import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_SCREAMING_SNAKE_CASE     =     logging.get_logger(__name__)


_SCREAMING_SNAKE_CASE     =     {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt'}

# See all MVP models at https://huggingface.co/models?filter=mvp
_SCREAMING_SNAKE_CASE     =     {
    'vocab_file': {
        'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json',
    },
    'added_tokens.json': {
        'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json',
    },
    'merges_file': {
        'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt',
    },
}

_SCREAMING_SNAKE_CASE     =     {
    'RUCAIBox/mvp': 1024,
}
@lru_cache()
def 					__lowercase						(    )					->Union[str, Any]:

  '''simple docstring'''




  a__  		=  (
      list(range(ord("!"       )			,					ord("~"       ) + 1       )       ) + list(range(ord("¡"       )			,					ord("¬"       ) + 1       )       ) + list(range(ord("®"       )			,					ord("ÿ"       ) + 1       )       )
  )
  a__  		=  bs[:]
  a__  		=  0
  for b in range(2**8       ):
    if b not in bs:
      bs.append(__lowercase       )
      cs.append(2**8 + n       )
      n += 1
  a__  		=  [chr(__lowercase       ) for n in cs]
  return dict(zip(__lowercase			,					__lowercase       )       )
def 					__lowercase						(    lowerCamelCase__       )					->Optional[Any]:

  '''simple docstring'''




  a__  		=  set()
  a__  		=  word[0]
  for char in word[1:]:
    pairs.add((prev_char, char)       )
    a__  		=  char
  return pairs







class        UpperCAmelCase_					(				_a     ):
    UpperCAmelCase_      :							List[str]    			=				VOCAB_FILES_NAMES
    UpperCAmelCase_      :							int    			=				PRETRAINED_VOCAB_FILES_MAP
    UpperCAmelCase_      :							Tuple    			=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    UpperCAmelCase_      :							Union[str, Any]    			=				['input_ids', 'attention_mask']




    def __init__(       self	: Any   ,   lowerCAmelCase	: List[str]   ,   lowerCAmelCase	: Union[str, Any]   ,   lowerCAmelCase	: List[str]="replace"   ,   lowerCAmelCase	: List[Any]="<s>"   ,   lowerCAmelCase	: Tuple="</s>"   ,   lowerCAmelCase	: Dict="</s>"   ,   lowerCAmelCase	: Any="<s>"   ,   lowerCAmelCase	: str="<unk>"   ,   lowerCAmelCase	: Dict="<pad>"   ,   lowerCAmelCase	: str="<mask>"   ,   lowerCAmelCase	: Tuple=False   ,   **lowerCAmelCase	: List[Any]   ,   )						->			Dict:
      a__  		=  AddedToken(_A   ,   lstrip=_A   ,   rstrip=_A ) if isinstance(_A   ,   _A ) else bos_token
      a__  		=  AddedToken(_A   ,   lstrip=_A   ,   rstrip=_A ) if isinstance(_A   ,   _A ) else eos_token
      a__  		=  AddedToken(_A   ,   lstrip=_A   ,   rstrip=_A ) if isinstance(_A   ,   _A ) else sep_token
      a__  		=  AddedToken(_A   ,   lstrip=_A   ,   rstrip=_A ) if isinstance(_A   ,   _A ) else cls_token
      a__  		=  AddedToken(_A   ,   lstrip=_A   ,   rstrip=_A ) if isinstance(_A   ,   _A ) else unk_token
      a__  		=  AddedToken(_A   ,   lstrip=_A   ,   rstrip=_A ) if isinstance(_A   ,   _A ) else pad_token

      # Mask token behave like a normal word, i.e. include the space before it
      a__  		=  AddedToken(_A   ,   lstrip=_A   ,   rstrip=_A ) if isinstance(_A   ,   _A ) else mask_token

      super().__init__(
          errors=_A   ,   bos_token=_A   ,   eos_token=_A   ,   unk_token=_A   ,   sep_token=_A   ,   cls_token=_A   ,   pad_token=_A   ,   mask_token=_A   ,   add_prefix_space=_A   ,   **_A   ,   )
      with open(_A   ,   encoding="utf-8" ) as vocab_handle:
        a__  		=  json.load(_A )
      a__  		=  {v: k for k, v in self.encoder.items()}
      a__  		=  errors  # how to handle errors in decoding
      a__  		=  bytes_to_unicode()
      a__  		=  {v: k for k, v in self.byte_encoder.items()}
      with open(_A   ,   encoding="utf-8" ) as merges_handle:
        a__  		=  merges_handle.read().split("\n" )[1:-1]
      a__  		=  [tuple(merge.split() ) for merge in bpe_merges]
      a__  		=  dict(zip(_A   ,   range(len(_A ) ) ) )
      a__  		=  {}
      a__  		=  add_prefix_space

      # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
      a__  		=  re.compile(r"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+" )




    @property
    def     __lowerCamelCase			(       self	: Optional[int] )						->			Dict:
      return len(self.encoder )




    def     __lowerCamelCase			(       self	: str )						->			Any:
      return dict(self.encoder   ,   **self.added_tokens_encoder )




    def     __lowerCamelCase			(       self	: Any   ,   lowerCAmelCase	: Optional[Any] )						->			Any:
      if token in self.cache:
        return self.cache[token]
      a__  		=  tuple(_A )
      a__  		=  get_pairs(_A )

      if not pairs:
        return token

      while True:
        a__  		=  min(_A   ,   key=lambda lowerCAmelCase : self.bpe_ranks.get(_A   ,   float("inf" ) ) )
        if bigram not in self.bpe_ranks:
          break
        a__  		=  bigram
        a__  		=  []
        a__  		=  0
        while i < len(_A ):
          try:
            a__  		=  word.index(_A   ,   _A )
          except ValueError:
            new_word.extend(word[i:] )
            break
          else:
            new_word.extend(word[i:j] )
            a__  		=  j

          if word[i] == first and i < len(_A ) - 1 and word[i + 1] == second:
            new_word.append(first + second )
            i += 2
          else:
            new_word.append(word[i] )
            i += 1
        a__  		=  tuple(_A )
        a__  		=  new_word
        if len(_A ) == 1:
          break
        else:
          a__  		=  get_pairs(_A )
      a__  		=  " ".join(_A )
      a__  		=  word
      return word




    def     __lowerCamelCase			(       self	: List[Any]   ,   lowerCAmelCase	: Optional[int] )						->			str:
      a__  		=  []
      for token in re.findall(self.pat   ,   _A ):
        a__  		=  "".join(
            self.byte_encoder[b] for b in token.encode("utf-8" ) )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
        bpe_tokens.extend(bpe_token for bpe_token in self.bpe(_A ).split(" " ) )
      return bpe_tokens




    def     __lowerCamelCase			(       self	: Optional[int]   ,   lowerCAmelCase	: int )						->			Optional[int]:
      return self.encoder.get(_A   ,   self.encoder.get(self.unk_token ) )




    def     __lowerCamelCase			(       self	: List[str]   ,   lowerCAmelCase	: List[str] )						->			List[Any]:
      return self.decoder.get(_A )




    def     __lowerCamelCase			(       self	: Tuple   ,   lowerCAmelCase	: Tuple )						->			List[str]:
      a__  		=  "".join(_A )
      a__  		=  bytearray([self.byte_decoder[c] for c in text] ).decode("utf-8"   ,   errors=self.errors )
      return text




    def     __lowerCamelCase			(       self	: Tuple   ,   lowerCAmelCase	: str   ,   lowerCAmelCase	: Optional[str] = None )						->			List[Any]:
      if not os.path.isdir(_A ):
        logger.error(f"Vocabulary path ({save_directory}) should be a directory" )
        return
      a__  		=  os.path.join(
          _A   ,   (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"] )
      a__  		=  os.path.join(
          _A   ,   (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"] )

      with open(_A   ,   "w"   ,   encoding="utf-8" ) as f:
        f.write(json.dumps(self.encoder   ,   indent=2   ,   sort_keys=_A   ,   ensure_ascii=_A ) + "\n" )

      a__  		=  0
      with open(_A   ,   "w"   ,   encoding="utf-8" ) as writer:
        writer.write("#version: 0.2\n" )
        for bpe_tokens, token_index in sorted(self.bpe_ranks.items()   ,   key=lambda lowerCAmelCase : kv[1] ):
          if index != token_index:
            logger.warning(
                f"Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."
                " Please check that the tokenizer is not corrupted!" )
            a__  		=  token_index
          writer.write(" ".join(_A ) + "\n" )
          index += 1

