



"""simple docstring"""






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


lowerCAmelCase__        =				logging.get_logger(__name__)

lowerCAmelCase__        =				{'''vocab_file''': '''sentencepiece.bpe.model'''}

lowerCAmelCase__        =				{
    '''vocab_file''': {
        '''moussaKam/mbarthez''': '''https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model''',
        '''moussaKam/barthez''': '''https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model''',
        '''moussaKam/barthez-orangesum-title''': (
            '''https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model'''
        ),
    },
}

lowerCAmelCase__        =				{
    '''moussaKam/mbarthez''': 1024,
    '''moussaKam/barthez''': 1024,
    '''moussaKam/barthez-orangesum-title''': 1024,
}

lowerCAmelCase__        =				'''▁'''






class        __snake_case       (	_lowercase):
  snake_case__				:   int  			=						VOCAB_FILES_NAMES
  snake_case__				:   Any  			=						PRETRAINED_VOCAB_FILES_MAP
  snake_case__				:   Optional[Any]  			=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  snake_case__				:   Union[str, Any]  			=						["input_ids", "attention_mask"]




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






         """simple docstring"""






         _lowerCamelCase						:				Dict    			= AddedToken(__lowerCAmelCase						,					lstrip=__lowerCAmelCase						,					rstrip=__lowerCAmelCase		) if isinstance(__lowerCAmelCase						,					__lowerCAmelCase		) else mask_token

         _lowerCamelCase						:				List[Any]    			= {} 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						,					sp_model_kwargs=self.sp_model_kwargs						,					**__lowerCAmelCase						,					)

         _lowerCamelCase						:				Dict    			= vocab_file
         _lowerCamelCase						:				int    			= spm.SentencePieceProcessor(**self.sp_model_kwargs		)
         self.sp_model.Load(str(__lowerCAmelCase		)		)

         _lowerCamelCase						:				Union[str, Any]    			= {'''<s>''': 0, '''<pad>''': 1, '''</s>''': 2, '''<unk>''': 3}

         _lowerCamelCase						:				int    			= len(self.sp_model		) - 1
         _lowerCamelCase						:				List[str]    			= {v: k for k, v in self.fairseq_tokens_to_ids.items()}




  def 						SCREAMING_SNAKE_CASE				( self     :						Dict						,					__lowerCAmelCase     :						List[int]						,					__lowerCAmelCase     :						Optional[List[int]] = None		):






         """simple docstring"""






         if token_ids_a is None:
                return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
         _lowerCamelCase						:				List[str]    			= [self.cls_token_id]
         _lowerCamelCase						:				int    			= [self.sep_token_id]
         return cls + token_ids_a + sep + sep + token_ids_a + sep




  def 						SCREAMING_SNAKE_CASE				( self     :						Dict						,					__lowerCAmelCase     :						List[int]						,					__lowerCAmelCase     :						Optional[List[int]] = None						,					__lowerCAmelCase     :						bool = False		):






         """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 						SCREAMING_SNAKE_CASE				( self     :						List[Any]						,					__lowerCAmelCase     :						List[int]						,					__lowerCAmelCase     :						Optional[List[int]] = None		):






         """simple docstring"""






         _lowerCamelCase						:				List[Any]    			= [self.sep_token_id]
         _lowerCamelCase						:				Optional[int]    			= [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 						SCREAMING_SNAKE_CASE				( self     :						Optional[int]		):






         """simple docstring"""






         return len(self.sp_model		)




  def 						SCREAMING_SNAKE_CASE				( self     :						Dict		):






         """simple docstring"""






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




  def 						SCREAMING_SNAKE_CASE				( self     :						Union[str, Any]						,					__lowerCAmelCase     :						str		):






         """simple docstring"""






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




  def 						SCREAMING_SNAKE_CASE				( self     :						Optional[Any]						,					__lowerCAmelCase     :						List[str]		):






