




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__				     = logging.get_logger(__name__)

UpperCAmelCase__				     = {"vocab_file": "sentencepiece.bpe.model"}

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

UpperCAmelCase__				     = {
    "camembert-base": 512,
}

UpperCAmelCase__				     = "▁"







class a (     __SCREAMING_SNAKE_CASE  ):
						"""simple docstring"""

						UpperCamelCase_	:       str       	=		VOCAB_FILES_NAMES
						UpperCamelCase_	:       List[Any]       	=		PRETRAINED_VOCAB_FILES_MAP
						UpperCamelCase_	:       Any       	=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						UpperCamelCase_	:       List[Any]       	=		['input_ids', 'attention_mask']






						def __init__( self :     List[Any]				,							lowerCamelCase__ :     int				,							lowerCamelCase__ :     Any="<s>"				,							lowerCamelCase__ :     str="</s>"				,							lowerCamelCase__ :     List[Any]="</s>"				,							lowerCamelCase__ :     List[Any]="<s>"				,							lowerCamelCase__ :     List[Any]="<unk>"				,							lowerCamelCase__ :     Any="<pad>"				,							lowerCamelCase__ :     int="<mask>"				,							lowerCamelCase__ :     int=["<s>NOTUSED", "</s>NOTUSED"]				,							lowerCamelCase__ :     Optional[Dict[str, Any]] = None				,							**lowerCamelCase__ :     Optional[int]				,							)    ->						None:
													"""simple docstring"""


													__lowercase      =    AddedToken(lowerCamelCase__				,							lstrip=lowerCamelCase__				,							rstrip=lowerCamelCase__				) if isinstance(lowerCamelCase__				,							lowerCamelCase__				) else mask_token

													__lowercase      =    {} if sp_model_kwargs is None else sp_model_kwargs

													super().__init__(
													    bos_token=lowerCamelCase__				,							eos_token=lowerCamelCase__				,							unk_token=lowerCamelCase__				,							sep_token=lowerCamelCase__				,							cls_token=lowerCamelCase__				,							pad_token=lowerCamelCase__				,							mask_token=lowerCamelCase__				,							additional_special_tokens=lowerCamelCase__				,							sp_model_kwargs=self.sp_model_kwargs				,							**lowerCamelCase__				,							)
													__lowercase      =    spm.SentencePieceProcessor(**self.sp_model_kwargs				)
													self.sp_model.Load(str(lowerCamelCase__				)				)
													__lowercase      =    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>
													__lowercase      =    {'''<s>NOTUSED''': 0, '''<pad>''': 1, '''</s>NOTUSED''': 2, '''<unk>''': 3}
													__lowercase      =    len(self.fairseq_tokens_to_ids				)
													__lowercase      =    len(self.sp_model				) + len(self.fairseq_tokens_to_ids				)
													__lowercase      =    {v: k for k, v in self.fairseq_tokens_to_ids.items()}






						def     UpperCAmelCase_      ( self :     List[Any]				,							lowerCamelCase__ :     List[int]				,							lowerCamelCase__ :     Optional[List[int]] = None				)    ->						List[int]:
													"""simple docstring"""


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






						def     UpperCAmelCase_      ( self :     Dict				,							lowerCamelCase__ :     List[int]				,							lowerCamelCase__ :     Optional[List[int]] = None				,							lowerCamelCase__ :     bool = False				)    ->						List[int]:
													"""simple docstring"""


													if already_has_special_tokens:
																				return super().get_special_tokens_mask(
																				    token_ids_a=lowerCamelCase__				,							token_ids_a=lowerCamelCase__				,							already_has_special_tokens=lowerCamelCase__				)

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






						def     UpperCAmelCase_      ( self :     List[Any]				,							lowerCamelCase__ :     List[int]				,							lowerCamelCase__ :     Optional[List[int]] = None				)    ->						List[int]:
													"""simple docstring"""


													__lowercase      =    [self.sep_token_id]
													__lowercase      =    [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     UpperCAmelCase_      ( self :     List[str]				)    ->						List[Any]:
													"""simple docstring"""


													return len(self.fairseq_tokens_to_ids				) + len(self.sp_model				)






						def     UpperCAmelCase_      ( self :     List[Any]				)    ->						List[Any]:
													"""simple docstring"""


													__lowercase      =    {self.convert_ids_to_tokens(lowerCamelCase__				): i for i in range(self.vocab_size				)}
													vocab.update(self.added_tokens_encoder				)
													return vocab






						def     UpperCAmelCase_      ( self :     Any				,							lowerCamelCase__ :     str				)    ->						List[str]:
													"""simple docstring"""


													return self.sp_model.encode(lowerCamelCase__				,							out_type=lowerCamelCase__				)






						def     UpperCAmelCase_      ( self :     str				,							lowerCamelCase__ :     str				)    ->						Any:
													"""simple docstring"""


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






						def     UpperCAmelCase_      ( self :     Optional[int]				,							lowerCamelCase__ :     Optional[Any]				)    ->						str:
													"""simple docstring"""


													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     UpperCAmelCase_      ( self :     List[Any]				,							lowerCamelCase__ :     int				)    ->						Any:
													"""simple docstring"""


													__lowercase      =    []
													__lowercase      =    ''''''
													__lowercase      =    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(lowerCamelCase__				) + token
																											__lowercase      =    True
																											__lowercase      =    []
																				else:
																											current_sub_tokens.append(lowerCamelCase__				)
																											__lowercase      =    False
													out_string += self.sp_model.decode(lowerCamelCase__				)
													return out_string.strip()






						def __getstate__( self :     Tuple				)    ->						Union[str, Any]:
													"""simple docstring"""


													__lowercase      =    self.__dict__.copy()
													__lowercase      =    None
													return state






						def __setstate__( self :     Any				,							lowerCamelCase__ :     Dict				)    ->						Tuple:
													"""simple docstring"""


													__lowercase      =    d

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

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






						def     UpperCAmelCase_      ( self :     Tuple				,							lowerCamelCase__ :     str				,							lowerCamelCase__ :     Optional[str] = None				)    ->						Tuple[str]:
													"""simple docstring"""


													if not os.path.isdir(lowerCamelCase__				):
																				logger.error(f'Vocabulary path ({save_directory}) should be a directory'				)
																				return
													__lowercase      =    os.path.join(
													    lowerCamelCase__				,							(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']				)

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

													return (out_vocab_file,)












from __future__ import annotations







def 		_A(       UpperCamelCase__							:			list[int]				,       UpperCamelCase__							:			list[int]				,       UpperCamelCase__							:			int				)    -> tuple[float, list[float]]:
							'''simple docstring'''


							__lowercase      =    list(range(len(UpperCamelCase__				)				)				)
							__lowercase      =    [v / w for v, w in zip(UpperCamelCase__				,       UpperCamelCase__				)]
							index.sort(key=lambda UpperCamelCase__				: ratio[i]				,       reverse=UpperCamelCase__				)

							__lowercase      =    0
							__lowercase      =    [0] * len(UpperCamelCase__				)
							for i in index:
														if weight[i] <= capacity:
																					__lowercase      =    1
																					max_value += value[i]
																					capacity -= weight[i]
														else:
																					__lowercase      =    capacity / weight[i]
																					max_value += value[i] * capacity / weight[i]
																					break

							return max_value, fractions


if __name__ == "__main__":
			import doctest

			doctest.testmod()






