
import argparse
import json
from typing import List

from ltp import LTP

from transformers.models.bert.tokenization_bert import BertTokenizer




def 	UpperCamelCase__  (     SCREAMING_SNAKE_CASE_	:	List[str]       )  ->     Dict:
						# This defines a "chinese character" as anything in the CJK Unicode block:
						#   https://en.wikipedia.org/wiki/CJK_Unified_Ideographs_(Unicode_block)
						#
						# Note that the CJK Unicode block is NOT all Japanese and Korean characters,
						# despite its name. The modern Korean Hangul alphabet is a different block,
						# as is Japanese Hiragana and Katakana. Those alphabets are used to write
						# space-separated words, so they are not treated specially and handled
						# like the all of the other languages.
						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 	UpperCamelCase__  (     SCREAMING_SNAKE_CASE_	:	str       )  ->     Optional[Any]:
						# word like '180' or '身高' or '神'
						for char in word:
												_lowercase					       =					ord(SCREAMING_SNAKE_CASE_       )
												if not _is_chinese_char(SCREAMING_SNAKE_CASE_       ):
																		return 0
						return 1




def 	UpperCamelCase__  (     SCREAMING_SNAKE_CASE_	:	List[str]       )  ->     int:
						_lowercase					       =					set()

						for token in tokens:
												_lowercase					       =					len(SCREAMING_SNAKE_CASE_       ) > 1 and is_chinese(SCREAMING_SNAKE_CASE_       )
												if chinese_word:
																		word_set.add(SCREAMING_SNAKE_CASE_       )
						_lowercase					       =					list(SCREAMING_SNAKE_CASE_       )
						return word_list




def 	UpperCamelCase__  (     SCREAMING_SNAKE_CASE_	:	List[str]		,   SCREAMING_SNAKE_CASE_	:	set()       )  ->     Optional[int]:
						if not chinese_word_set:
												return bert_tokens
						_lowercase					       =					max([len(SCREAMING_SNAKE_CASE_       ) for w in chinese_word_set]       )

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




def 	UpperCamelCase__  (     SCREAMING_SNAKE_CASE_	:	List[str]		,   SCREAMING_SNAKE_CASE_	:	LTP		,   SCREAMING_SNAKE_CASE_	:	BertTokenizer       )  ->     Dict:
						_lowercase					       =					[]

						for i in range(0		,   len(SCREAMING_SNAKE_CASE_       )		,   1_00       ):
												_lowercase					       =					ltp_tokenizer.pipeline(lines[i : i + 1_00]		,   tasks=["""cws"""]       ).cws
												_lowercase					       =					[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					       =					[]
						for i in range(0		,   len(SCREAMING_SNAKE_CASE_       )		,   1_00       ):
												_lowercase					       =					bert_tokenizer(lines[i : i + 1_00]		,   add_special_tokens=SCREAMING_SNAKE_CASE_		,   truncation=SCREAMING_SNAKE_CASE_		,   max_length=5_12       )
												bert_res.extend(res["""input_ids"""]       )
						assert len(SCREAMING_SNAKE_CASE_       ) == len(SCREAMING_SNAKE_CASE_       )

						_lowercase					       =					[]
						for input_ids, chinese_word in zip(SCREAMING_SNAKE_CASE_		,   SCREAMING_SNAKE_CASE_       ):
												_lowercase					       =					[]
												for id in input_ids:
																		_lowercase					       =					bert_tokenizer._convert_id_to_token(SCREAMING_SNAKE_CASE_       )
																		input_tokens.append(SCREAMING_SNAKE_CASE_       )
												_lowercase					       =					add_sub_symbol(SCREAMING_SNAKE_CASE_		,   SCREAMING_SNAKE_CASE_       )
												_lowercase					       =					[]
												# 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					       =					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 	UpperCamelCase__  (     SCREAMING_SNAKE_CASE_	:	Optional[int]       )  ->     List[str]:
						# For Chinese (Ro)Bert, the best result is from : RoBERTa-wwm-ext (https://github.com/ymcui/Chinese-BERT-wwm)
						# If we want to fine-tune these model, we have to use same tokenizer : LTP (https://github.com/HIT-SCIR/ltp)
						with open(args.file_name		,   """r"""		,   encoding="""utf-8"""       ) as f:
												_lowercase					       =					f.readlines()
						_lowercase					       =					[line.strip() for line in data if len(SCREAMING_SNAKE_CASE_       ) > 0 and not line.isspace()]  # avoid delimiter like '\u2029'
						_lowercase					       =					LTP(args.ltp       )  # faster in GPU device
						_lowercase					       =					BertTokenizer.from_pretrained(args.bert       )

						_lowercase					       =					prepare_ref(SCREAMING_SNAKE_CASE_		,   SCREAMING_SNAKE_CASE_		,   SCREAMING_SNAKE_CASE_       )

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


if __name__ == "__main__":
		A		: Union[str, Any]								=     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''',
		)

		A		: Any								=     parser.parse_args()
		main(args)

def 	UpperCamelCase__  (     SCREAMING_SNAKE_CASE_	:	int = 2_00_00_00       )  ->     int:
						_lowercase					       =					[0 for i in range(n + 1       )]
						_lowercase					       =					1
						_lowercase					       =					1

						for i in range(2		,   int(n**0.5       ) + 1       ):
												if primality_list[i] == 0:
																		for j in range(i * i		,   n + 1		,   SCREAMING_SNAKE_CASE_       ):
																								_lowercase					       =					1
						_lowercase					       =					0
						for i in range(SCREAMING_SNAKE_CASE_       ):
												if primality_list[i] == 0:
																		sum_of_primes += i
						return sum_of_primes


if __name__ == "__main__":
		print(F'{solution() = }')