         """simple docstring"""






         if token in self.fairseq_tokens_to_ids:
                return self.fairseq_tokens_to_ids[token]
         _lowerCamelCase						:				List[Any]    			= self.sp_model.PieceToId(__lowerCAmelCase		)

         return spm_id if spm_id else self.unk_token_id




  def 						SCREAMING_SNAKE_CASE				( self     :						List[Any]						,					__lowerCAmelCase     :						str		):






         """simple docstring"""






         if index in self.fairseq_ids_to_tokens:
                return self.fairseq_ids_to_tokens[index]
         return self.sp_model.IdToPiece(__lowerCAmelCase		)




  def 						SCREAMING_SNAKE_CASE				( self     :						str						,					__lowerCAmelCase     :						Dict		):






         """simple docstring"""






         _lowerCamelCase						:				Tuple    			= []
         _lowerCamelCase						:				Tuple    			= ''''''
         _lowerCamelCase						:				Dict    			= 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
                       _lowerCamelCase						:				Union[str, Any]    			= True
                       _lowerCamelCase						:				List[Any]    			= []
                else:
                       current_sub_tokens.append(__lowerCAmelCase		)
                       _lowerCamelCase						:				List[str]    			= False
         out_string += self.sp_model.decode(__lowerCAmelCase		)
         return out_string.strip()




  def __getstate__( self     :						List[str]		):






         """simple docstring"""






         _lowerCamelCase						:				Dict    			= self.__dict__.copy()
         _lowerCamelCase						:				int    			= None
         return state




  def __setstate__( self     :						int						,					__lowerCAmelCase     :						Any		):






         """simple docstring"""






         _lowerCamelCase						:				Union[str, Any]    			= d

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

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




  def 						SCREAMING_SNAKE_CASE				( self     :						Tuple						,					__lowerCAmelCase     :						str						,					__lowerCAmelCase     :						Optional[str] = None		):






         """simple docstring"""






         if not os.path.isdir(__lowerCAmelCase		):
                logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''		)
                return
         _lowerCamelCase						:				Any    			= 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 ...configuration_utils import PretrainedConfig
from ...utils import logging


__a  :     str       =  logging.get_logger(__name__)

__a  :     Optional[int]       =  {
    """google/vivit-b-16x2-kinetics400""": (
        """https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json"""
    ),
    # See all Vivit models at https://huggingface.co/models?filter=vivit
}




class    _UpperCamelCase      (						_UpperCAmelCase ):


			"""simple docstring"""






			__a  : Tuple			 =						'''vivit'''





			def __init__(   self      ,   lowerCAmelCase__=2_24      ,   lowerCAmelCase__=32      ,   lowerCAmelCase__=[2, 16, 16]      ,   lowerCAmelCase__=3      ,   lowerCAmelCase__=7_68      ,   lowerCAmelCase__=12      ,   lowerCAmelCase__=12      ,   lowerCAmelCase__=30_72      ,   lowerCAmelCase__="gelu_fast"      ,   lowerCAmelCase__=0.0      ,   lowerCAmelCase__=0.0      ,   lowerCAmelCase__=0.02      ,   lowerCAmelCase__=1E-06      ,   lowerCAmelCase__=True      ,   **lowerCAmelCase__      ,   )     ->					int:

							'''simple docstring'''


							__lowercase 			=							hidden_size
							__lowercase 			=							num_hidden_layers
							__lowercase 			=							num_attention_heads
							__lowercase 			=							intermediate_size
							__lowercase 			=							hidden_act
							__lowercase 			=							hidden_dropout_prob
							__lowercase 			=							attention_probs_dropout_prob
							__lowercase 			=							initializer_range
							__lowercase 			=							layer_norm_eps

							__lowercase 			=							image_size
							__lowercase 			=							num_frames
							__lowercase 			=							tubelet_size
							__lowercase 			=							num_channels
							__lowercase 			=							qkv_bias

							super().__init__(**lowerCAmelCase__						)