

import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_UpperCAmelCase						:  Optional[Any]									=			logging.get_logger(__name__)

_UpperCAmelCase						:  Any									=			{"""vocab_file""": """sentencepiece.bpe.model"""}

_UpperCAmelCase						:  int									=			{
    """vocab_file""": {
        """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model""",
    }
}

_UpperCAmelCase						:  Tuple									=			{
    """camembert-base""": 512,
}

_UpperCAmelCase						:  Union[str, Any]									=			"""▁"""







class 					lowercase							(			lowercase_     ):
				__SCREAMING_SNAKE_CASE   :					int			     =     VOCAB_FILES_NAMES
				__SCREAMING_SNAKE_CASE   :					Optional[int]			     =     PRETRAINED_VOCAB_FILES_MAP
				__SCREAMING_SNAKE_CASE   :					Union[str, Any]			     =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				__SCREAMING_SNAKE_CASE   :					int			     =     ['''input_ids''', '''attention_mask''']




				def __init__(   self ,  snake_case ,  snake_case="<s>" ,  snake_case="</s>" ,  snake_case="</s>" ,  snake_case="<s>" ,  snake_case="<unk>" ,  snake_case="<pad>" ,  snake_case="<mask>" ,  snake_case=["<s>NOTUSED", "</s>NOTUSED"] ,  snake_case = None ,  **snake_case ,  ):
											# Mask token behave like a normal word, i.e. include the space before it
											snake_case_     							=       AddedToken(snake_case ,  lstrip=snake_case ,  rstrip=snake_case			) if isinstance(snake_case ,  snake_case			) else mask_token

											snake_case_     							=       {} if sp_model_kwargs is None else sp_model_kwargs

											super().__init__(
											    bos_token=snake_case ,  eos_token=snake_case ,  unk_token=snake_case ,  sep_token=snake_case ,  cls_token=snake_case ,  pad_token=snake_case ,  mask_token=snake_case ,  additional_special_tokens=snake_case ,  sp_model_kwargs=self.sp_model_kwargs ,  **snake_case ,  )
											snake_case_     							=       spm.SentencePieceProcessor(**self.sp_model_kwargs			)
											self.sp_model.Load(str(snake_case			)			)
											snake_case_     							=       vocab_file
											# HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
											# sentencepiece vocabulary (this is the case for <s> and </s>
											snake_case_     							=       {'<s>NOTUSED': 0, '<pad>': 1, '</s>NOTUSED': 2, '<unk>': 3}
											snake_case_     							=       len(self.fairseq_tokens_to_ids			)
											snake_case_     							=       len(self.sp_model			) + len(self.fairseq_tokens_to_ids			)
											snake_case_     							=       {v: k for k, v in self.fairseq_tokens_to_ids.items()}




				def        a				(   self ,  snake_case ,  snake_case = None			):

											if token_ids_a is None:
																		return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
											snake_case_     							=       [self.cls_token_id]
											snake_case_     							=       [self.sep_token_id]
											return cls + token_ids_a + sep + sep + token_ids_a + sep




				def        a				(   self ,  snake_case ,  snake_case = None ,  snake_case = False			):
											if already_has_special_tokens:
																		return super().get_special_tokens_mask(
																		    token_ids_a=snake_case ,  token_ids_a=snake_case ,  already_has_special_tokens=snake_case			)

											if token_ids_a is None:
																		return [1] + ([0] * len(snake_case			)) + [1]
											return [1] + ([0] * len(snake_case			)) + [1, 1] + ([0] * len(snake_case			)) + [1]




				def        a				(   self ,  snake_case ,  snake_case = None			):
											snake_case_     							=       [self.sep_token_id]
											snake_case_     							=       [self.cls_token_id]

											if token_ids_a is None:
																		return len(cls + token_ids_a + sep			) * [0]
											return len(cls + token_ids_a + sep + sep + token_ids_a + sep			) * [0]




