


"""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


snake_case__		:     Optional[Any]    				=				logging.get_logger(__name__)

snake_case__		:     List[str]    				=				{'''vocab_file''': '''sentencepiece.model'''}

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

snake_case__		:     Tuple    				=				{
    '''google/rembert''': 256,
}



class 		snake_case_(       a__			):
     __UpperCamelCase  =					VOCAB_FILES_NAMES
     __UpperCamelCase  =					PRETRAINED_VOCAB_FILES_MAP
     __UpperCamelCase  =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES






     def __init__(	self  :					Tuple					,				UpperCamelCase_  :					List[str]					,				UpperCamelCase_  :					str=False					,				UpperCamelCase_  :					Tuple=True					,				UpperCamelCase_  :					Optional[Any]=True					,				UpperCamelCase_  :					Tuple="[CLS]"					,				UpperCamelCase_  :					Any="[SEP]"					,				UpperCamelCase_  :					Union[str, Any]="[UNK]"					,				UpperCamelCase_  :					Union[str, Any]="[SEP]"					,				UpperCamelCase_  :					Optional[int]="[PAD]"					,				UpperCamelCase_  :					Tuple="[CLS]"					,				UpperCamelCase_  :					Optional[int]="[MASK]"					,				**UpperCamelCase_  :					Union[str, Any]					,				):
           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_					,				)

           lowerCAmelCase					:	Dict       =   do_lower_case
           lowerCAmelCase					:	List[Any]       =   remove_space
           lowerCAmelCase					:	Any       =   keep_accents
           lowerCAmelCase					:	Optional[Any]       =   vocab_file

           lowerCAmelCase					:	Dict       =   spm.SentencePieceProcessor()
           self.sp_model.Load(UpperCamelCase_				)






     @property
     def      lowerCamelCase__     (	self  :					Tuple				):
           return len(self.sp_model				)






     def      lowerCamelCase__     (	self  :					Union[str, Any]				):
           lowerCAmelCase					:	Any       =   {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  :					int				):
           lowerCAmelCase					:	Optional[Any]       =   self.__dict__.copy()
           lowerCAmelCase					:	Optional[Any]       =   None
           return state






     def __setstate__(	self  :					List[str]					,				UpperCamelCase_  :					List[Any]				):
           lowerCAmelCase					:	List[str]       =   d
           lowerCAmelCase					:	Optional[int]       =   spm.SentencePieceProcessor()
           self.sp_model.Load(self.vocab_file				)






     def      lowerCamelCase__     (	self  :					Optional[int]					,				UpperCamelCase_  :					Optional[int]					,				UpperCamelCase_  :					int=False				):
           lowerCAmelCase					:	List[str]       =   self.sp_model.EncodeAsPieces(UpperCamelCase_				)
           return pieces






     def      lowerCamelCase__     (	self  :					Optional[int]					,				UpperCamelCase_  :					Dict				):
           return self.sp_model.PieceToId(UpperCamelCase_				)






     def      lowerCamelCase__     (	self  :					Tuple					,				UpperCamelCase_  :					Dict				):
           return self.sp_model.IdToPiece(UpperCamelCase_				)






     def      lowerCamelCase__     (	self  :					List[Any]					,				UpperCamelCase_  :					Optional[Any]				):
           lowerCAmelCase					:	int       =   self.sp_model.decode_pieces(UpperCamelCase_				)
           return out_string






     def      lowerCamelCase__     (	self  :					Tuple					,				UpperCamelCase_  :					List[int]					,				UpperCamelCase_  :					Optional[List[int]] = None				):
           lowerCAmelCase					:	List[Any]       =   [self.sep_token_id]
           lowerCAmelCase					:	Union[str, Any]       =   [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  :					str					,				UpperCamelCase_  :					List[int]					,				UpperCamelCase_  :					Optional[List[int]] = None					,				UpperCamelCase_  :					bool = False				):

           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  :					Dict					,				UpperCamelCase_  :					List[int]					,				UpperCamelCase_  :					Optional[List[int]] = None				):
           lowerCAmelCase					:	Union[str, Any]       =   [self.sep_token_id]
           lowerCAmelCase					:	List[str]       =   [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  :					Any					,				UpperCamelCase_  :					str					,				UpperCamelCase_  :					Optional[str] = None				):
           if not os.path.isdir(UpperCamelCase_				):
                 logger.error('''Vocabulary path ({}) should be a directory'''.format(UpperCamelCase_				)				)
                 return
           lowerCAmelCase					:	List[Any]       =   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"""





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


snake_case__		:     Tuple    				=				logging.get_logger(__name__)

snake_case__		:     int    				=				{
    '''facebook/levit-128S''': '''https://huggingface.co/facebook/levit-128S/resolve/main/config.json''',
    # See all LeViT models at https://huggingface.co/models?filter=levit
}



class 		snake_case_(       a__			):
     __UpperCamelCase  =					'''levit'''






     def __init__(	self  :					str					,				UpperCamelCase_  :					Union[str, Any]=2_2_4					,				UpperCamelCase_  :					Union[str, Any]=3					,				UpperCamelCase_  :					Union[str, Any]=3					,				UpperCamelCase_  :					int=2					,				UpperCamelCase_  :					Union[str, Any]=1					,				UpperCamelCase_  :					Tuple=1_6					,				UpperCamelCase_  :					Dict=[1_2_8, 2_5_6, 3_8_4]					,				UpperCamelCase_  :					Optional[Any]=[4, 8, 1_2]					,				UpperCamelCase_  :					Dict=[4, 4, 4]					,				UpperCamelCase_  :					Any=[1_6, 1_6, 1_6]					,				UpperCamelCase_  :					str=0					,				UpperCamelCase_  :					int=[2, 2, 2]					,				UpperCamelCase_  :					Optional[Any]=[2, 2, 2]					,				UpperCamelCase_  :					str=0.02					,				**UpperCamelCase_  :					List[str]					,				):
           super().__init__(**UpperCamelCase_				)
           lowerCAmelCase					:	Tuple       =   image_size
           lowerCAmelCase					:	int       =   num_channels
           lowerCAmelCase					:	Optional[int]       =   kernel_size
           lowerCAmelCase					:	Dict       =   stride
           lowerCAmelCase					:	List[Any]       =   padding
           lowerCAmelCase					:	Dict       =   hidden_sizes
           lowerCAmelCase					:	List[str]       =   num_attention_heads
           lowerCAmelCase					:	Tuple       =   depths
           lowerCAmelCase					:	Dict       =   key_dim
           lowerCAmelCase					:	Union[str, Any]       =   drop_path_rate
           lowerCAmelCase					:	List[Any]       =   patch_size
           lowerCAmelCase					:	Tuple       =   attention_ratio
           lowerCAmelCase					:	Optional[int]       =   mlp_ratio
           lowerCAmelCase					:	Union[str, Any]       =   initializer_range
           lowerCAmelCase					:	List[str]       =   [
               ['''Subsample''', key_dim[0], hidden_sizes[0] // key_dim[0], 4, 2, 2],
               ['''Subsample''', key_dim[0], hidden_sizes[1] // key_dim[0], 4, 2, 2],
           ]



class 		snake_case_(       a__			):
     __UpperCamelCase  =					version.parse('''1.11'''			)






     @property
     def      lowerCamelCase__     (	self  :					Tuple				):
           return OrderedDict(
               [
                   ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
               ]				)






     @property
     def      lowerCamelCase__     (	self  :					Optional[Any]				):
           return 1E-4