      return vocab_file, merge_file




    def     __lowerCamelCase			(       self	: int   ,   lowerCAmelCase	: List[int]   ,   lowerCAmelCase	: Optional[List[int]] = None )						->			Tuple:
      if token_ids_a is None:
        return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      a__  		=  [self.cls_token_id]
      a__  		=  [self.sep_token_id]
      return cls + token_ids_a + sep + sep + token_ids_a + sep




    def     __lowerCamelCase			(       self	: Union[str, Any]   ,   lowerCAmelCase	: List[int]   ,   lowerCAmelCase	: Optional[List[int]] = None   ,   lowerCAmelCase	: bool = False )						->			Optional[int]:
      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 None:
        return [1] + ([0] * len(_A )) + [1]
      return [1] + ([0] * len(_A )) + [1, 1] + ([0] * len(_A )) + [1]




    def     __lowerCamelCase			(       self	: List[str]   ,   lowerCAmelCase	: List[int]   ,   lowerCAmelCase	: Optional[List[int]] = None )						->			str:
      a__  		=  [self.sep_token_id]
      a__  		=  [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]




    def     __lowerCamelCase			(       self	: Tuple   ,   lowerCAmelCase	: Any   ,   lowerCAmelCase	: List[Any]=False   ,   **lowerCAmelCase	: str )						->			Dict:
      a__  		=  kwargs.pop("add_prefix_space"   ,   self.add_prefix_space )
      if (is_split_into_words or add_prefix_space) and (len(_A ) > 0 and not text[0].isspace()):
        a__  		=  " " + text
      return (text, kwargs)






from ...configuration_utils import PretrainedConfig
from ...utils import logging


snake_case     :    Any						=    logging.get_logger(__name__)

snake_case     :    List[str]						=    {
    'MCG-NJU/videomae-base': 'https://huggingface.co/MCG-NJU/videomae-base/resolve/main/config.json',
}




class 				lowerCAmelCase__	(						UpperCamelCase    ):
					__A  :     str     =    'videomae'







					def __init__(							self   :  Optional[Any]      ,		_A   :  str=224      ,		_A   :  Union[str, Any]=16      ,		_A   :  int=3      ,		_A   :  Tuple=16      ,		_A   :  int=2      ,		_A   :  List[Any]=768      ,		_A   :  List[Any]=12      ,		_A   :  Tuple=12      ,		_A   :  List[Any]=3072      ,		_A   :  Union[str, Any]="gelu"      ,		_A   :  Any=0.0      ,		_A   :  str=0.0      ,		_A   :  Tuple=0.02      ,		_A   :  Optional[Any]=1e-12      ,		_A   :  Tuple=True      ,		_A   :  Dict=True      ,		_A   :  str=6      ,		_A   :  Optional[int]=384      ,		_A   :  Any=4      ,		_A   :  Any=1536      ,		_A   :  Optional[int]=True      ,		**_A   :  Tuple      ,		):
											super().__init__(**_A)

											A__						:				List[str]         =			image_size
											A__						:				Union[str, Any]         =			patch_size
											A__						:				Optional[int]         =			num_channels
											A__						:				int         =			num_frames
											A__						:				List[Any]         =			tubelet_size

											A__						:				str         =			hidden_size
											A__						:				Optional[Any]         =			num_hidden_layers
											A__						:				int         =			num_attention_heads
											A__						:				List[Any]         =			intermediate_size
											A__						:				Optional[int]         =			hidden_act
											A__						:				Any         =			hidden_dropout_prob
											A__						:				str         =			attention_probs_dropout_prob
											A__						:				List[Any]         =			initializer_range
											A__						:				str         =			layer_norm_eps
											A__						:				Any         =			qkv_bias
											A__						:				Union[str, Any]         =			use_mean_pooling

											A__						:				int         =			decoder_num_attention_heads
											A__						:				Tuple         =			decoder_hidden_size
											A__						:				int         =			decoder_num_hidden_layers
											A__						:				int         =			decoder_intermediate_size
											A__						:				Any         =			norm_pix_loss