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


a_							=      logging.get_logger(__name__)


a_							=      """▁"""

a_							=      {"""vocab_file""": """spiece.model"""}

a_							=      {
    """vocab_file""": {
        """google/reformer-crime-and-punishment""": (
            """https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model"""
        )
    }
}

a_							=      {
    """google/reformer-crime-and-punishment""": 524288,
}


class 			UpperCAmelCase__    (		snake_case					):



  """simple docstring"""






  lowerCAmelCase__		:	Union[str, Any]    		= VOCAB_FILES_NAMES
  lowerCAmelCase__		:	List[str]    		= PRETRAINED_VOCAB_FILES_MAP
  lowerCAmelCase__		:	int    		= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  lowerCAmelCase__		:	Tuple    		= ['input_ids', 'attention_mask']






  def __init__(				self:			str				,				__lowerCAmelCase:			int				,				__lowerCAmelCase:			Tuple="</s>"				,				__lowerCAmelCase:			str="<unk>"				,				__lowerCAmelCase:			Optional[int]=[]				,				__lowerCAmelCase:			Optional[Dict[str, Any]] = None				,				**__lowerCAmelCase:			Optional[Any]				,				) -> None:




    '''simple docstring'''




    __UpperCAmelCase						    =       {} if sp_model_kwargs is None else sp_model_kwargs

    super().__init__(
        eos_token=__lowerCAmelCase				,				unk_token=__lowerCAmelCase				,				additional_special_tokens=__lowerCAmelCase				,				sp_model_kwargs=self.sp_model_kwargs				,				**__lowerCAmelCase				,				)

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






  @property
  def 	_UpperCAmelCase				(				self:			Optional[int]   ) -> Optional[Any]:




    '''simple docstring'''




    return self.sp_model.get_piece_size()






  def 	_UpperCAmelCase				(				self:			Tuple   ) -> Dict[str, int]:




    '''simple docstring'''




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






  def __getstate__(				self:			Union[str, Any]   ) -> Any:




    '''simple docstring'''




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






  def __setstate__(				self:			Tuple				,				__lowerCAmelCase:			int   ) -> Union[str, Any]:




    '''simple docstring'''




    __UpperCAmelCase						    =       d

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

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






  def 	_UpperCAmelCase				(				self:			List[Any]				,				__lowerCAmelCase:			str   ) -> List[str]:




    '''simple docstring'''




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






  def 	_UpperCAmelCase				(				self:			str				,				__lowerCAmelCase:			Any   ) -> Optional[Any]:




    '''simple docstring'''




    return self.sp_model.piece_to_id(__lowerCAmelCase   )






  def 	_UpperCAmelCase				(				self:			str				,				__lowerCAmelCase:			List[Any]   ) -> Any:




    '''simple docstring'''




    if index < self.sp_model.get_piece_size():
      __UpperCAmelCase						    =       self.sp_model.IdToPiece(__lowerCAmelCase   )
    return token






  def 	_UpperCAmelCase				(				self:			List[str]				,				__lowerCAmelCase:			Dict   ) -> int:




    '''simple docstring'''




    __UpperCAmelCase						    =       []
    __UpperCAmelCase						    =       ""
    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(__lowerCAmelCase   ) + token
        __UpperCAmelCase						    =       []
      else:
        current_sub_tokens.append(__lowerCAmelCase   )
    out_string += self.sp_model.decode(__lowerCAmelCase   )
    return out_string.strip()






  def 	_UpperCAmelCase				(				self:			Optional[Any]				,				__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
    __UpperCAmelCase						    =       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:
        __UpperCAmelCase						    =       self.sp_model.serialized_model_proto()
        fi.write(__lowerCAmelCase   )

    return (out_vocab_file,)




from ...configuration_utils import PretrainedConfig
from ...utils import logging


a_							=      logging.get_logger(__name__)

a_							=      {
    """facebook/vit-mae-base""": """https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json""",
    # See all ViT MAE models at https://huggingface.co/models?filter=vit-mae
}


class 			UpperCAmelCase__    (		snake_case					):



  """simple docstring"""






  lowerCAmelCase__		:	Dict    		= 'vit_mae'






  def __init__(				self:			List[Any]				,				__lowerCAmelCase:			Any=768				,				__lowerCAmelCase:			List[str]=12				,				__lowerCAmelCase:			Optional[int]=12				,				__lowerCAmelCase:			Tuple=3_072				,				__lowerCAmelCase:			List[Any]="gelu"				,				__lowerCAmelCase:			Dict=0.0				,				__lowerCAmelCase:			Tuple=0.0				,				__lowerCAmelCase:			Any=0.02				,				__lowerCAmelCase:			List[Any]=1E-12				,				__lowerCAmelCase:			List[str]=224				,				__lowerCAmelCase:			Optional[Any]=16				,				__lowerCAmelCase:			Union[str, Any]=3				,				__lowerCAmelCase:			Tuple=True				,				__lowerCAmelCase:			Union[str, Any]=16				,				__lowerCAmelCase:			Optional[int]=512				,				__lowerCAmelCase:			int=8				,				__lowerCAmelCase:			int=2_048				,				__lowerCAmelCase:			str=0.75				,				__lowerCAmelCase:			Union[str, Any]=False				,				**__lowerCAmelCase:			List[Any]				,				) -> Optional[int]:




    '''simple docstring'''




    super().__init__(**__lowerCAmelCase   )

    __UpperCAmelCase						    =       hidden_size
    __UpperCAmelCase						    =       num_hidden_layers
    __UpperCAmelCase						    =       num_attention_heads
    __UpperCAmelCase						    =       intermediate_size
    __UpperCAmelCase						    =       hidden_act
    __UpperCAmelCase						    =       hidden_dropout_prob
    __UpperCAmelCase						    =       attention_probs_dropout_prob
    __UpperCAmelCase						    =       initializer_range
    __UpperCAmelCase						    =       layer_norm_eps
    __UpperCAmelCase						    =       image_size
    __UpperCAmelCase						    =       patch_size
    __UpperCAmelCase						    =       num_channels
    __UpperCAmelCase						    =       qkv_bias
    __UpperCAmelCase						    =       decoder_num_attention_heads
    __UpperCAmelCase						    =       decoder_hidden_size
    __UpperCAmelCase						    =       decoder_num_hidden_layers
    __UpperCAmelCase						    =       decoder_intermediate_size
    __UpperCAmelCase						    =       mask_ratio
    __UpperCAmelCase						    =       norm_pix_loss



