code: 
  
  
  import json
  from typing import TYPE_CHECKING, List, Optional, Tuple
  
  from tokenizers import pre_tokenizers
  
  from ...tokenization_utils_base import AddedToken, BatchEncoding
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import logging
  from .tokenization_deberta import DebertaTokenizer
  
  
  if TYPE_CHECKING:
    from transformers.pipelines.conversational import Conversation
  
  
  __a   				=      logging.get_logger(__name__)
  
  __a   				=      {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}
  
  __a   				=      {
      '''vocab_file''': {
          '''microsoft/deberta-base''': '''https://huggingface.co/microsoft/deberta-base/resolve/main/vocab.json''',
          '''microsoft/deberta-large''': '''https://huggingface.co/microsoft/deberta-large/resolve/main/vocab.json''',
          '''microsoft/deberta-xlarge''': '''https://huggingface.co/microsoft/deberta-xlarge/resolve/main/vocab.json''',
          '''microsoft/deberta-base-mnli''': '''https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/vocab.json''',
          '''microsoft/deberta-large-mnli''': '''https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/vocab.json''',
          '''microsoft/deberta-xlarge-mnli''': (
              '''https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/vocab.json'''
          ),
      },
      '''merges_file''': {
          '''microsoft/deberta-base''': '''https://huggingface.co/microsoft/deberta-base/resolve/main/merges.txt''',
          '''microsoft/deberta-large''': '''https://huggingface.co/microsoft/deberta-large/resolve/main/merges.txt''',
          '''microsoft/deberta-xlarge''': '''https://huggingface.co/microsoft/deberta-xlarge/resolve/main/merges.txt''',
          '''microsoft/deberta-base-mnli''': '''https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/merges.txt''',
          '''microsoft/deberta-large-mnli''': '''https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/merges.txt''',
          '''microsoft/deberta-xlarge-mnli''': (
              '''https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/merges.txt'''
          ),
      },
  }
  
  __a   				=      {
      '''microsoft/deberta-base''': 5_12,
      '''microsoft/deberta-large''': 5_12,
      '''microsoft/deberta-xlarge''': 5_12,
      '''microsoft/deberta-base-mnli''': 5_12,
      '''microsoft/deberta-large-mnli''': 5_12,
      '''microsoft/deberta-xlarge-mnli''': 5_12,
  }
  
  __a   				=      {
      '''microsoft/deberta-base''': {'''do_lower_case''': False},
      '''microsoft/deberta-large''': {'''do_lower_case''': False},
  }
  
  
  
  
  
  
  
  class 				__SCREAMING_SNAKE_CASE   (			A__   ):
        A				:							Dict    							=     VOCAB_FILES_NAMES
        A				:							str    							=     PRETRAINED_VOCAB_FILES_MAP
        A				:							Union[str, Any]    							=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
        A				:							Union[str, Any]    							=     ['input_ids', 'attention_mask', 'token_type_ids']
        A				:							Optional[int]    							=     DebertaTokenizer
  
  
        def __init__(							self							,						SCREAMING_SNAKE_CASE__=None							,						SCREAMING_SNAKE_CASE__=None							,						SCREAMING_SNAKE_CASE__=None							,						SCREAMING_SNAKE_CASE__="replace"							,						SCREAMING_SNAKE_CASE__="[CLS]"							,						SCREAMING_SNAKE_CASE__="[SEP]"							,						SCREAMING_SNAKE_CASE__="[SEP]"							,						SCREAMING_SNAKE_CASE__="[CLS]"							,						SCREAMING_SNAKE_CASE__="[UNK]"							,						SCREAMING_SNAKE_CASE__="[PAD]"							,						SCREAMING_SNAKE_CASE__="[MASK]"							,						SCREAMING_SNAKE_CASE__=False							,						**SCREAMING_SNAKE_CASE__							,						):
              super().__init__(
                  SCREAMING_SNAKE_CASE__							,						SCREAMING_SNAKE_CASE__							,						tokenizer_file=SCREAMING_SNAKE_CASE__							,						errors=SCREAMING_SNAKE_CASE__							,						bos_token=SCREAMING_SNAKE_CASE__							,						eos_token=SCREAMING_SNAKE_CASE__							,						unk_token=SCREAMING_SNAKE_CASE__							,						sep_token=SCREAMING_SNAKE_CASE__							,						cls_token=SCREAMING_SNAKE_CASE__							,						pad_token=SCREAMING_SNAKE_CASE__							,						mask_token=SCREAMING_SNAKE_CASE__							,						add_prefix_space=SCREAMING_SNAKE_CASE__							,						**SCREAMING_SNAKE_CASE__							,						)
              lowercase			:   Union[str, Any]					   =		kwargs.pop('''add_bos_token'''							,						SCREAMING_SNAKE_CASE__		)
  
              lowercase			:   List[Any]					   =		json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()		)
              if pre_tok_state.get('''add_prefix_space'''							,						SCREAMING_SNAKE_CASE__		) != add_prefix_space:
                    lowercase			:   Union[str, Any]					   =		getattr(SCREAMING_SNAKE_CASE__							,						pre_tok_state.pop('''type'''		)		)
                    lowercase			:   str					   =		add_prefix_space
                    lowercase			:   Tuple					   =		pre_tok_class(**SCREAMING_SNAKE_CASE__		)
  
              lowercase			:   Optional[int]					   =		add_prefix_space
  
  
        @property
        def        __lowerCamelCase			(							self		):
              if self._mask_token is None:
                    if self.verbose:
                          logger.error('''Using mask_token, but it is not set yet.'''		)
                    return None
              return str(self._mask_token		)
  
