASE							)				,				100							):
												lowercase_     :					Union[str, Any]													=	ltp_tokenizer.pipeline(lines[i : i + 100]				,				tasks=['''cws''']							).cws
												lowercase_     :					Dict													=	[get_chinese_word(__SCREAMING_SNAKE_CASE							) for r in res]
												ltp_res.extend(__SCREAMING_SNAKE_CASE							)
						assert len(__SCREAMING_SNAKE_CASE							) == len(__SCREAMING_SNAKE_CASE							)

						lowercase_     :					str													=	[]
						for i in range(0				,				len(__SCREAMING_SNAKE_CASE							)				,				100							):
												lowercase_     :					Any													=	bert_tokenizer(lines[i : i + 100]				,				add_special_tokens=__SCREAMING_SNAKE_CASE				,				truncation=__SCREAMING_SNAKE_CASE				,				max_length=512							)
												bert_res.extend(res['''input_ids''']							)
						assert len(__SCREAMING_SNAKE_CASE							) == len(__SCREAMING_SNAKE_CASE							)

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

						assert len(__SCREAMING_SNAKE_CASE							) == len(__SCREAMING_SNAKE_CASE							)

						return ref_ids
def  snake_case_		(    __SCREAMING_SNAKE_CASE :			Optional[Any]							):



						"""simple docstring"""





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

						lowercase_     :					Optional[Any]													=	prepare_ref(__SCREAMING_SNAKE_CASE				,				__SCREAMING_SNAKE_CASE				,				__SCREAMING_SNAKE_CASE							)

						with open(args.save_path				,				'''w'''				,				encoding='''utf-8'''							) as f:
												lowercase_     :					List[Any]													=	[json.dumps(__SCREAMING_SNAKE_CASE							) + '''\n''' for ref in ref_ids]
												f.writelines(__SCREAMING_SNAKE_CASE							)


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

							_lowercase			:  Tuple   							=	parser.parse_args()
							main(args)





'''simple docstring'''







from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def  snake_case_		(    __SCREAMING_SNAKE_CASE :			int							):



						"""simple docstring"""





						lowercase_     :					Tuple													=	prime_factors(__SCREAMING_SNAKE_CASE							)
						if is_square_free(__SCREAMING_SNAKE_CASE							):
												return -1 if len(__SCREAMING_SNAKE_CASE							) % 2 else 1
						return 0


if __name__ == "__main__":
							import doctest

							doctest.testmod()



