

import json
from typing import List, Optional, Tuple

from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoFormerTokenizer
from .tokenization_utils import JiebaPreTokenizer


_lowerCAmelCase					:			int  				=			logging.get_logger(__name__)

_lowerCAmelCase					:			Tuple  				=			{"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

_lowerCAmelCase					:			Optional[Any]  				=			{
    "vocab_file": {
        "junnyu/roformer_chinese_small": "https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/vocab.txt",
        "junnyu/roformer_chinese_base": "https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/vocab.txt",
        "junnyu/roformer_chinese_char_small": (
            "https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/vocab.txt"
        ),
        "junnyu/roformer_chinese_char_base": (
            "https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/vocab.txt"
        ),
        "junnyu/roformer_small_discriminator": (
            "https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/vocab.txt"
        ),
        "junnyu/roformer_small_generator": (
            "https://huggingface.co/junnyu/roformer_small_generator/resolve/main/vocab.txt"
        ),
    }
}

_lowerCAmelCase					:			Any  				=			{
    "junnyu/roformer_chinese_small": 1_536,
    "junnyu/roformer_chinese_base": 1_536,
    "junnyu/roformer_chinese_char_small": 512,
    "junnyu/roformer_chinese_char_base": 512,
    "junnyu/roformer_small_discriminator": 128,
    "junnyu/roformer_small_generator": 128,
}


_lowerCAmelCase					:			Tuple  				=			{
    "junnyu/roformer_chinese_small": {"do_lower_case": True},
    "junnyu/roformer_chinese_base": {"do_lower_case": True},
    "junnyu/roformer_chinese_char_small": {"do_lower_case": True},
    "junnyu/roformer_chinese_char_base": {"do_lower_case": True},
    "junnyu/roformer_small_discriminator": {"do_lower_case": True},
    "junnyu/roformer_small_generator": {"do_lower_case": True},
}






class 	__magic_name__    (			lowerCAmelCase_      ):
			SCREAMING_SNAKE_CASE							   =						VOCAB_FILES_NAMES
			SCREAMING_SNAKE_CASE							   =						PRETRAINED_VOCAB_FILES_MAP
			SCREAMING_SNAKE_CASE							   =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			SCREAMING_SNAKE_CASE							   =						PRETRAINED_INIT_CONFIGURATION
			SCREAMING_SNAKE_CASE							   =						RoFormerTokenizer





			def __init__(		self					,  __snake_case=None					,  __snake_case=None					,  __snake_case=True					,  __snake_case="[UNK]"					,  __snake_case="[SEP]"					,  __snake_case="[PAD]"					,  __snake_case="[CLS]"					,  __snake_case="[MASK]"					,  __snake_case=True					,  __snake_case=None					,  **__snake_case					,  )   -> Optional[Any]:




						'''simple docstring'''
						super().__init__(
						    __snake_case					,  tokenizer_file=__snake_case					,  do_lower_case=__snake_case					,  unk_token=__snake_case					,  sep_token=__snake_case					,  pad_token=__snake_case					,  cls_token=__snake_case					,  mask_token=__snake_case					,  tokenize_chinese_chars=__snake_case					,  strip_accents=__snake_case					,  **__snake_case					,  )

						__a        =json.loads(self.backend_tokenizer.normalizer.__getstate__()					)
						if (
						    pre_tok_state.get('lowercase'					,  __snake_case					) != do_lower_case
						    or pre_tok_state.get('strip_accents'					,  __snake_case					) != strip_accents
						):
									__a        =getattr(__snake_case					,  pre_tok_state.pop('type'					)					)
									__a        =do_lower_case
									__a        =strip_accents
									__a        =pre_tok_class(**__snake_case					)

						__a        =do_lower_case





			def __getstate__(		self					)   -> List[Any]:




						'''simple docstring'''
						__a        =self.__dict__.copy()
						__a        =BertPreTokenizer()
						return state





			def __setstate__(		self					,  __snake_case					)   -> Union[str, Any]:




						'''simple docstring'''
						__a        =d
						__a        =self.__dict__['_tokenizer'].get_vocab()
						__a        =PreTokenizer.custom(JiebaPreTokenizer(__snake_case					)					)





			def 		__magic_name__    (		self					,  __snake_case					,  __snake_case=None					)   -> Union[str, Any]:




						'''simple docstring'''
						__a        =[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 		__magic_name__    (		self					,  __snake_case					,  __snake_case = None					)   -> List[int]:




						'''simple docstring'''
						__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					) * [0] + len(token_ids_a + sep					) * [1]





			def 		__magic_name__    (		self					,  __snake_case					,  __snake_case = None					)   -> Tuple[str]:




						'''simple docstring'''
						__a        =self._tokenizer.model.save(__snake_case					,  name=__snake_case					)
						return tuple(__snake_case					)





			def 		__magic_name__    (		self					,  __snake_case					,  __snake_case=None					,  __snake_case=None					,  __snake_case=False					,  **__snake_case					,  )   -> Any:




						'''simple docstring'''
						__a        =BertPreTokenizer()
						return super().save_pretrained(__snake_case					,  __snake_case					,  __snake_case					,  __snake_case					,  **__snake_case					)









# 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        UpperCamelCase_(							_snake_case   :  Tuple	):




			"""simple docstring"""






			__a        =[False] * len(_snake_case	)
			__a        =[-1] * len(_snake_case	)

			def dfs(_snake_case   :  Dict       ,     _snake_case   :  Any	):
						__a        =True
						__a        =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
_lowerCAmelCase					:			int  				=			{0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 4: []}


print(check_bipartite_dfs(graph))






