


import os
from shutil import copyfile
from typing import Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
					from .tokenization_reformer import ReformerTokenizer
else:
					UpperCamelCase			:					Any         =							None


UpperCamelCase			:					List[Any]         =							logging.get_logger(__name__)


UpperCamelCase			:					int         =							'''▁'''

UpperCamelCase			:					List[str]         =							{'''vocab_file''': '''spiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

UpperCamelCase			:					Any         =							{
    '''vocab_file''': {
        '''google/reformer-crime-and-punishment''': (
            '''https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model'''
        )
    },
    '''tokenizer_file''': {
        '''google/reformer-crime-and-punishment''': (
            '''https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/tokenizer.json'''
        )
    },
}

UpperCamelCase			:					List[str]         =							{
    '''google/reformer-crime-and-punishment''': 524_288,
}

class      __snake_case				(   _UpperCAmelCase):
					SCREAMING_SNAKE_CASE_		:       int								=			VOCAB_FILES_NAMES
					SCREAMING_SNAKE_CASE_		:       Union[str, Any]								=			PRETRAINED_VOCAB_FILES_MAP
					SCREAMING_SNAKE_CASE_		:       List[Any]								=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					SCREAMING_SNAKE_CASE_		:       Dict								=			["input_ids", "attention_mask"]
					SCREAMING_SNAKE_CASE_		:       List[Any]								=			ReformerTokenizer
					def __init__(						self       :						int	,      _lowerCAmelCase       :						Dict=None	,      _lowerCAmelCase       :						str=None	,      _lowerCAmelCase       :						Tuple="</s>"	,      _lowerCAmelCase       :						int="<unk>"	,      _lowerCAmelCase       :						Any=[]	,      **_lowerCAmelCase       :						List[str]	,      )							->					Any:



											'''simple docstring'''





											super().__init__(
											    _lowerCAmelCase	,      tokenizer_file=_lowerCAmelCase	,      eos_token=_lowerCAmelCase	,      unk_token=_lowerCAmelCase	,      additional_special_tokens=_lowerCAmelCase	,      **_lowerCAmelCase	,      )

											__magic_name__					=      vocab_file
											__magic_name__					=      False if not self.vocab_file else True







					def 	a			(						self       :						Union[str, Any]	,      _lowerCAmelCase       :						str	,      _lowerCAmelCase       :						Optional[str] = None  )							->					Tuple[str]:



											'''simple docstring'''





											if not self.can_save_slow_tokenizer:
																	raise ValueError(
																	    'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
																	    'tokenizer.'  )

											if not os.path.isdir(_lowerCAmelCase  ):
																	logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''  )
																	return
											__magic_name__					=      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  ):
																	copyfile(self.vocab_file	,      _lowerCAmelCase  )

											return (out_vocab_file,)





from ..utils import DummyObject, requires_backends

class      __snake_case				(   metaclass=_UpperCAmelCase):
					SCREAMING_SNAKE_CASE_		:       str								=			["torch", "transformers", "k_diffusion"]
					def __init__(						self       :						Tuple	,      *_lowerCAmelCase       :						Union[str, Any]	,      **_lowerCAmelCase       :						Union[str, Any]  )							->					Dict:



											'''simple docstring'''





											requires_backends(self	,      ['torch', 'transformers', 'k_diffusion']  )
					@classmethod
					def 	a			(						cls       :						Optional[int]	,      *_lowerCAmelCase       :						Any	,      **_lowerCAmelCase       :						Optional[Any]  )							->					Optional[Any]:



											'''simple docstring'''





											requires_backends(cls	,      ['torch', 'transformers', 'k_diffusion']  )







					@classmethod
					def 	a			(						cls       :						Union[str, Any]	,      *_lowerCAmelCase       :						Tuple	,      **_lowerCAmelCase       :						str  )							->					Tuple:



											'''simple docstring'''





											requires_backends(cls	,      ['torch', 'transformers', 'k_diffusion']  )

