'''simple docstring'''




import argparse
import json
from typing import List

from ltp import LTP

from transformers.models.bert.tokenization_bert import BertTokenizer

def _lowercase	(      lowerCamelCase__						)					->       int:





							"""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 _lowercase	(      lowerCamelCase__						)					->       int:





							"""simple docstring"""


							for char in word:
														__UpperCAmelCase  :				Any       				=		ord(UpperCAmelCase__						)
														if not _is_chinese_char(UpperCAmelCase__						):
																					return 0
							return 1

def _lowercase	(      lowerCamelCase__						)					->       Optional[Any]:





							"""simple docstring"""


							__UpperCAmelCase  :				Union[str, Any]       				=		set()

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

def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__						)					->       Union[str, Any]:





							"""simple docstring"""


							if not chinese_word_set:
														return bert_tokens
							__UpperCAmelCase  :				Union[str, Any]       				=		max([len(UpperCAmelCase__						) for w in chinese_word_set]						)

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

def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__						)					->       Any:





							"""simple docstring"""


							__UpperCAmelCase  :				Optional[Any]       				=		[]

							for i in range(0							,    len(UpperCAmelCase__						)							,    100						):
														__UpperCAmelCase  :				str       				=		ltp_tokenizer.pipeline(lines[i : i + 100]							,    tasks=["cws"]						).cws
														__UpperCAmelCase  :				int       				=		[get_chinese_word(UpperCAmelCase__						) for r in res]
														ltp_res.extend(UpperCAmelCase__						)
							assert len(UpperCAmelCase__						) == len(UpperCAmelCase__						)

							__UpperCAmelCase  :				Union[str, Any]       				=		[]
							for i in range(0							,    len(UpperCAmelCase__						)							,    100						):
														__UpperCAmelCase  :				List[str]       				=		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__						)

							__UpperCAmelCase  :				Any       				=		[]
							for input_ids, chinese_word in zip(UpperCAmelCase__							,    UpperCAmelCase__						):
														__UpperCAmelCase  :				str       				=		[]
														for id in input_ids:
																					__UpperCAmelCase  :				Optional[int]       				=		bert_tokenizer._convert_id_to_token(UpperCAmelCase__						)
																					input_tokens.append(UpperCAmelCase__						)
														__UpperCAmelCase  :				Any       				=		add_sub_symbol(UpperCAmelCase__							,    UpperCAmelCase__						)
														__UpperCAmelCase  :				List[str]       				=		[]
														# 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] == "##":
																												__UpperCAmelCase  :				int       				=		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 _lowercase	(      lowerCamelCase__						)					->       int:





							"""simple docstring"""


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

							__UpperCAmelCase  :				int       				=		prepare_ref(UpperCAmelCase__							,    UpperCAmelCase__							,    UpperCAmelCase__						)

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


if __name__ == "__main__":
			_a   :	int 							=   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   :	List[str] 							=   parser.parse_args()
			main(args)







'''simple docstring'''




def _lowercase	(      lowerCamelCase__ = 100						)					->       int:





       """simple docstring"""


       __UpperCAmelCase  :				Optional[Any]       				=		(n * (n + 1) // 2) ** 2
       __UpperCAmelCase  :				Any       				=		n * (n + 1) * (2 * n + 1) // 6
       return sum_cubes - sum_squares


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






