





import math

import tensorflow as tf
from packaging import version



def 				lowerCAmelCase_ (							A_):
    UpperCamelCase__:	int					=     tf.convert_to_tensor(A_)
    UpperCamelCase__:	int					=     0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sqrt(2.0)    ,x.dtype)))

    return x * cdf



def 				lowerCAmelCase_ (							A_):
    UpperCamelCase__:	Union[str, Any]					=     tf.convert_to_tensor(A_)
    UpperCamelCase__:	List[Any]					=     tf.cast(math.pi    ,x.dtype)
    UpperCamelCase__:	List[Any]					=     tf.cast(0.04_4715    ,x.dtype)
    UpperCamelCase__:	List[str]					=     0.5 * (1.0 + tf.tanh(tf.sqrt(2.0 / pi) * (x + coeff * tf.pow(A_    ,3))))

    return x * cdf



def 				lowerCAmelCase_ (							A_):
    UpperCamelCase__:	Union[str, Any]					=     tf.convert_to_tensor(A_)

    return x * tf.tanh(tf.math.softplus(A_))



def 				lowerCAmelCase_ (							A_):
    UpperCamelCase__:	Dict					=     tf.convert_to_tensor(A_)
    UpperCamelCase__:	Optional[Any]					=     tf.cast(0.04_4715    ,x.dtype)
    UpperCamelCase__:	Optional[Any]					=     tf.cast(0.79_7884_5608    ,x.dtype)

    return 0.5 * x * (1.0 + tf.tanh(x * coeffa * (1.0 + coeffa * x * x)))



def 				lowerCAmelCase_ (							A_):
    UpperCamelCase__:	str					=     tf.convert_to_tensor(A_)
    UpperCamelCase__:	str					=     tf.cast(1.702    ,x.dtype)
    return x * tf.math.sigmoid(coeff * x)



def 				lowerCAmelCase_ (							A_):
    return tf.clip_by_value(_gelu(A_)    ,-10    ,10)



def 				lowerCAmelCase_ (							A_    ,A_=-1):
    UpperCamelCase__				, UpperCamelCase__:	str					=     tf.split(A_    ,2    ,axis=A_)
    return a * tf.math.sigmoid(A_)


if version.parse(tf.version.VERSION) >= version.parse('''2.4'''):



   def 				lowerCAmelCase_ (							A_):
       return tf.keras.activations.gelu(A_    ,approximate=A_)

   A__:    Tuple  	=	tf.keras.activations.gelu




   A__:    int  	=	approximate_gelu_wrap
else:
   A__:    Optional[Any]  	=	_gelu
   A__:    str  	=	_gelu_new


A__:    Union[str, Any]  	=	{
    '''gelu''': gelu,
    '''gelu_10''': gelu_aa,
    '''gelu_fast''': gelu_fast,
    '''gelu_new''': gelu_new,
    '''glu''': glu,
    '''mish''': mish,
    '''quick_gelu''': quick_gelu,
    '''relu''': tf.keras.activations.relu,
    '''sigmoid''': tf.keras.activations.sigmoid,
    '''silu''': tf.keras.activations.swish,
    '''swish''': tf.keras.activations.swish,
    '''tanh''': tf.keras.activations.tanh,
}




def 				lowerCAmelCase_ (							A_):
    if activation_string in ACTaFN:
        return ACTaFN[activation_string]
    else:
        raise KeyError(F"function {activation_string} not found in ACT2FN mapping {list(ACTaFN.keys())}")








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


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

A__:    int  	=	{'''vocab_file''': '''sentencepiece.model'''}

A__:    Dict  	=	{
    '''vocab_file''': {
        '''google/rembert''': '''https://huggingface.co/google/rembert/resolve/main/sentencepiece.model''',
    },
}

A__:    Any  	=	{
    '''google/rembert''': 256,
}




class        _a    (    UpperCamelCase__):

      """simple docstring"""


