


"""simple docstring"""







import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_longformer import LongformerTokenizer


lowerCamelCase_  :  str     		=    logging.get_logger(__name__)

lowerCamelCase_  :  List[str]     		=    {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

lowerCamelCase_  :  Tuple     		=    {
    "vocab_file": {
        "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json",
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt",
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt"
        ),
    },
    "tokenizer_file": {
        "allenai/longformer-base-4096": (
            "https://huggingface.co/allenai/longformer-base-4096/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/tokenizer.json"
        ),
    },
}

lowerCamelCase_  :  str     		=    {
    "allenai/longformer-base-4096": 4_0_9_6,
    "allenai/longformer-large-4096": 4_0_9_6,
    "allenai/longformer-large-4096-finetuned-triviaqa": 4_0_9_6,
    "allenai/longformer-base-4096-extra.pos.embd.only": 4_0_9_6,
    "allenai/longformer-large-4096-extra.pos.embd.only": 4_0_9_6,
}






class  __A							(			lowerCAmelCase_     ):






 """simple docstring"""




 __lowerCAmelCase					   =    VOCAB_FILES_NAMES
 __lowerCAmelCase					   =    PRETRAINED_VOCAB_FILES_MAP
 __lowerCAmelCase					   =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __lowerCAmelCase					   =    ["input_ids", "attention_mask"]
 __lowerCAmelCase					   =    LongformerTokenizer


 def __init__(						self					,       __A=None					,       __A=None					,       __A=None					,       __A="replace"					,       __A="<s>"					,       __A="</s>"					,       __A="</s>"					,       __A="<s>"					,       __A="<unk>"					,       __A="<pad>"					,       __A="<mask>"					,       __A=False					,       __A=True					,       **__A					,       )   ->	List[str]:
     super().__init__(
         __A					,       __A					,       tokenizer_file=__A					,       errors=__A					,       bos_token=__A					,       eos_token=__A					,       sep_token=__A					,       cls_token=__A					,       unk_token=__A					,       pad_token=__A					,       mask_token=__A					,       add_prefix_space=__A					,       trim_offsets=__A					,       **__A					,       )

     a											=json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()		)
     if pre_tok_state.get('''add_prefix_space'''					,       __A		) != add_prefix_space:
         a											=getattr(__A					,       pre_tok_state.pop('''type'''		)		)
         a											=add_prefix_space
         a											=pre_tok_class(**__A		)

     a											=add_prefix_space

     a											='''post_processor'''
     a											=getattr(self.backend_tokenizer					,       __A					,       __A		)
     if tokenizer_component_instance:
         a											=json.loads(tokenizer_component_instance.__getstate__()		)

         # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
         if "sep" in state:
             a											=tuple(state['''sep''']		)
         if "cls" in state:
             a											=tuple(state['''cls''']		)

         a											=False

         if state.get('''add_prefix_space'''					,       __A		) != add_prefix_space:
             a											=add_prefix_space
             a											=True

         if state.get('''trim_offsets'''					,       __A		) != trim_offsets:
             a											=trim_offsets
             a											=True

         if changes_to_apply:
             a											=getattr(__A					,       state.pop('''type'''		)		)
             a											=component_class(**__A		)
             setattr(self.backend_tokenizer					,       __A					,       __A		)


 @property
 def  SCREAMING_SNAKE_CASE				(						self		)   ->	str:
     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  SCREAMING_SNAKE_CASE				(						self					,       __A		)   ->	List[str]:
     a											=AddedToken(__A					,       lstrip=__A					,       rstrip=__A		) if isinstance(__A					,       __A		) else value
     a											=value


 def  SCREAMING_SNAKE_CASE				(						self					,       *__A					,       **__A		)   ->	BatchEncoding:
     a											=kwargs.get('''is_split_into_words'''					,       __A		)
     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(*__A					,       **__A		)


 def  SCREAMING_SNAKE_CASE				(						self					,       *__A					,       **__A		)   ->	BatchEncoding:
     a											=kwargs.get('''is_split_into_words'''					,       __A		)

     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(*__A					,       **__A		)


 def  SCREAMING_SNAKE_CASE				(						self					,       __A					,       __A = None		)   ->	Tuple[str]:
     a											=self._tokenizer.model.save(__A					,       name=__A		)
     return tuple(__A		)


 def  SCREAMING_SNAKE_CASE				(						self					,       __A					,       __A=None		)   ->	str:
     a											=[self.bos_token_id] + token_ids_a + [self.eos_token_id]
     if token_ids_a is None:
         return output

     return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]





 def  SCREAMING_SNAKE_CASE				(						self					,       __A					,       __A = None		)   ->	List[int]:
     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]




"""simple docstring"""






_lowercase					:					str 		=		{
    0: "underwear",
    1: "pants",
    2: "belt",
    3: "suit",
    4: "shoe",
    5: "socks",
    6: "shirt",
    7: "tie",
    8: "watch",
}

_lowercase					:					Dict 		=		[[1, 4], [2, 4], [3], [], [], [4], [2, 7], [3], []]

_lowercase					:					Union[str, Any] 		=		[0 for x in range(len(graph))]
_lowercase					:					Union[str, Any] 		=		[]






def 	snake_case__  (						__lowerCamelCase							:       Optional[int]				,						__lowerCamelCase							:       Dict      ):
			"""simple docstring"""
			lowerCamelCase__						:						int						      =1
			while stack:
						lowerCamelCase__						:						int						      =stack.pop()
						print(__lowerCamelCase				,						clothes[current_clothing]      )
						order += 1






def 	snake_case__  (						__lowerCamelCase							:       Optional[Any]				,						__lowerCamelCase							:       str				,						__lowerCamelCase							:       Tuple      ):
			"""simple docstring"""
			lowerCamelCase__						:						Dict						      =1
			for v in graph[u]:
						if not visited[v]:
									depth_first_search(__lowerCamelCase				,						__lowerCamelCase				,						__lowerCamelCase      )

			stack.append(__lowerCamelCase      )






def 	snake_case__  (						__lowerCamelCase							:       Optional[Any]				,						__lowerCamelCase							:       Optional[Any]      ):
			"""simple docstring"""
			for v in range(len(__lowerCamelCase      )      ):
						if not visited[v]:
									depth_first_search(__lowerCamelCase				,						__lowerCamelCase				,						__lowerCamelCase      )


if __name__ == "__main__":
		topological_sort(graph, visited)
		print(stack)
		print_stack(stack, clothes)




