


'''simple docstring'''



import argparse
import json
from typing import List

from ltp import LTP

from transformers.models.bert.tokenization_bert import BertTokenizer


def    lowerCamelCase__   ( A     :    Optional[int]  ):




						'''simple docstring'''






						if (
						    (cp >= 0x4e00 and cp <= 0x9fff)
						    or (cp >= 0x3400 and cp <= 0x4dbf)  #
						    or (cp >= 0x2_0000 and cp <= 0x2_a6df)  #
						    or (cp >= 0x2_a700 and cp <= 0x2_b73f)  #
						    or (cp >= 0x2_b740 and cp <= 0x2_b81f)  #
						    or (cp >= 0x2_b820 and cp <= 0x2_ceaf)  #
						    or (cp >= 0xf900 and cp <= 0xfaff)
						    or (cp >= 0x2_f800 and cp <= 0x2_fa1f)  #
						):  #
												return True

						return False


def    lowerCamelCase__   ( A     :    int  ):




						'''simple docstring'''






						for char in word:
												UpperCAmelCase         =			ord(lowerCAmelCase_  )
												if not _is_chinese_char(lowerCAmelCase_  ):
																		return 0
						return 1


def    lowerCamelCase__   ( A     :    Any  ):




						'''simple docstring'''






						UpperCAmelCase         =			set()

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


def    lowerCamelCase__   ( A     :    List[str]   ,     A     :    Any  ):




						'''simple docstring'''






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

						UpperCAmelCase         =			bert_tokens
						UpperCAmelCase         =			0, len(lowerCAmelCase_  )
						while start < end:
												UpperCAmelCase         =			True
												if is_chinese(bert_word[start]  ):
																		UpperCAmelCase         =			min(end - start   ,     lowerCAmelCase_  )
																		for i in range(lowerCAmelCase_   ,     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    lowerCamelCase__   ( A     :    str   ,     A     :    int   ,     A     :    Dict  ):




						'''simple docstring'''






						UpperCAmelCase         =			[]

						for i in range(0   ,     len(lowerCAmelCase_  )   ,     1_00  ):
												UpperCAmelCase         =			ltp_tokenizer.pipeline(lines[i : i + 1_00]   ,     tasks=['''cws''']  ).cws
												UpperCAmelCase         =			[get_chinese_word(lowerCAmelCase_  ) for r in res]
												ltp_res.extend(lowerCAmelCase_  )
						assert len(lowerCAmelCase_  ) == len(lowerCAmelCase_  )

						UpperCAmelCase         =			[]
						for i in range(0   ,     len(lowerCAmelCase_  )   ,     1_00  ):
												UpperCAmelCase         =			bert_tokenizer(lines[i : i + 1_00]   ,     add_special_tokens=lowerCAmelCase_   ,     truncation=lowerCAmelCase_   ,     max_length=5_12  )
												bert_res.extend(res['''input_ids''']  )
						assert len(lowerCAmelCase_  ) == len(lowerCAmelCase_  )

						UpperCAmelCase         =			[]
						for input_ids, chinese_word in zip(lowerCAmelCase_   ,     lowerCAmelCase_  ):
												UpperCAmelCase         =			[]
												for id in input_ids:
																		UpperCAmelCase         =			bert_tokenizer._convert_id_to_token(lowerCAmelCase_  )
																		input_tokens.append(lowerCAmelCase_  )
												UpperCAmelCase         =			add_sub_symbol(lowerCAmelCase_   ,     lowerCAmelCase_  )
												UpperCAmelCase         =			[]
												# 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] == "##":
																								UpperCAmelCase         =			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    lowerCamelCase__   ( A     :    Tuple  ):




						'''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(lowerCAmelCase_  ) > 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(lowerCAmelCase_   ,     lowerCAmelCase_   ,     lowerCAmelCase_  )

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


if __name__ == "__main__":
	_lowercase    :    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""",
	)

	_lowercase    :    Union[str, Any]			     =  parser.parse_args()
	main(args)





'''simple docstring'''



import functools


def    lowerCamelCase__   ( A     :    list[int]   ,     A     :    list[int]  ):




						'''simple docstring'''






						if not isinstance(A   ,     A  ) or not all(isinstance(A   ,     A  ) for day in days  ):
												raise ValueError('''The parameter days should be a list of integers'''  )

						if len(A  ) != 3 or not all(isinstance(A   ,     A  ) for cost in costs  ):
												raise ValueError('''The parameter costs should be a list of three integers'''  )

						if len(A  ) == 0:
												return 0

						if min(A  ) <= 0:
												raise ValueError('''All days elements should be greater than 0'''  )

						if max(A  ) >= 3_66:
												raise ValueError('''All days elements should be less than 366'''  )

						UpperCAmelCase         =			set(A  )

						@functools.cache
						def dynamic_programming(A     :    int  ) -> int:
												if index > 3_65:
																		return 0

												if index not in days_set:
																		return dynamic_programming(index + 1  )

												return min(
												    costs[0] + dynamic_programming(index + 1  )   ,     costs[1] + dynamic_programming(index + 7  )   ,     costs[2] + dynamic_programming(index + 30  )   ,     )

						return dynamic_programming(1  )


if __name__ == "__main__":
	import doctest

	doctest.testmod()





