




import argparse
import json
from typing import List

from ltp import LTP

from transformers import BertTokenizer


def 							__SCREAMING_SNAKE_CASE  (			snake_case_						):

						'''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 							__SCREAMING_SNAKE_CASE  (			snake_case_						):

						'''simple docstring'''


						for char in word:
												_UpperCAmelCase													=     ord(snake_case_						)
												if not _is_chinese_char(snake_case_						):
																		return 0
						return 1


def 							__SCREAMING_SNAKE_CASE  (			snake_case_						):

						'''simple docstring'''


						_UpperCAmelCase													=     set()

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


def 							__SCREAMING_SNAKE_CASE  (			snake_case_	,    snake_case_						):

						'''simple docstring'''


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

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


def 							__SCREAMING_SNAKE_CASE  (			snake_case_	,    snake_case_	,    snake_case_						):

						'''simple docstring'''


						_UpperCAmelCase													=     []

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

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

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

						assert len(snake_case_						) == len(snake_case_						)

						return ref_ids


def 							__SCREAMING_SNAKE_CASE  (			snake_case_						):

						'''simple docstring'''


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

						_UpperCAmelCase													=     prepare_ref(snake_case_	,    snake_case_	,    snake_case_						)

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


if __name__ == "__main__":
				lowercase_	:				List[Any]  				= 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')

				lowercase_	:				List[str]  				= parser.parse_args()
				main(args)











def _a				(	lowerCamelCase:   int = 2_00 )	->						int:







      '''simple docstring'''






      __A          =				[1, 2, 5, 10, 20, 50, 1_00, 2_00]
      __A          =				[0] * (pence + 1)
      __A          =				1  # base case: 1 way to make 0 pence

      for coin in coins:
            for i in range(lowerCamelCase					,				pence + 1					,				1 ):
                  number_of_ways[i] += number_of_ways[i - coin]
      return number_of_ways[pence]


if __name__ == "__main__":
       assert solution(200) == 73682





