





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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


lowerCAmelCase_    =    logging.get_logger(__name__)

lowerCAmelCase_    =    {'''vocab_file''': '''spiece.model'''}

lowerCAmelCase_    =    {
    '''vocab_file''': {
        '''bert_for_seq_generation''': (
            '''https://huggingface.co/google/bert_for_seq_generation_L-24_bbc_encoder/resolve/main/spiece.model'''
        ),
    }
}

lowerCAmelCase_    =    {'''bert_for_seq_generation''': 5_1_2}



class  __lowerCAmelCase	(      _UpperCamelCase					):
			lowerCamelCase_					:					str	      =				VOCAB_FILES_NAMES
			lowerCamelCase_					:					Tuple	      =				PRETRAINED_VOCAB_FILES_MAP
			lowerCamelCase_					:					str	      =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCamelCase_					:					List[int]	      =				[]
			lowerCamelCase_					:					List[Any]	      =				['input_ids', 'attention_mask']






			def __init__(self ,							__magic_name__ ,							__magic_name__="<s>" ,							__magic_name__="</s>" ,							__magic_name__="<unk>" ,							__magic_name__="<pad>" ,							__magic_name__="<::::>" ,							__magic_name__ = None ,							**__magic_name__ ,							)					->       str:


							'''simple docstring'''



							snake_case_						:   Union[str, Any]           =  {} if sp_model_kwargs is None else sp_model_kwargs

							# Add extra_ids to the special token list
							super().__init__(
							    bos_token=_UpperCAmelCase ,							eos_token=_UpperCAmelCase ,							unk_token=_UpperCAmelCase ,							pad_token=_UpperCAmelCase ,							sep_token=_UpperCAmelCase ,							sp_model_kwargs=self.sp_model_kwargs ,							**_UpperCAmelCase ,							)

							snake_case_						:   Tuple           =  vocab_file

							snake_case_						:   int           =  spm.SentencePieceProcessor(**self.sp_model_kwargs   )
							self.sp_model.Load(_UpperCAmelCase   )






			@property
			def       lowerCamelCase  (self   )					->       int:


							'''simple docstring'''



							return self.sp_model.get_piece_size()






			def       lowerCamelCase  (self   )					->       List[Any]:


							'''simple docstring'''



							snake_case_						:   Any           =  {self.convert_ids_to_tokens(_UpperCAmelCase   ): i for i in range(self.vocab_size   )}
							vocab.update(self.added_tokens_encoder   )
							return vocab






			def __getstate__(self   )					->       Optional[Any]:


							'''simple docstring'''



							snake_case_						:   List[Any]           =  self.__dict__.copy()
							snake_case_						:   Dict           =  None
							return state






			def __setstate__(self ,							__magic_name__   )					->       List[Any]:


							'''simple docstring'''



							snake_case_						:   Dict           =  d

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

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






			def       lowerCamelCase  (self ,							__magic_name__   )					->       Any:


							'''simple docstring'''



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






			def       lowerCamelCase  (self ,							__magic_name__   )					->       Optional[Any]:


							'''simple docstring'''



							return self.sp_model.piece_to_id(_UpperCAmelCase   )






			def       lowerCamelCase  (self ,							__magic_name__   )					->       int:


							'''simple docstring'''



							snake_case_						:   Union[str, Any]           =  self.sp_model.IdToPiece(_UpperCAmelCase   )
							return token






			def       lowerCamelCase  (self ,							__magic_name__   )					->       Optional[int]:


							'''simple docstring'''



							snake_case_						:   Tuple           =  []
							snake_case_						:   Union[str, Any]           =  ''
							for token in tokens:
											# make sure that special tokens are not decoded using sentencepiece model
											if token in self.all_special_tokens:
															out_string += self.sp_model.decode(_UpperCAmelCase   ) + token
															snake_case_						:   str           =  []
											else:
															current_sub_tokens.append(_UpperCAmelCase   )
							out_string += self.sp_model.decode(_UpperCAmelCase   )
							return out_string.strip()






			def       lowerCamelCase  (self ,							__magic_name__ ,							__magic_name__ = None   )					->       Any:


							'''simple docstring'''



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

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

							return (out_vocab_file,)












from typing import List, Optional

from tokenizers import ByteLevelBPETokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer


lowerCAmelCase_    =    logging.get_logger(__name__)

lowerCAmelCase_    =    {
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
}

lowerCAmelCase_    =    {
    '''vocab_file''': {
        '''facebook/blenderbot_small-90M''': '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json'''
    },
    '''merges_file''': {
        '''facebook/blenderbot_small-90M''': '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt'''
    },
    '''tokenizer_config_file''': {
        '''facebook/blenderbot_small-90M''': (
            '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json'''
        )
    },
}

lowerCAmelCase_    =    {
    '''facebook/blenderbot_small-90M''': 5_1_2,
}



class  __lowerCAmelCase	(      _a					):
			lowerCamelCase_					:					int	      =				VOCAB_FILES_NAMES
			lowerCamelCase_					:					List[Any]	      =				PRETRAINED_VOCAB_FILES_MAP
			lowerCamelCase_					:					int	      =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCamelCase_					:					Optional[Any]	      =				BlenderbotSmallTokenizer






			def __init__(self ,							__magic_name__=None ,							__magic_name__=None ,							__magic_name__="<|endoftext|>" ,							__magic_name__="<|endoftext|>" ,							__magic_name__="<|endoftext|>" ,							__magic_name__=False ,							__magic_name__=True ,							**__magic_name__ ,							)					->       Union[str, Any]:


							'''simple docstring'''



							super().__init__(
							    ByteLevelBPETokenizer(
							        vocab=__magic_name__ ,							merges=__magic_name__ ,							add_prefix_space=__magic_name__ ,							trim_offsets=__magic_name__ ,							) ,							bos_token=__magic_name__ ,							eos_token=__magic_name__ ,							unk_token=__magic_name__ ,							**__magic_name__ ,							)
							snake_case_						:   Optional[int]           =  add_prefix_space






			def       lowerCamelCase  (self ,							__magic_name__ ,							__magic_name__=None   )					->       Any:


							'''simple docstring'''



							snake_case_						:   Optional[int]           =  [self.bos_token_id] + token_ids_a + [self.eos_token_id]
							if token_ids_a is None:
											return output

							return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]






			def       lowerCamelCase  (self ,							__magic_name__ ,							__magic_name__ = None   )					->       List[int]:


							'''simple docstring'''



							snake_case_						:   List[str]           =  [self.sep_token_id]
							snake_case_						:   Optional[Any]           =  [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]
