


'''simple docstring'''







# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also say that there is no edge that connects
# vertices of same set.






def 	SCREAMING_SNAKE_CASE_					(  _UpperCAmelCase	:	List[Any]  )  ->			List[Any]:
       _a    : Any     					=[False] * len(__snake_case  )
       _a    : Dict     					=[-1] * len(__snake_case  )

       def dfs(_UpperCAmelCase	:	Dict    ,_UpperCAmelCase	:	Tuple  ):
              _a    : Optional[Any]     					=True
              _a    : Dict     					=c
              for u in graph[v]:
                     if not visited[u]:
                            dfs(__snake_case    ,1 - c  )

       for i in range(len(__snake_case  )  ):
              if not visited[i]:
                     dfs(__snake_case    ,0  )

       for i in range(len(__snake_case  )  ):
              for j in graph[i]:
                     if color[i] == color[j]:
                            return False

       return True


# Adjacency list of graph
A__:    str					    =       {0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 4: []}
print(check_bipartite_dfs(graph))










import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer


__UpperCAmelCase								=						logging.get_logger(__name__)

__UpperCAmelCase								=						{'vocab_file': 'vocab.txt'}

__UpperCAmelCase								=						{
    'vocab_file': {
        'YituTech/conv-bert-base': 'https://huggingface.co/YituTech/conv-bert-base/resolve/main/vocab.txt',
        'YituTech/conv-bert-medium-small': (
            'https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/vocab.txt'
        ),
        'YituTech/conv-bert-small': 'https://huggingface.co/YituTech/conv-bert-small/resolve/main/vocab.txt',
    }
}

__UpperCAmelCase								=						{
    'YituTech/conv-bert-base': 512,
    'YituTech/conv-bert-medium-small': 512,
    'YituTech/conv-bert-small': 512,
}


__UpperCAmelCase								=						{
    'YituTech/conv-bert-base': {'do_lower_case': True},
    'YituTech/conv-bert-medium-small': {'do_lower_case': True},
    'YituTech/conv-bert-small': {'do_lower_case': True},
}



class   lowerCamelCase      (_snake_case			):







		'''simple docstring'''



		_snake_case    :    Optional[int]       						=  VOCAB_FILES_NAMES
		_snake_case    :    int       						=  PRETRAINED_VOCAB_FILES_MAP
		_snake_case    :    Dict       						=  PRETRAINED_INIT_CONFIGURATION
		_snake_case    :    List[str]       						=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		_snake_case    :    Any       						=  ConvBertTokenizer



		def __init__(							self				,		_UpperCamelCase=None				,		_UpperCamelCase=None				,		_UpperCamelCase=True				,		_UpperCamelCase="[UNK]"				,		_UpperCamelCase="[SEP]"				,		_UpperCamelCase="[PAD]"				,		_UpperCamelCase="[CLS]"				,		_UpperCamelCase="[MASK]"				,		_UpperCamelCase=True				,		_UpperCamelCase=None				,		**_UpperCamelCase				,		)	->							Dict:
							super().__init__(
							    _UpperCamelCase				,		tokenizer_file=_UpperCamelCase				,		do_lower_case=_UpperCamelCase				,		unk_token=_UpperCamelCase				,		sep_token=_UpperCamelCase				,		pad_token=_UpperCamelCase				,		cls_token=_UpperCamelCase				,		mask_token=_UpperCamelCase				,		tokenize_chinese_chars=_UpperCamelCase				,		strip_accents=_UpperCamelCase				,		**_UpperCamelCase				,		)

							UpperCAmelCase_    :      Optional[int]            =						json.loads(self.backend_tokenizer.normalizer.__getstate__()   )
							if (
							    normalizer_state.get('lowercase'				,		_UpperCamelCase   ) != do_lower_case
							    or normalizer_state.get('strip_accents'				,		_UpperCamelCase   ) != strip_accents
							    or normalizer_state.get('handle_chinese_chars'				,		_UpperCamelCase   ) != tokenize_chinese_chars
							):
												UpperCAmelCase_    :      Any            =						getattr(_UpperCamelCase				,		normalizer_state.pop('type'   )   )
												UpperCAmelCase_    :      str            =						do_lower_case
												UpperCAmelCase_    :      List[Any]            =						strip_accents
												UpperCAmelCase_    :      str            =						tokenize_chinese_chars
												UpperCAmelCase_    :      Tuple            =						normalizer_class(**_UpperCamelCase   )

							UpperCAmelCase_    :      Any            =						do_lower_case



		def 					__UpperCAmelCase			(							self				,		_UpperCamelCase				,		_UpperCamelCase=None   )	->							List[str]:
							UpperCAmelCase_    :      int            =						[self.cls_token_id] + token_ids_a + [self.sep_token_id]

							if token_ids_a:
												output += token_ids_a + [self.sep_token_id]

							return output



		def 					__UpperCAmelCase			(							self				,		_UpperCamelCase				,		_UpperCamelCase = None   )	->							List[int]:
							UpperCAmelCase_    :      Union[str, Any]            =						[self.sep_token_id]
							UpperCAmelCase_    :      int            =						[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 					__UpperCAmelCase			(							self				,		_UpperCamelCase				,		_UpperCamelCase = None   )	->							Tuple[str]:
							UpperCAmelCase_    :      Any            =						self._tokenizer.model.save(_UpperCamelCase				,		name=_UpperCamelCase   )
							return tuple(_UpperCamelCase   )






