"""simple docstring"""




import argparse
import json
from typing import List

from ltp import LTP

from transformers import BertTokenizer






def      UpperCAmelCase    (		UpperCamelCase__ ):






							"""simple docstring"""





							if (
							    (cp >= 0x4_e_0_0 and cp <= 0x9_f_f_f)
							    or (cp >= 0x3_4_0_0 and cp <= 0x4_d_b_f)  #
							    or (cp >= 0x2_0_0_0_0 and cp <= 0x2_a_6_d_f)  #
							    or (cp >= 0x2_a_7_0_0 and cp <= 0x2_b_7_3_f)  #
							    or (cp >= 0x2_b_7_4_0 and cp <= 0x2_b_8_1_f)  #
							    or (cp >= 0x2_b_8_2_0 and cp <= 0x2_c_e_a_f)  #
							    or (cp >= 0xf_9_0_0 and cp <= 0xf_a_f_f)
							    or (cp >= 0x2_f_8_0_0 and cp <= 0x2_f_a_1_f)  #
							):  #
														return True

							return False






def      UpperCAmelCase    (		UpperCamelCase__ ):






							"""simple docstring"""





							for char in word:
														A__		   =							ord(_lowerCamelCase )
														if not _is_chinese_char(_lowerCamelCase ):
																					return 0
							return 1






def      UpperCAmelCase    (		UpperCamelCase__ ):






							"""simple docstring"""





							A__		   =							set()

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






def      UpperCAmelCase    (		UpperCamelCase__				,			UpperCamelCase__ ):






							"""simple docstring"""





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

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






def      UpperCAmelCase    (		UpperCamelCase__				,			UpperCamelCase__				,			UpperCamelCase__ ):






							"""simple docstring"""





							A__		   =							[]

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

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

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

							assert len(_lowerCamelCase ) == len(_lowerCamelCase )

							return ref_ids






def      UpperCAmelCase    (		UpperCamelCase__ ):






							"""simple docstring"""





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

							A__		   =							prepare_ref(_lowerCamelCase				,			_lowerCamelCase				,			_lowerCamelCase )

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


if __name__ == "__main__":
				__lowerCamelCase							 =     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")

				__lowerCamelCase							 =     parser.parse_args()
				main(args)










def 				A				(					_lowerCamelCase  ):





							'''simple docstring'''




							if bit_count < 0:
														raise ValueError("The given input must be positive"  )

							# get the generated string sequence
							_lowerCAmelCase     :							List[str]    =    gray_code_sequence_string(_lowerCamelCase  )
							#
							# convert them to integers
							for i in range(len(_lowerCamelCase  )  ):
														_lowerCAmelCase     :							List[str]    =    int(sequence[i]				, 2  )

							return sequence






def 				A				(					_lowerCamelCase  ):





							'''simple docstring'''




							if bit_count == 0:
														return ["0"]

							if bit_count == 1:
														return ["0", "1"]

							_lowerCAmelCase     :							List[Any]    =    1 << bit_count  # defines the length of the sequence
							# 1<< n is equivalent to 2^n

							# recursive answer will generate answer for n-1 bits
							_lowerCAmelCase     :							Optional[int]    =    gray_code_sequence_string(bit_count - 1  )

							_lowerCAmelCase     :							str    =    []

							# append 0 to first half of the smaller sequence generated
							for i in range(seq_len // 2  ):
														_lowerCAmelCase     :							Dict    =    "0" + smaller_sequence[i]
														sequence.append(_lowerCamelCase  )

							# append 1 to second half ... start from the end of the list
							for i in reversed(range(seq_len // 2  )  ):
														_lowerCAmelCase     :							Optional[Any]    =    "1" + smaller_sequence[i]
														sequence.append(_lowerCamelCase  )

							return sequence


if __name__ == "__main__":
						import doctest

						doctest.testmod()