  
        @mask_token.setter
        def        __lowerCamelCase			(							self							,						SCREAMING_SNAKE_CASE__		):
              lowercase			:   Optional[int]					   =		AddedToken(SCREAMING_SNAKE_CASE__							,						lstrip=SCREAMING_SNAKE_CASE__							,						rstrip=SCREAMING_SNAKE_CASE__		) if isinstance(SCREAMING_SNAKE_CASE__							,						SCREAMING_SNAKE_CASE__		) else value
              lowercase			:   List[str]					   =		value
  
  
        def        __lowerCamelCase			(							self							,						SCREAMING_SNAKE_CASE__							,						SCREAMING_SNAKE_CASE__ = None		):
              if token_ids_a is None:
                    return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
              lowercase			:   List[Any]					   =		[self.cls_token_id]
              lowercase			:   str					   =		[self.sep_token_id]
              return cls + token_ids_a + sep + token_ids_a + sep
  
  
        def        __lowerCamelCase			(							self							,						SCREAMING_SNAKE_CASE__							,						SCREAMING_SNAKE_CASE__ = None		):
              lowercase			:   Optional[int]					   =		[self.sep_token_id]
              lowercase			:   Optional[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        __lowerCamelCase			(							self							,						*SCREAMING_SNAKE_CASE__							,						**SCREAMING_SNAKE_CASE__		):
              lowercase			:   List[Any]					   =		kwargs.get('''is_split_into_words'''							,						SCREAMING_SNAKE_CASE__		)
              assert self.add_prefix_space or not is_split_into_words, (
                  f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
                  "to use it with pretokenized inputs."
              )
  
              return super()._batch_encode_plus(*SCREAMING_SNAKE_CASE__							,						**SCREAMING_SNAKE_CASE__		)
  
  
        def        __lowerCamelCase			(							self							,						*SCREAMING_SNAKE_CASE__							,						**SCREAMING_SNAKE_CASE__		):
              lowercase			:   int					   =		kwargs.get('''is_split_into_words'''							,						SCREAMING_SNAKE_CASE__		)
  
              assert self.add_prefix_space or not is_split_into_words, (
                  f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
                  "to use it with pretokenized inputs."
              )
  
              return super()._encode_plus(*SCREAMING_SNAKE_CASE__							,						**SCREAMING_SNAKE_CASE__		)
  
  
        def        __lowerCamelCase			(							self							,						SCREAMING_SNAKE_CASE__							,						SCREAMING_SNAKE_CASE__ = None		):
              lowercase			:   Dict					   =		self._tokenizer.model.save(SCREAMING_SNAKE_CASE__							,						name=SCREAMING_SNAKE_CASE__		)
              return tuple(SCREAMING_SNAKE_CASE__		)
  
  
  
  
  
  
        def        __lowerCamelCase			(							self							,						SCREAMING_SNAKE_CASE__		):
              lowercase			:   int					   =		[]
              for is_user, text in conversation.iter_texts():
                    input_ids.extend(self.encode(SCREAMING_SNAKE_CASE__							,						add_special_tokens=SCREAMING_SNAKE_CASE__		) + [self.eos_token_id]		)
  
              if len(SCREAMING_SNAKE_CASE__		) > self.model_max_length:
                    lowercase			:   List[str]					   =		input_ids[-self.model_max_length :]
              return input_ids
  
  
style_context: 
  
  
  __a   				=      [
      [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
      [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0],
      [0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0],
      [0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0],
      [0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0],
      [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0],
      [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0],
      [0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0],
  ]
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase,    _UpperCamelCase,    _UpperCamelCase,    _UpperCamelCase     )    ->bool:
  
  
  
  
  
  
  
        """simple docstring"""
  
        return 0 <= row < rows and 0 <= col < cols
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase,    _UpperCamelCase,    _UpperCamelCase,    _UpperCamelCase     )    ->int:
  
  
  
  
  
  
  
        """simple docstring"""
  
        lowercase			:   Optional[int]					   =		len(_UpperCamelCase     )
        lowercase			:   str					   =		len(mat[0]     )
        if is_safe(_UpperCamelCase,    _UpperCamelCase,    _UpperCamelCase,    _UpperCamelCase     ) and (row, col) not in seen and mat[row][col] == 1:
              seen.add((row, col)     )
              return (
                  1
                  + depth_first_search(row + 1,    _UpperCamelCase,    _UpperCamelCase,    _UpperCamelCase     )
                  + depth_first_search(row - 1,    _UpperCamelCase,    _UpperCamelCase,    _UpperCamelCase     )
                  + depth_first_search(_UpperCamelCase,    col + 1,    _UpperCamelCase,    _UpperCamelCase     )
                  + depth_first_search(_UpperCamelCase,    col - 1,    _UpperCamelCase,    _UpperCamelCase     )
              )
        else:
              return 0
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase     )    ->int:
  
  
  
  
  
  
  
        """simple docstring"""
  
        lowercase			:   set					   =		set()
  
        lowercase			:   Tuple					   =		0
        for row, line in enumerate(_UpperCamelCase     ):
              for col, item in enumerate(_UpperCamelCase     ):
                    if item == 1 and (row, col) not in seen:
                          # Maximizing the area
                          lowercase			:   Tuple					   =		max(_UpperCamelCase,    depth_first_search(_UpperCamelCase,    _UpperCamelCase,    _UpperCamelCase,    _UpperCamelCase     )     )
        return max_area
  
  
  if __name__ == "__main__":
    import doctest
  
    print(find_max_area(matrix))  # Output -> 6
    doctest.testmod()
  
  