


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      :    Union[str, Any]		=					logging.get_logger(__name__)


A      :    List[str]		=					"▁"

A      :    Dict		=					{"vocab_file": "spiece.model"}

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

A      :    Optional[int]		=					{
    "google/reformer-crime-and-punishment": 524288,
}







class 			_lowercase (							lowercase__):


       """simple docstring"""




       A__											=			VOCAB_FILES_NAMES
       A__											=			PRETRAINED_VOCAB_FILES_MAP
       A__											=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       A__											=			["input_ids", "attention_mask"]





       def __init__(   self							:			int					,      __lowerCamelCase							:			Union[str, Any]					,      __lowerCamelCase							:			str="</s>"					,      __lowerCamelCase							:			Dict="<unk>"					,      __lowerCamelCase							:			Optional[int]=[]					,      __lowerCamelCase							:			Optional[int] = None					,      **__lowerCamelCase							:			List[str]					,      ):


             '''simple docstring'''



             lowerCamelCase__		:				Optional[int]    =  {} 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					,      )

             lowerCamelCase__		:				Tuple    =  vocab_file
             lowerCamelCase__		:				Union[str, Any]    =  spm.SentencePieceProcessor(**self.sp_model_kwargs       )
             self.sp_model.Load(__lowerCamelCase       )





       @property
       def 						lowerCAmelCase     (   self							:			Dict       ):


             '''simple docstring'''



             return self.sp_model.get_piece_size()





       def 						lowerCAmelCase     (   self							:			Optional[int]       ):


             '''simple docstring'''



             lowerCamelCase__		:				Optional[Any]    =  {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							:			List[str]       ):


             '''simple docstring'''



             lowerCamelCase__		:				Any    =  self.__dict__.copy()
             lowerCamelCase__		:				Optional[Any]    =  None
             return state





       def __setstate__(   self							:			Tuple					,      __lowerCamelCase							:			List[Any]       ):


             '''simple docstring'''



             lowerCamelCase__		:				Optional[Any]    =  d

             # for backward compatibility
             if not hasattr(self					,      "sp_model_kwargs"       ):
                   lowerCamelCase__		:				Union[str, Any]    =  {}

             lowerCamelCase__		:				Optional[int]    =  spm.SentencePieceProcessor(**self.sp_model_kwargs       )
             self.sp_model.Load(self.vocab_file       )





       def 						lowerCAmelCase     (   self							:			Tuple					,      __lowerCamelCase							:			List[str]       ):


             '''simple docstring'''



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





       def 						lowerCAmelCase     (   self							:			Optional[int]					,      __lowerCamelCase							:			List[Any]       ):


             '''simple docstring'''



             return self.sp_model.piece_to_id(__lowerCamelCase       )





       def 						lowerCAmelCase     (   self							:			Dict					,      __lowerCamelCase							:			Optional[int]       ):


             '''simple docstring'''



             if index < self.sp_model.get_piece_size():
                   lowerCamelCase__		:				Union[str, Any]    =  self.sp_model.IdToPiece(__lowerCamelCase       )
             return token





       def 						lowerCAmelCase     (   self							:			int					,      __lowerCamelCase							:			Any       ):


             '''simple docstring'''



             lowerCamelCase__		:				str    =  []
             lowerCamelCase__		:				List[str]    =  ""
             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
                         lowerCamelCase__		:				List[str]    =  []
                   else:
                         current_sub_tokens.append(__lowerCamelCase       )
             out_string += self.sp_model.decode(__lowerCamelCase       )
             return out_string.strip()





       def 						lowerCAmelCase     (   self							:			Union[str, Any]					,      __lowerCamelCase							:			Dict					,      __lowerCamelCase							:			List[Any] = None       ):


             '''simple docstring'''



             if not os.path.isdir(__lowerCamelCase       ):
                   logger.error(f"Vocabulary path ({save_directory}) should be a directory"       )
                   return
             lowerCamelCase__		:				Dict    =  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:
                         lowerCamelCase__		:				Tuple    =  self.sp_model.serialized_model_proto()
                         fi.write(__lowerCamelCase       )

             return (out_vocab_file,)






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase__   	=							{
    '''configuration_timesformer''': ['''TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TimesformerConfig'''],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase__   	=							[
      '''TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''TimesformerModel''',
      '''TimesformerForVideoClassification''',
      '''TimesformerPreTrainedModel''',
  ]

if TYPE_CHECKING:
  from .configuration_timesformer import TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, TimesformerConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_timesformer import (
        TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        TimesformerForVideoClassification,
        TimesformerModel,
        TimesformerPreTrainedModel,
    )

else:
  import sys

  UpperCAmelCase__   	=							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

