


'''simple docstring'''






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


lowercase							=logging.get_logger(__name__)


lowercase							="""▁"""

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

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

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






class  __magic_name__							(		lowerCAmelCase__    ):
       UpperCAmelCase										=VOCAB_FILES_NAMES
       UpperCAmelCase										=PRETRAINED_VOCAB_FILES_MAP
       UpperCAmelCase										=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       UpperCAmelCase										=["input_ids", "attention_mask"]






       def __init__(      self  ,							snake_case  ,							snake_case="</s>"  ,							snake_case="<unk>"  ,							snake_case=[]  ,							snake_case = None  ,							**snake_case  ,							)						->  Dict:




          '''simple docstring'''
          _UpperCAmelCase       :       int							   ={} if sp_model_kwargs is None else sp_model_kwargs

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

          _UpperCAmelCase       :       List[str]							   =vocab_file
          _UpperCAmelCase       :       Dict							   =spm.SentencePieceProcessor(**self.sp_model_kwargs)
          self.sp_model.Load(a__)






       @property
       def       lowerCAmelCase		(      self)						->  Dict:




          '''simple docstring'''
          return self.sp_model.get_piece_size()






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




          '''simple docstring'''
          _UpperCAmelCase       :       int							   ={self.convert_ids_to_tokens(a__): i for i in range(self.vocab_size)}
          vocab.update(self.added_tokens_encoder)
          return vocab






       def __getstate__(      self)						->  List[str]:




          '''simple docstring'''
          _UpperCAmelCase       :       Any							   =self.__dict__.copy()
          _UpperCAmelCase       :       Union[str, Any]							   =None
          return state






       def __setstate__(      self  ,							snake_case)						->  Any:




          '''simple docstring'''
          _UpperCAmelCase       :       Optional[Any]							   =d

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

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






       def       lowerCAmelCase		(      self  ,							snake_case)						->  Dict:




          '''simple docstring'''
          return self.sp_model.encode(a__  ,							out_type=a__)






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




          '''simple docstring'''
          return self.sp_model.piece_to_id(a__)






       def       lowerCAmelCase		(      self  ,							snake_case)						->  Dict:




          '''simple docstring'''
          if index < self.sp_model.get_piece_size():
             _UpperCAmelCase       :       List[Any]							   =self.sp_model.IdToPiece(a__)
          return token






       def       lowerCAmelCase		(      self  ,							snake_case)						->  Any:




          '''simple docstring'''
          _UpperCAmelCase       :       List[Any]							   =[]
          _UpperCAmelCase       :       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(a__) + token
                _UpperCAmelCase       :       Any							   =[]
             else:
                current_sub_tokens.append(a__)
          out_string += self.sp_model.decode(a__)
          return out_string.strip()






       def       lowerCAmelCase		(      self  ,							snake_case  ,							snake_case = None)						->  Any:




          '''simple docstring'''
          if not os.path.isdir(a__):
             logger.error(f"Vocabulary path ({save_directory}) should be a directory")
             return
          _UpperCAmelCase       :       List[Any]							   =os.path.join(
              a__  ,							(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])

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

          return (out_vocab_file,)





'''simple docstring'''






import jax.numpy as jnp

from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig


lowercase							=logging.get_logger(__name__)

lowercase							='T5Config'





def lowerCamelCase__      (						__lowerCamelCase	:							jnp.array	,   __lowerCamelCase	:							int	,   __lowerCamelCase	:							int							):







   '''simple docstring'''




   _UpperCAmelCase       :       List[Any]							   =jnp.zeros_like(__lowerCamelCase							)
   _UpperCAmelCase       :       Union[str, Any]							   =shifted_input_ids.at[:, 1:].set(input_ids[:, :-1]							)
   _UpperCAmelCase       :       List[Any]							   =shifted_input_ids.at[:, 0].set(__lowerCamelCase							)

   _UpperCAmelCase       :       str							   =jnp.where(shifted_input_ids == -1_0_0	,   __lowerCamelCase	,   __lowerCamelCase							)
   return shifted_input_ids






class  __magic_name__							(		lowerCAmelCase    ):
       UpperCAmelCase										="mt5"
       UpperCAmelCase										=MTaConfig






class  __magic_name__							(		lowerCAmelCase    ):
       UpperCAmelCase										="mt5"
       UpperCAmelCase										=MTaConfig






class  __magic_name__							(		lowerCAmelCase    ):
       UpperCAmelCase										="mt5"
       UpperCAmelCase										=MTaConfig

