






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


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

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

a						:			List[Any]     	=					{
    "vocab_file": {
        "camembert-base": "https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model",
    }
}

a						:			Any     	=					{
    "camembert-base": 512,
}

a						:			int     	=					"▁"
class        a       (					lowercase__  ):



      """simple docstring"""


      a    :					Tuple							=      VOCAB_FILES_NAMES
      a    :					Optional[int]							=      PRETRAINED_VOCAB_FILES_MAP
      a    :					Optional[int]							=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      a    :					List[str]							=      ['input_ids', 'attention_mask']
      def __init__( self   :     Any						, __lowercase   :     Any						, __lowercase   :     List[str]="<s>"						, __lowercase   :     List[Any]="</s>"						, __lowercase   :     Optional[Any]="</s>"						, __lowercase   :     List[str]="<s>"						, __lowercase   :     List[Any]="<unk>"						, __lowercase   :     Union[str, Any]="<pad>"						, __lowercase   :     Any="<mask>"						, __lowercase   :     Dict=["<s>NOTUSED", "</s>NOTUSED"]						, __lowercase   :     List[str] = None						, **__lowercase   :     Union[str, Any]						, )				-> Any:
        __UpperCAmelCase				:      List[Any]	 =    AddedToken(__lowercase						, lstrip=__lowercase						, rstrip=__lowercase   ) if isinstance(__lowercase						, __lowercase   ) else mask_token

        __UpperCAmelCase				:      Union[str, Any]	 =    {} if sp_model_kwargs is None else sp_model_kwargs

        super().__init__(
            bos_token=__lowercase						, eos_token=__lowercase						, unk_token=__lowercase						, sep_token=__lowercase						, cls_token=__lowercase						, pad_token=__lowercase						, mask_token=__lowercase						, additional_special_tokens=__lowercase						, sp_model_kwargs=self.sp_model_kwargs						, **__lowercase						, )
        __UpperCAmelCase				:      List[Any]	 =    spm.SentencePieceProcessor(**self.sp_model_kwargs   )
        self.sp_model.Load(str(__lowercase   )   )
        __UpperCAmelCase				:      List[str]	 =    vocab_file
        # HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
        # sentencepiece vocabulary (this is the case for <s> and </s>
        __UpperCAmelCase				:      Optional[Any]	 =    {"<s>NOTUSED": 0, "<pad>": 1, "</s>NOTUSED": 2, "<unk>": 3}
        __UpperCAmelCase				:      List[str]	 =    len(self.fairseq_tokens_to_ids   )
        __UpperCAmelCase				:      Optional[Any]	 =    len(self.sp_model   ) + len(self.fairseq_tokens_to_ids   )
        __UpperCAmelCase				:      str	 =    {v: k for k, v in self.fairseq_tokens_to_ids.items()}
      def       UpperCAmelCase ( self   :     Tuple						, __lowercase   :     Tuple						, __lowercase   :     int = None   )				-> List[Any]:





        if token_ids_a is None:
          return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
        __UpperCAmelCase				:      Union[str, Any]	 =    [self.cls_token_id]
        __UpperCAmelCase				:      Union[str, Any]	 =    [self.sep_token_id]
        return cls + token_ids_a + sep + sep + token_ids_a + sep
      def       UpperCAmelCase ( self   :     Dict						, __lowercase   :     Optional[Any]						, __lowercase   :     Union[str, Any] = None						, __lowercase   :     str = False   )				-> List[str]:





        if already_has_special_tokens:
          return super().get_special_tokens_mask(
              token_ids_a=__lowercase						, token_ids_a=__lowercase						, already_has_special_tokens=__lowercase   )

        if token_ids_a is None:
          return [1] + ([0] * len(__lowercase   )) + [1]
        return [1] + ([0] * len(__lowercase   )) + [1, 1] + ([0] * len(__lowercase   )) + [1]
      def       UpperCAmelCase ( self   :     Optional[int]						, __lowercase   :     List[Any]						, __lowercase   :     int = None   )				-> str:
        __UpperCAmelCase				:      List[str]	 =    [self.sep_token_id]
        __UpperCAmelCase				:      Tuple	 =    [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       UpperCAmelCase ( self   :     Optional[int]   )				-> Union[str, Any]:
        return len(self.fairseq_tokens_to_ids   ) + len(self.sp_model   )
      def       UpperCAmelCase ( self   :     Union[str, Any]   )				-> List[Any]:
        __UpperCAmelCase				:      Tuple	 =    {self.convert_ids_to_tokens(__lowercase   ): i for i in range(self.vocab_size   )}
        vocab.update(self.added_tokens_encoder   )
        return vocab
      def       UpperCAmelCase ( self   :     Union[str, Any]						, __lowercase   :     Tuple   )				-> int:
        return self.sp_model.encode(__lowercase						, out_type=__lowercase   )
      def       UpperCAmelCase ( self   :     Optional[Any]						, __lowercase   :     Tuple   )				-> Tuple:





        if token in self.fairseq_tokens_to_ids:
          return self.fairseq_tokens_to_ids[token]
        elif self.sp_model.PieceToId(__lowercase   ) == 0:
          # Convert sentence piece unk token to fairseq unk token index
          return self.unk_token_id
        return self.fairseq_offset + self.sp_model.PieceToId(__lowercase   )
      def       UpperCAmelCase ( self   :     Any						, __lowercase   :     int   )				-> List[str]:





        if index in self.fairseq_ids_to_tokens:
          return self.fairseq_ids_to_tokens[index]
        return self.sp_model.IdToPiece(index - self.fairseq_offset   )
      def       UpperCAmelCase ( self   :     List[Any]						, __lowercase   :     Dict   )				-> List[Any]:
        __UpperCAmelCase				:      Union[str, Any]	 =    []
        __UpperCAmelCase				:      List[str]	 =    ""
        __UpperCAmelCase				:      Any	 =    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(__lowercase   ) + token
            __UpperCAmelCase				:      str	 =    True
            __UpperCAmelCase				:      Any	 =    []
          else:
            current_sub_tokens.append(__lowercase   )
            __UpperCAmelCase				:      Dict	 =    False
        out_string += self.sp_model.decode(__lowercase   )
        return out_string.strip()
      def __getstate__( self   :     List[str]   )				-> Optional[Any]:
        __UpperCAmelCase				:      str	 =    self.__dict__.copy()
        __UpperCAmelCase				:      Dict	 =    None
        return state
      def __setstate__( self   :     Union[str, Any]						, __lowercase   :     Union[str, Any]   )				-> Optional[Any]:
        __UpperCAmelCase				:      int	 =    d

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

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




      def       UpperCAmelCase ( self   :     Dict						, __lowercase   :     Dict						, __lowercase   :     int = None   )				-> Tuple:





        if not os.path.isdir(__lowercase   ):
          logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""   )
          return
        __UpperCAmelCase				:      List[str]	 =    os.path.join(
            __lowercase						, (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]   )

        if os.path.abspath(self.vocab_file   ) != os.path.abspath(__lowercase   ) and os.path.isfile(self.vocab_file   ):
          copyfile(self.vocab_file						, __lowercase   )
        elif not os.path.isfile(self.vocab_file   ):
          with open(__lowercase						, """wb"""   ) as fi:
            __UpperCAmelCase				:      str	 =    self.sp_model.serialized_model_proto()
            fi.write(__lowercase   )

        return (out_vocab_file,)






'''simple docstring'''


from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_UpperCamelCase 							=  logging.get_logger(__name__)

_UpperCamelCase 							=  {
    """microsoft/beit-base-patch16-224-pt22k""": (
        """https://huggingface.co/microsoft/beit-base-patch16-224-pt22k/resolve/main/config.json"""
    ),
    # See all BEiT models at https://huggingface.co/models?filter=beit
}







class 							__magic_name__	(       lowerCAmelCase ):

     """simple docstring"""






     lowerCamelCase__       						=				'beit'


     def __init__(   self			,     lowerCamelCase=8192			,     lowerCamelCase=768			,     lowerCamelCase=12			,     lowerCamelCase=12			,     lowerCamelCase=3072			,     lowerCamelCase="gelu"			,     lowerCamelCase=0.0			,     lowerCamelCase=0.0			,     lowerCamelCase=0.02			,     lowerCamelCase=1E-12			,     lowerCamelCase=224			,     lowerCamelCase=16			,     lowerCamelCase=3			,     lowerCamelCase=False			,     lowerCamelCase=False			,     lowerCamelCase=False			,     lowerCamelCase=False			,     lowerCamelCase=0.1			,     lowerCamelCase=0.1			,     lowerCamelCase=True			,     lowerCamelCase=[3, 5, 7, 11]			,     lowerCamelCase=[1, 2, 3, 6]			,     lowerCamelCase=True			,     lowerCamelCase=0.4			,     lowerCamelCase=256			,     lowerCamelCase=1			,     lowerCamelCase=False			,     lowerCamelCase=255			,     **lowerCamelCase			,     ):


          '''simple docstring'''





          super().__init__(**lowerCamelCase		)

          __A	:       int      =							vocab_size
          __A	:       Tuple      =							hidden_size
          __A	:       List[str]      =							num_hidden_layers
          __A	:       Optional[int]      =							num_attention_heads
          __A	:       Dict      =							intermediate_size
          __A	:       Optional[int]      =							hidden_act
          __A	:       str      =							hidden_dropout_prob
          __A	:       Dict      =							attention_probs_dropout_prob
          __A	:       int      =							initializer_range
          __A	:       List[str]      =							layer_norm_eps

          __A	:       str      =							image_size
          __A	:       Optional[int]      =							patch_size
          __A	:       List[Any]      =							num_channels
          __A	:       List[str]      =							use_mask_token
          __A	:       Union[str, Any]      =							use_absolute_position_embeddings
          __A	:       Optional[int]      =							use_relative_position_bias
          __A	:       int      =							use_shared_relative_position_bias
          __A	:       int      =							layer_scale_init_value
          __A	:       Union[str, Any]      =							drop_path_rate
          __A	:       Dict      =							use_mean_pooling
          # decode head attributes (semantic segmentation)
          __A	:       List[str]      =							out_indices
          __A	:       str      =							pool_scales
          # auxiliary head attributes (semantic segmentation)
          __A	:       List[str]      =							use_auxiliary_head
          __A	:       Tuple      =							auxiliary_loss_weight
          __A	:       Dict      =							auxiliary_channels
          __A	:       Tuple      =							auxiliary_num_convs
          __A	:       List[str]      =							auxiliary_concat_input
          __A	:       int      =							semantic_loss_ignore_index







class 							__magic_name__	(       lowerCAmelCase ):

     """simple docstring"""






     lowerCamelCase__       						=				version.parse('1.11' )


     @property
     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          return OrderedDict(
              [
                  ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
              ]		)


     @property
     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          return 1E-4