				@property
				def        a				(   self			):
											return len(self.fairseq_tokens_to_ids			) + len(self.sp_model			)




				def        a				(   self			):
											snake_case_     							=       {self.convert_ids_to_tokens(snake_case			): i for i in range(self.vocab_size			)}
											vocab.update(self.added_tokens_encoder			)
											return vocab




				def        a				(   self ,  snake_case			):
											return self.sp_model.encode(snake_case ,  out_type=snake_case			)




				def        a				(   self ,  snake_case			):
											if token in self.fairseq_tokens_to_ids:
																		return self.fairseq_tokens_to_ids[token]
											elif self.sp_model.PieceToId(snake_case			) == 0:
																		# Convert sentence piece unk token to fairseq unk token index
																		return self.unk_token_id
											return self.fairseq_offset + self.sp_model.PieceToId(snake_case			)




				def        a				(   self ,  snake_case			):
											if index in self.fairseq_ids_to_tokens:
																		return self.fairseq_ids_to_tokens[index]
											return self.sp_model.IdToPiece(index - self.fairseq_offset			)




				def        a				(   self ,  snake_case			):
											snake_case_     							=       []
											snake_case_     							=       ''
											snake_case_     							=       False
											for token in tokens:
																		# make sure that special tokens are not decoded using sentencepiece model
																		if token in self.all_special_tokens:
																									if not prev_is_special:
																																out_string += " "
																									out_string += self.sp_model.decode(snake_case			) + token
																									snake_case_     							=       True
																									snake_case_     							=       []
																		else:
																									current_sub_tokens.append(snake_case			)
																									snake_case_     							=       False
											out_string += self.sp_model.decode(snake_case			)
											return out_string.strip()




				def __getstate__(   self			):
											snake_case_     							=       self.__dict__.copy()
											snake_case_     							=       None
											return state




				def __setstate__(   self ,  snake_case			):
											snake_case_     							=       d

											# for backward compatibility
											if not hasattr(self ,  'sp_model_kwargs'			):
																		snake_case_     							=       {}

											snake_case_     							=       spm.SentencePieceProcessor(**self.sp_model_kwargs			)
											self.sp_model.Load(self.vocab_file			)




				def        a				(   self ,  snake_case ,  snake_case = None			):
											if not os.path.isdir(snake_case			):
																		logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''			)
																		return
											snake_case_     							=       os.path.join(
											    snake_case ,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']			)

											if os.path.abspath(self.vocab_file			) != os.path.abspath(snake_case			) and os.path.isfile(self.vocab_file			):
																		copyfile(self.vocab_file ,  snake_case			)
											elif not os.path.isfile(self.vocab_file			):
																		with open(snake_case ,  'wb'			) as fi:
																									snake_case_     							=       self.sp_model.serialized_model_proto()
																									fi.write(snake_case			)

											return (out_vocab_file,)







_UpperCAmelCase						:  int									=			range(2, 20 + 1)
_UpperCAmelCase						:  Dict									=			[10**k for k in range(ks[-1] + 1)]
_UpperCAmelCase						:  dict[int, dict[int, list[list[int]]]]									=			{}





def    __lowerCamelCase      (					UpperCamelCase__  ,				UpperCamelCase__  ,				UpperCamelCase__  ,				UpperCamelCase__ ):







							'''simple docstring'''






							snake_case_     							=       sum(a_i[j] for j in range(UpperCamelCase__  ,				len(UpperCamelCase__ ) ) )
							snake_case_     							=       sum(a_i[j] * base[j] for j in range(min(len(UpperCamelCase__ )  ,				UpperCamelCase__ ) ) )

							snake_case_							,       snake_case_     							=       0, 0
							snake_case_     							=       n - i

							snake_case_     							=       memo.get(UpperCamelCase__ )

							if sub_memo is not None:
														snake_case_     							=       sub_memo.get(UpperCamelCase__ )

														if jumps is not None and len(UpperCamelCase__ ) > 0:
																					# find and make the largest jump without going over
																					snake_case_     							=       -1
																					for _k in range(len(UpperCamelCase__ ) - 1  ,				-1  ,				-1 ):
																												if jumps[_k][2] <= k and jumps[_k][1] <= max_dn:
																																			snake_case_     							=       _k
																																			break