      UpperCamelCase__  		=       VOCAB_FILES_NAMES
      UpperCamelCase__  		=       PRETRAINED_VOCAB_FILES_MAP
      UpperCamelCase__  		=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES






      def __init__(		self:			str	,    __lowerCamelCase:			Optional[Any]	,    __lowerCamelCase:			List[str]=False	,    __lowerCamelCase:			Optional[Any]=True	,    __lowerCamelCase:			Dict=True	,    __lowerCamelCase:			Tuple="[CLS]"	,    __lowerCamelCase:			List[str]="[SEP]"	,    __lowerCamelCase:			List[str]="[UNK]"	,    __lowerCamelCase:			Union[str, Any]="[SEP]"	,    __lowerCamelCase:			List[Any]="[PAD]"	,    __lowerCamelCase:			Optional[int]="[CLS]"	,    __lowerCamelCase:			str="[MASK]"	,    **__lowerCamelCase:			Union[str, Any]	,    ):
          '''simple docstring'''


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

          UpperCamelCase__:	Optional[int]					=     do_lower_case
          UpperCamelCase__:	Optional[int]					=     remove_space
          UpperCamelCase__:	str					=     keep_accents
          UpperCamelCase__:	Union[str, Any]					=     vocab_file

          UpperCamelCase__:	Any					=     spm.SentencePieceProcessor()
          self.sp_model.Load(__lowerCamelCase					)






      @property
      def 			UpperCAmelCase_       (		self:			Any					):
          '''simple docstring'''


          return len(self.sp_model					)






      def 			UpperCAmelCase_       (		self:			Optional[Any]					):
          '''simple docstring'''


          UpperCamelCase__:	List[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:			Optional[int]					):
          '''simple docstring'''


          UpperCamelCase__:	Any					=     self.__dict__.copy()
          UpperCamelCase__:	str					=     None
          return state






      def __setstate__(		self:			Optional[int]	,    __lowerCamelCase:			Union[str, Any]					):
          '''simple docstring'''


          UpperCamelCase__:	int					=     d
          UpperCamelCase__:	List[Any]					=     spm.SentencePieceProcessor()
          self.sp_model.Load(self.vocab_file					)






      def 			UpperCAmelCase_       (		self:			Tuple	,    __lowerCamelCase:			str	,    __lowerCamelCase:			Optional[Any]=False					):
          '''simple docstring'''


          UpperCamelCase__:	Union[str, Any]					=     self.sp_model.EncodeAsPieces(__lowerCamelCase					)
          return pieces






      def 			UpperCAmelCase_       (		self:			Tuple	,    __lowerCamelCase:			Union[str, Any]					):
          '''simple docstring'''


          return self.sp_model.PieceToId(__lowerCamelCase					)






      def 			UpperCAmelCase_       (		self:			Tuple	,    __lowerCamelCase:			Optional[int]					):
          '''simple docstring'''


          return self.sp_model.IdToPiece(__lowerCamelCase					)






      def 			UpperCAmelCase_       (		self:			Optional[Any]	,    __lowerCamelCase:			Any					):
          '''simple docstring'''


          UpperCamelCase__:	Optional[Any]					=     self.sp_model.decode_pieces(__lowerCamelCase					)
          return out_string






      def 			UpperCAmelCase_       (		self:			Any	,    __lowerCamelCase:			List[int]	,    __lowerCamelCase:			Optional[List[int]] = None					):
          '''simple docstring'''


          UpperCamelCase__:	int					=     [self.sep_token_id]
          UpperCamelCase__:	int					=     [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 			UpperCAmelCase_       (		self:			List[str]	,    __lowerCamelCase:			List[int]	,    __lowerCamelCase:			Optional[List[int]] = None	,    __lowerCamelCase:			bool = False					):
          '''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(__lowerCamelCase					)) + [1] + ([0] * len(__lowerCamelCase					)) + [1]
          return [1] + ([0] * len(__lowerCamelCase					)) + [1]






      def 			UpperCAmelCase_       (		self:			Any	,    __lowerCamelCase:			List[int]	,    __lowerCamelCase:			Optional[List[int]] = None					):
          '''simple docstring'''


          UpperCamelCase__:	Dict					=     [self.sep_token_id]
          UpperCamelCase__:	Dict					=     [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 			UpperCAmelCase_       (		self:			Optional[Any]	,    __lowerCamelCase:			str	,    __lowerCamelCase:			Optional[str] = None					):
          '''simple docstring'''


          if not os.path.isdir(__lowerCamelCase					):
              logger.error("Vocabulary path ({}) should be a directory".format(__lowerCamelCase					)					)
              return
          UpperCamelCase__:	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					):
              copyfile(self.vocab_file	,    __lowerCamelCase					)

          return (out_vocab_file,)

