

import collections
import os
from typing import List, Optional, Tuple

from transformers.utils import is_jieba_available, requires_backends


if is_jieba_available():
    import jieba

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


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

lowerCAmelCase   :      Optional[int]     =     {"vocab_file": "vocab.txt"}

lowerCAmelCase   :      Dict     =     {
    "vocab_file": {
        "openbmb/cpm-ant-10b": "https://huggingface.co/openbmb/cpm-ant-10b/blob/main/vocab.txt",
    },
}

lowerCAmelCase   :      int     =     {
    "openbmb/cpm-ant-10b": 10_24,
}

def       A_     (							a     ):

      """simple docstring"""



      SCREAMING_SNAKE_CASE_ :     Optional[int]							=   collections.OrderedDict()
      with open(_UpperCamelCase    ,      'r'    ,      encoding='utf-8'     ) as reader:
            SCREAMING_SNAKE_CASE_ :     Optional[Any]							=   reader.readlines()
      for index, token in enumerate(_UpperCamelCase     ):
            SCREAMING_SNAKE_CASE_ :     List[Any]							=   token.rstrip('\n'     )
            SCREAMING_SNAKE_CASE_ :     List[str]							=   index
      return vocab
class        _A						(     A__):

  def __init__( self       ,    _SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE="<unk>"       ,    _SCREAMING_SNAKE_CASE=200    ):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_ :     Any							=   vocab
        SCREAMING_SNAKE_CASE_ :     List[str]							=   unk_token
        SCREAMING_SNAKE_CASE_ :     Union[str, Any]							=   max_input_chars_per_word



  def        UpperCAmelCase			( self       ,    _SCREAMING_SNAKE_CASE    ):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_ :     Tuple							=   list(_a    )
        if len(_a    ) > self.max_input_chars_per_word:
              return [self.unk_token]

        SCREAMING_SNAKE_CASE_ :     Tuple							=   0
        SCREAMING_SNAKE_CASE_ :     Dict							=   []
        while start < len(_a    ):
              SCREAMING_SNAKE_CASE_ :     Tuple							=   len(_a    )
              SCREAMING_SNAKE_CASE_ :     Dict							=   None
              while start < end:
                    SCREAMING_SNAKE_CASE_ :     List[Any]							=   ''.join(chars[start:end]    )
                    if substr in self.vocab:
                          SCREAMING_SNAKE_CASE_ :     int							=   substr
                          break
                    end -= 1
              if cur_substr is None:
                    sub_tokens.append(self.unk_token    )
                    start += 1
              else:
                    sub_tokens.append(_a    )
                    SCREAMING_SNAKE_CASE_ :     Optional[Any]							=   end

        return sub_tokens

class        _A						(     A__):
  SCREAMING_SNAKE_CASE			:					Any				=     VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE			:					Optional[Any]				=     PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE			:					List[Any]				=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE			:					Optional[int]				=     ['''input_ids''', '''attention_mask''']
  SCREAMING_SNAKE_CASE			:					Dict				=     False

  def __init__( self       ,    _SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE="<d>"       ,    _SCREAMING_SNAKE_CASE="</d>"       ,    _SCREAMING_SNAKE_CASE="<s>"       ,    _SCREAMING_SNAKE_CASE="</s>"       ,    _SCREAMING_SNAKE_CASE="<pad>"       ,    _SCREAMING_SNAKE_CASE="<unk>"       ,    _SCREAMING_SNAKE_CASE="</n>"       ,    _SCREAMING_SNAKE_CASE="</_>"       ,    _SCREAMING_SNAKE_CASE="left"       ,    **_SCREAMING_SNAKE_CASE       ,    ):





        """simple docstring"""







        requires_backends(self       ,    ['jieba']    )
        super().__init__(
            bod_token=_a       ,    eod_token=_a       ,    bos_token=_a       ,    eos_token=_a       ,    pad_token=_a       ,    unk_token=_a       ,    line_token=_a       ,    space_token=_a       ,    padding_side=_a       ,    **_a       ,    )
        SCREAMING_SNAKE_CASE_ :     Union[str, Any]							=   bod_token
        SCREAMING_SNAKE_CASE_ :     Optional[Any]							=   eod_token
        SCREAMING_SNAKE_CASE_ :     List[Any]							=   load_vocab(_a    )
        SCREAMING_SNAKE_CASE_ :     List[Any]							=   self.encoder[space_token]
        SCREAMING_SNAKE_CASE_ :     Optional[Any]							=   self.encoder[line_token]

        del self.encoder[space_token]
        del self.encoder[line_token]

        SCREAMING_SNAKE_CASE_ :     Any							=   collections.OrderedDict(sorted(self.encoder.items()       ,    key=lambda _SCREAMING_SNAKE_CASE    : x[1]    )    )
        SCREAMING_SNAKE_CASE_ :     Union[str, Any]							=   {v: k for k, v in self.encoder.items()}