																					if max_jump >= 0:
																												snake_case_							,       snake_case_							,       snake_case_     							=       jumps[max_jump]
																												# since the difference between jumps is cached, add c
																												snake_case_     							=       diff + c
																												for j in range(min(UpperCamelCase__  ,				len(UpperCamelCase__ ) ) ):
																																			snake_case_							,       snake_case_     							=       divmod(UpperCamelCase__  ,				10 )
																												if new_c > 0:
																																			add(UpperCamelCase__  ,				UpperCamelCase__  ,				UpperCamelCase__ )

														else:
																					snake_case_     							=       []
							else:
														snake_case_     							=       {c: []}
														snake_case_     							=       sub_memo

							if dn >= max_dn or c + diff >= base[k]:
														return diff, dn

							if k > ks[0]:
														while True:
																					# keep doing smaller jumps
																					snake_case_							,       snake_case_     							=       next_term(UpperCamelCase__  ,				k - 1  ,				i + dn  ,				UpperCamelCase__ )
																					diff += _diff
																					dn += terms_jumped

																					if dn >= max_dn or c + diff >= base[k]:
																												break
							else:
														# would be too small a jump, just compute sequential terms instead
														snake_case_							,       snake_case_     							=       compute(UpperCamelCase__  ,				UpperCamelCase__  ,				i + dn  ,				UpperCamelCase__ )
														diff += _diff
														dn += terms_jumped

							snake_case_     							=       sub_memo[c]

							# keep jumps sorted by # of terms skipped
							snake_case_     							=       0
							while j < len(UpperCamelCase__ ):
														if jumps[j][1] > dn:
																					break
														j += 1

							# cache the jump for this value digitsum(b) and c
							sub_memo[c].insert(UpperCamelCase__  ,				(diff, dn, k) )
							return (diff, dn)





def    __lowerCamelCase      (					UpperCamelCase__  ,				UpperCamelCase__  ,				UpperCamelCase__  ,				UpperCamelCase__ ):







							'''simple docstring'''






							if i >= n:
														return 0, i
							if k > len(UpperCamelCase__ ):
														a_i.extend([0 for _ in range(k - len(UpperCamelCase__ ) )] )

							# note: a_i -> b * 10^k + c
							# ds_b -> digitsum(b)
							# ds_c -> digitsum(c)
							snake_case_     							=       i
							snake_case_							,       snake_case_							,       snake_case_     							=       0, 0, 0
							for j in range(len(UpperCamelCase__ ) ):
														if j >= k:
																					ds_b += a_i[j]
														else:
																					ds_c += a_i[j]

							while i < n:
														i += 1
														snake_case_     							=       ds_c + ds_b
														diff += addend
														snake_case_     							=       0
														for j in range(UpperCamelCase__ ):
																					snake_case_     							=       a_i[j] + addend
																					snake_case_							,       snake_case_     							=       divmod(UpperCamelCase__  ,				10 )

																					ds_c += a_i[j]

														if addend > 0:
																					break

							if addend > 0:
														add(UpperCamelCase__  ,				UpperCamelCase__  ,				UpperCamelCase__ )
							return diff, i - start_i





def    __lowerCamelCase      (					UpperCamelCase__  ,				UpperCamelCase__  ,				UpperCamelCase__ ):







							'''simple docstring'''






							for j in range(UpperCamelCase__  ,				len(UpperCamelCase__ ) ):
														snake_case_     							=       digits[j] + addend
														if s >= 10:
																					snake_case_							,       snake_case_     							=       divmod(UpperCamelCase__  ,				10 )
																					snake_case_     							=       addend // 10 + quotient
														else:
																					snake_case_     							=       s
																					snake_case_     							=       addend // 10

														if addend == 0:
																					break

							while addend > 0:
														snake_case_							,       snake_case_     							=       divmod(UpperCamelCase__  ,				10 )
														digits.append(UpperCamelCase__ )





def    __lowerCamelCase      (					UpperCamelCase__ = 10**15 ):







							'''simple docstring'''






							snake_case_     							=       [1]
							snake_case_     							=       1
							snake_case_     							=       0
							while True:
														snake_case_							,       snake_case_     							=       next_term(UpperCamelCase__  ,				20  ,				i + dn  ,				UpperCamelCase__ )
														dn += terms_jumped
														if dn == n - i:
																					break

							snake_case_     							=       0
							for j in range(len(UpperCamelCase__ ) ):
														a_n += digits[j] * 10**j
							return a_n


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




