




import argparse
import json
from typing import List

from ltp import LTP

from transformers import BertTokenizer







def 			lowerCamelCase_		(       UpperCamelCase__				:      Tuple      )     ->       Tuple:





				"""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 			lowerCamelCase_		(       UpperCamelCase__				:      str      )     ->       List[str]:





				"""simple docstring"""


				for char in word:
								__lowerCamelCase		       =    ord(UpperCamelCase__      )
								if not _is_chinese_char(UpperCamelCase__      ):
												return 0
				return 1







def 			lowerCamelCase_		(       UpperCamelCase__				:      List[str]      )     ->       List[Any]:





				"""simple docstring"""


				__lowerCamelCase		       =    set()

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







def 			lowerCamelCase_		(       UpperCamelCase__				:      List[str] ,     UpperCamelCase__				:      set()      )     ->       Tuple:





				"""simple docstring"""


				if not chinese_word_set:
								return bert_tokens
				__lowerCamelCase		       =    max([len(UpperCamelCase__      ) for w in chinese_word_set]      )

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







def 			lowerCamelCase_		(       UpperCamelCase__				:      List[str] ,     UpperCamelCase__				:      LTP ,     UpperCamelCase__				:      BertTokenizer      )     ->       Optional[int]:





				"""simple docstring"""


				__lowerCamelCase		       =    []

				for i in range(0 ,     len(UpperCamelCase__      ) ,     100      ):
								__lowerCamelCase		       =    ltp_tokenizer.seg(lines[i : i + 100]      )[0]
								__lowerCamelCase		       =    [get_chinese_word(UpperCamelCase__      ) for r in res]
								ltp_res.extend(UpperCamelCase__      )
				assert len(UpperCamelCase__      ) == len(UpperCamelCase__      )

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

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

				assert len(UpperCamelCase__      ) == len(UpperCamelCase__      )

				return ref_ids







def 			lowerCamelCase_		(       UpperCamelCase__				:      str      )     ->       Optional[int]:





				"""simple docstring"""


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

				__lowerCamelCase		       =    prepare_ref(UpperCamelCase__ ,     UpperCamelCase__ ,     UpperCamelCase__      )

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


if __name__ == "__main__":
					__A        =    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")

					__A        =    parser.parse_args()
					main(args)








from __future__ import annotations

# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
__A        =    10







def 			lowerCamelCase_		(       UpperCamelCase__				:      int ,     UpperCamelCase__				:      int ,     UpperCamelCase__				:      list[int] ,     UpperCamelCase__				:      int      )     ->       int:





				"""simple docstring"""


				for i in range(UpperCamelCase__ ,     UpperCamelCase__      ):
								if array[i] == target:
												return i
				return -1







def 			lowerCamelCase_		(       UpperCamelCase__				:      list[int] ,     UpperCamelCase__				:      int      )     ->       int:





				"""simple docstring"""


				__lowerCamelCase		       =    0
				__lowerCamelCase		       =    len(UpperCamelCase__      )
				while left <= right:
								if right - left < precision:
												return lin_search(UpperCamelCase__ ,     UpperCamelCase__ ,     UpperCamelCase__ ,     UpperCamelCase__      )

								__lowerCamelCase		       =    (left + right) // 3 + 1
								__lowerCamelCase		       =    2 * (left + right) // 3 + 1

								if array[one_third] == target:
												return one_third
								elif array[two_third] == target:
												return two_third

								elif target < array[one_third]:
												__lowerCamelCase		       =    one_third - 1
								elif array[two_third] < target:
												__lowerCamelCase		       =    two_third + 1

								else:
												__lowerCamelCase		       =    one_third + 1
												__lowerCamelCase		       =    two_third - 1
				else:
								return -1







def 			lowerCamelCase_		(       UpperCamelCase__				:      int ,     UpperCamelCase__				:      int ,     UpperCamelCase__				:      list[int] ,     UpperCamelCase__				:      int      )     ->       int:





				"""simple docstring"""


				if left < right:
								if right - left < precision:
												return lin_search(UpperCamelCase__ ,     UpperCamelCase__ ,     UpperCamelCase__ ,     UpperCamelCase__      )
								__lowerCamelCase		       =    (left + right) // 3 + 1
								__lowerCamelCase		       =    2 * (left + right) // 3 + 1

								if array[one_third] == target:
												return one_third
								elif array[two_third] == target:
												return two_third

								elif target < array[one_third]:
												return rec_ternary_search(UpperCamelCase__ ,     one_third - 1 ,     UpperCamelCase__ ,     UpperCamelCase__      )
								elif array[two_third] < target:
												return rec_ternary_search(two_third + 1 ,     UpperCamelCase__ ,     UpperCamelCase__ ,     UpperCamelCase__      )
								else:
												return rec_ternary_search(one_third + 1 ,     two_third - 1 ,     UpperCamelCase__ ,     UpperCamelCase__      )
				else:
								return -1


if __name__ == "__main__":
					import doctest

					doctest.testmod()

					__A        =    input("Enter numbers separated by comma:\n").strip()
					__A        =    [int(item.strip()) for item in user_input.split(",")]
					assert collection == sorted(collection), f"List must be ordered.\n{collection}."
					__A        =    int(input("Enter the number to be found in the list:\n").strip())
					__A        =    ite_ternary_search(collection, target)
					__A        =    rec_ternary_search(0, len(collection) - 1, collection, target)
					if resulta != -1:
										print(f'''Iterative search: {target} found at positions: {resulta}''')
										print(f'''Recursive search: {target} found at positions: {resulta}''')
					else:
										print("Not found")


