"""simple docstring"""






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

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
       from .tokenization_rembert import RemBertTokenizer
else:
       __A			   = None

__A			   = logging.get_logger(__name__)
__A			   = {'vocab_file': 'sentencepiece.model', 'tokenizer_file': 'tokenizer.json'}

__A			   = {
    'vocab_file': {
        'google/rembert': 'https://huggingface.co/google/rembert/resolve/main/sentencepiece.model',
    },
    'tokenizer_file': {
        'google/rembert': 'https://huggingface.co/google/rembert/resolve/main/tokenizer.json',
    },
}

__A			   = {
    'google/rembert': 2_5_6,
}

__A			   = '▁'


class     UpperCAmelCase						(_UpperCAmelCase  ):



    """simple docstring"""

    _UpperCAmelCase	:Optional[Any]						    = VOCAB_FILES_NAMES
    _UpperCAmelCase	:Optional[int]						    = PRETRAINED_VOCAB_FILES_MAP
    _UpperCAmelCase	:Any						    = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    _UpperCAmelCase	:Tuple						    = RemBertTokenizer






    def __init__(   self    ,			_UpperCAmelCase=None    ,			_UpperCAmelCase=None    ,			_UpperCAmelCase=True    ,			_UpperCAmelCase=True    ,			_UpperCAmelCase=False    ,			_UpperCAmelCase="[CLS]"    ,			_UpperCAmelCase="[SEP]"    ,			_UpperCAmelCase="<unk>"    ,			_UpperCAmelCase="[SEP]"    ,			_UpperCAmelCase="<pad>"    ,			_UpperCAmelCase="[CLS]"    ,			_UpperCAmelCase="[MASK]"    ,			**_UpperCAmelCase    ,			):
       lowercase__:   Dict					=      AddedToken(__SCREAMING_SNAKE_CASE    ,			lstrip=__SCREAMING_SNAKE_CASE    ,			rstrip=__SCREAMING_SNAKE_CASE							) if isinstance(__SCREAMING_SNAKE_CASE    ,			__SCREAMING_SNAKE_CASE							) else mask_token

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

       lowercase__:   Dict					=      do_lower_case
       lowercase__:   Optional[int]					=      remove_space
       lowercase__:   str					=      keep_accents
       lowercase__:   str					=      vocab_file
       lowercase__:   Tuple					=      False if not self.vocab_file else True






    def _snake_case			(   self    ,			_UpperCAmelCase    ,			_UpperCAmelCase = None							):
       lowercase__:   List[str]					=      [self.sep_token_id]
       lowercase__:   List[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 _snake_case			(   self    ,			_UpperCAmelCase    ,			_UpperCAmelCase = None    ,			_UpperCAmelCase = 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(__SCREAMING_SNAKE_CASE							)) + [1] + ([0] * len(__SCREAMING_SNAKE_CASE							)) + [1]
       return [1] + ([0] * len(__SCREAMING_SNAKE_CASE							)) + [1]






    def _snake_case			(   self    ,			_UpperCAmelCase    ,			_UpperCAmelCase = None							):
       lowercase__:   List[str]					=      [self.sep_token_id]
       lowercase__:   List[Any]					=      [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 _snake_case			(   self    ,			_UpperCAmelCase    ,			_UpperCAmelCase = None							):




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

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

       return (out_vocab_file,)



'''simple docstring'''



from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


UpperCAmelCase :       Optional[int]			   =     logging.get_logger(__name__)

UpperCAmelCase :       str			   =     {
    'facebook/convnextv2-tiny-1k-224': 'https://huggingface.co/facebook/convnextv2-tiny-1k-224/resolve/main/config.json',
}







class 						lowerCAmelCase__   (      a ,					a					):



 """simple docstring"""



 lowerCAmelCase__  					=      "convnextv2"
 def __init__(		self					:       Any					,							__SCREAMING_SNAKE_CASE					:       int=3					,							__SCREAMING_SNAKE_CASE					:       Dict=4					,							__SCREAMING_SNAKE_CASE					:       List[Any]=4					,							__SCREAMING_SNAKE_CASE					:       Optional[int]=None					,							__SCREAMING_SNAKE_CASE					:       Dict=None					,							__SCREAMING_SNAKE_CASE					:       Optional[int]="gelu"					,							__SCREAMING_SNAKE_CASE					:       Union[str, Any]=0.02					,							__SCREAMING_SNAKE_CASE					:       Dict=1E-12					,							__SCREAMING_SNAKE_CASE					:       List[str]=0.0					,							__SCREAMING_SNAKE_CASE					:       Optional[Any]=224					,							__SCREAMING_SNAKE_CASE					:       Tuple=None					,							__SCREAMING_SNAKE_CASE					:       List[str]=None					,							**__SCREAMING_SNAKE_CASE					:       Union[str, Any]					,							)  -> Union[str, Any]:


      """simple docstring"""




      super().__init__(**__SCREAMING_SNAKE_CASE			)

      __SCREAMING_SNAKE_CASE     =      num_channels
      __SCREAMING_SNAKE_CASE     =      patch_size
      __SCREAMING_SNAKE_CASE     =      num_stages
      __SCREAMING_SNAKE_CASE     =      [96, 192, 384, 768] if hidden_sizes is None else hidden_sizes
      __SCREAMING_SNAKE_CASE     =      [3, 3, 9, 3] if depths is None else depths
      __SCREAMING_SNAKE_CASE     =      hidden_act
      __SCREAMING_SNAKE_CASE     =      initializer_range
      __SCREAMING_SNAKE_CASE     =      layer_norm_eps
      __SCREAMING_SNAKE_CASE     =      drop_path_rate
      __SCREAMING_SNAKE_CASE     =      image_size
      __SCREAMING_SNAKE_CASE     =      ["""stem"""] + [f'stage{idx}' for idx in range(1					,							len(self.depths			) + 1			)]
      __SCREAMING_SNAKE_CASE   ,			__SCREAMING_SNAKE_CASE     =      get_aligned_output_features_output_indices(
          out_features=__SCREAMING_SNAKE_CASE					,							out_indices=__SCREAMING_SNAKE_CASE					,							stage_names=self.stage_names			)