        SCREAMING_SNAKE_CASE_ :     str							=   WordpieceTokenizer(vocab=self.encoder       ,    unk_token=self.unk_token    )

  @property
  def        UpperCAmelCase			( self    ):





        """simple docstring"""







        return self.encoder[self.bod_token]

  @property
  def        UpperCAmelCase			( self    ):





        """simple docstring"""







        return self.encoder[self.eod_token]

  @property
  def        UpperCAmelCase			( self    ):





        """simple docstring"""







        return self.encoder["\n"]

  @property
  def        UpperCAmelCase			( self    ):





        """simple docstring"""







        return len(self.encoder    )

  def        UpperCAmelCase			( self    ):





        """simple docstring"""







        return dict(self.encoder       ,    **self.added_tokens_encoder    )

  def        UpperCAmelCase			( self       ,    _SCREAMING_SNAKE_CASE    ):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_ :     Tuple							=   []
        for x in jieba.cut(_a       ,    cut_all=_a    ):
              output_tokens.extend(self.wordpiece_tokenizer.tokenize(_a    )    )
        return output_tokens

  def        UpperCAmelCase			( self       ,    _SCREAMING_SNAKE_CASE       ,    **_SCREAMING_SNAKE_CASE    ):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_ :     Dict							=   [i for i in token_ids if i >= 0]
        SCREAMING_SNAKE_CASE_ :     List[str]							=   [
            x for x in token_ids if x != self.pad_token_id and x != self.eos_token_id and x != self.bos_token_id
        ]
        return super()._decode(_a       ,    **_a    )

  def        UpperCAmelCase			( self       ,    _SCREAMING_SNAKE_CASE    ):





        """simple docstring"""







        return token in self.encoder

  def        UpperCAmelCase			( self       ,    _SCREAMING_SNAKE_CASE    ):





        """simple docstring"""







        return "".join(_a    )

  def        UpperCAmelCase			( self       ,    _SCREAMING_SNAKE_CASE    ):





        """simple docstring"""







        return self.encoder.get(_a       ,    self.encoder.get(self.unk_token    )    )

  def        UpperCAmelCase			( self       ,    _SCREAMING_SNAKE_CASE    ):





        """simple docstring"""







        return self.decoder.get(_a       ,    self.unk_token    )

  def        UpperCAmelCase			( self       ,    _SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE = None    ):





        """simple docstring"""







        if os.path.isdir(_a    ):
              SCREAMING_SNAKE_CASE_ :     Optional[int]							=   os.path.join(
                  _a       ,    (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']    )
        else:
              SCREAMING_SNAKE_CASE_ :     Tuple							=   (filename_prefix + '-' if filename_prefix else '') + save_directory
        SCREAMING_SNAKE_CASE_ :     Optional[Any]							=   0
        if " " in self.encoder:
              SCREAMING_SNAKE_CASE_ :     Tuple							=   self.encoder[' ']
              del self.encoder[" "]
        if "\n" in self.encoder:
              SCREAMING_SNAKE_CASE_ :     str							=   self.encoder['\n']
              del self.encoder["\n"]
        SCREAMING_SNAKE_CASE_ :     Tuple							=   collections.OrderedDict(sorted(self.encoder.items()       ,    key=lambda _SCREAMING_SNAKE_CASE    : x[1]    )    )
        with open(_a       ,    'w'       ,    encoding='utf-8'    ) as writer:
              for token, token_index in self.encoder.items():
                    if index != token_index:
                          logger.warning(
                              f"Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive."
                              ' Please check that the vocabulary is not corrupted!'    )
                          SCREAMING_SNAKE_CASE_ :     List[str]							=   token_index
                    writer.write(token + '\n'    )
                    index += 1
        return (vocab_file,)

  def        UpperCAmelCase			( self       ,    _SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE = None    ):





        """simple docstring"""







        if token_ids_a is None:
              return [self.bos_token_id] + token_ids_a
        return [self.bos_token_id] + token_ids_a + [self.bos_token_id] + token_ids_a



  def        UpperCAmelCase			( self       ,    _SCREAMING_SNAKE_CASE       ,    _SCREAMING_SNAKE_CASE = None       ,    _SCREAMING_SNAKE_CASE = False    ):





        """simple docstring"""







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

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









'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


lowerCamelCase :      List[str]					 =     logging.get_logger(__name__)

lowerCamelCase :      List[Any]					 =     {
    "facebook/convnextv2-tiny-1k-224": "https://huggingface.co/facebook/convnextv2-tiny-1k-224/resolve/main/config.json",
}







class 							A__    (       A__     ,   A__  ):
  A__		 =				'convnextv2'





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





       '''simple docstring'''






       super().__init__(**_a )

       _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=_a							,					out_indices=_a							,					stage_names=self.stage_names )
