




'''simple docstring'''





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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_SCREAMING_SNAKE_CASE							:       Dict						=			logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE							:       Optional[int]						=			{"vocab_file": "sentencepiece.model"}

_SCREAMING_SNAKE_CASE							:       Optional[int]						=			{
    "vocab_file": {
        "google/rembert": "https://huggingface.co/google/rembert/resolve/main/sentencepiece.model",
    },
}

_SCREAMING_SNAKE_CASE							:       List[str]						=			{
    "google/rembert": 256,
}




class 			_snake_case		(     __lowercase							):
   lowerCAmelCase_					:				Optional[Any]							=   VOCAB_FILES_NAMES
   lowerCAmelCase_					:				int							=   PRETRAINED_VOCAB_FILES_MAP
   lowerCAmelCase_					:				Any							=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES




   def __init__( self    ,							a__    ,							a__=False    ,							a__=True    ,							a__=True    ,							a__="[CLS]"    ,							a__="[SEP]"    ,							a__="[UNK]"    ,							a__="[SEP]"    ,							a__="[PAD]"    ,							a__="[CLS]"    ,							a__="[MASK]"    ,							**a__    ,							)    ->    List[Any]:

          '''simple docstring'''




          super().__init__(
              do_lower_case=UpperCAmelCase__    ,							remove_space=UpperCAmelCase__    ,							keep_accents=UpperCAmelCase__    ,							bos_token=UpperCAmelCase__    ,							eos_token=UpperCAmelCase__    ,							unk_token=UpperCAmelCase__    ,							sep_token=UpperCAmelCase__    ,							pad_token=UpperCAmelCase__    ,							cls_token=UpperCAmelCase__    ,							mask_token=UpperCAmelCase__    ,							**UpperCAmelCase__    ,							)

          snake_case_      =				do_lower_case
          snake_case_      =				remove_space
          snake_case_      =				keep_accents
          snake_case_      =				vocab_file

          snake_case_      =				spm.SentencePieceProcessor()
          self.sp_model.Load(UpperCAmelCase__							)




   @property
   def        lowerCAmelCase__    ( self							)    ->    List[Any]:

          '''simple docstring'''




          return len(self.sp_model							)




   def        lowerCAmelCase__    ( self							)    ->    int:

          '''simple docstring'''




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




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

          '''simple docstring'''




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




   def __setstate__( self    ,							a__							)    ->    Dict:

          '''simple docstring'''




          snake_case_      =				d
          snake_case_      =				spm.SentencePieceProcessor()
          self.sp_model.Load(self.vocab_file							)




   def        lowerCAmelCase__    ( self    ,							a__    ,							a__=False							)    ->    Any:

          '''simple docstring'''




          snake_case_      =				self.sp_model.EncodeAsPieces(UpperCAmelCase__							)
          return pieces




   def        lowerCAmelCase__    ( self    ,							a__							)    ->    Any:

          '''simple docstring'''




          return self.sp_model.PieceToId(UpperCAmelCase__							)




   def        lowerCAmelCase__    ( self    ,							a__							)    ->    Optional[int]:

          '''simple docstring'''




          return self.sp_model.IdToPiece(UpperCAmelCase__							)




   def        lowerCAmelCase__    ( self    ,							a__							)    ->    int:

          '''simple docstring'''




          snake_case_      =				self.sp_model.decode_pieces(UpperCAmelCase__							)
          return out_string




   def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None							)    ->    List[int]:

          '''simple docstring'''




          snake_case_      =				[self.sep_token_id]
          snake_case_      =				[self.cls_token_id]
          if token_ids_a is None:
                 return cls + token_ids_a + sep
          return cls + token_ids_a + sep + token_ids_a + sep




   def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None    ,							a__ = False							)    ->    List[int]:

          '''simple docstring'''




          if already_has_special_tokens:
                 if token_ids_a is not None:
                        raise ValueError(
                            "You should not supply a second sequence if the provided sequence of "
                            "ids is already formatted with special tokens for the model."							)
                 return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

          if token_ids_a is not None:
                 return [1] + ([0] * len(UpperCAmelCase__							)) + [1] + ([0] * len(UpperCAmelCase__							)) + [1]
          return [1] + ([0] * len(UpperCAmelCase__							)) + [1]




   def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None							)    ->    List[int]:

          '''simple docstring'''




          snake_case_      =				[self.sep_token_id]
          snake_case_      =				[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							) * [0] + len(token_ids_a + sep							) * [1]




   def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None							)    ->    Tuple[str]:

          '''simple docstring'''




          if not os.path.isdir(UpperCAmelCase__							):
                 logger.error("Vocabulary path ({}) should be a directory".format(UpperCAmelCase__							)							)
                 return
          snake_case_      =				os.path.join(
              UpperCAmelCase__    ,							(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]							)

          if os.path.abspath(self.vocab_file							) != os.path.abspath(UpperCAmelCase__							):
                 copyfile(self.vocab_file    ,							UpperCAmelCase__							)

          return (out_vocab_file,)










'''simple docstring'''





import logging
import os

from .state import PartialState




class 			_snake_case		(     logging.LoggerAdapter							):




			@staticmethod
			def        lowerCAmelCase__    ( a__							)    ->    Optional[Any]:

										'''simple docstring'''




										snake_case_      =				PartialState()
										return not main_process_only or (main_process_only and state.is_main_process)




			def        lowerCAmelCase__    ( self    ,							a__    ,							a__    ,							*a__    ,							**a__							)    ->    List[Any]:

										'''simple docstring'''




										if PartialState._shared_state == {}:
																	raise RuntimeError(
																	    "You must initialize the accelerate state by calling either `PartialState()` or `Accelerator()` before using the logging utility."							)
										snake_case_      =				kwargs.pop("main_process_only"    ,							a__							)
										snake_case_      =				kwargs.pop("in_order"    ,							a__							)

										if self.isEnabledFor(a__							):
																	if self._should_log(a__							):
																								snake_case_ ,				snake_case_      =				self.process(a__    ,							a__							)
																								self.logger.log(a__    ,							a__    ,							*a__    ,							**a__							)

																	elif in_order:
																								snake_case_      =				PartialState()
																								for i in range(state.num_processes							):
																															if i == state.process_index:
																																						snake_case_ ,				snake_case_      =				self.process(a__    ,							a__							)
																																						self.logger.log(a__    ,							a__    ,							*a__    ,							**a__							)
																															state.wait_for_everyone()


def 					UpperCamelCase_(     snake_case							:	str							,    snake_case							:	str = None					):

							'''simple docstring'''






							if log_level is None:
														snake_case_      =				os.environ.get("ACCELERATE_LOG_LEVEL"							,    snake_case					)
							snake_case_      =				logging.getLogger(snake_case					)
							if log_level is not None:
														logger.setLevel(log_level.upper()					)
														logger.root.setLevel(log_level.upper()					)
							return MultiProcessAdapter(snake_case							,    {}					)




