


A_								=   {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}

A_								=   {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}







def 				UpperCAmelCase					(  UpperCAmelCase					,UpperCAmelCase					,UpperCAmelCase   )->		list[int]:







					'''simple docstring'''



					SCREAMING_SNAKE_CASE_						   =							True
					SCREAMING_SNAKE_CASE_						   =							[]

					for neighbour in graph[vert]:
										if not visited[neighbour]:
															order += topology_sort(_lowerCamelCase					,_lowerCamelCase					,_lowerCamelCase   )

					order.append(_lowerCamelCase   )

					return order







def 				UpperCAmelCase					(  UpperCAmelCase					,UpperCAmelCase					,UpperCAmelCase   )->		list[int]:







					'''simple docstring'''



					SCREAMING_SNAKE_CASE_						   =							True
					SCREAMING_SNAKE_CASE_						   =							[vert]

					for neighbour in reversed_graph[vert]:
										if not visited[neighbour]:
															component += find_components(_lowerCamelCase					,_lowerCamelCase					,_lowerCamelCase   )

					return component







def 				UpperCAmelCase					(  UpperCAmelCase   )->		list[list[int]]:







					'''simple docstring'''



					SCREAMING_SNAKE_CASE_						   =							len(_lowerCamelCase   ) * [False]
					SCREAMING_SNAKE_CASE_						   =							{vert: [] for vert in range(len(_lowerCamelCase   )   )}

					for vert, neighbours in graph.items():
										for neighbour in neighbours:
															reversed_graph[neighbour].append(_lowerCamelCase   )

					SCREAMING_SNAKE_CASE_						   =							[]
					for i, was_visited in enumerate(_lowerCamelCase   ):
										if not was_visited:
															order += topology_sort(_lowerCamelCase					,_lowerCamelCase					,_lowerCamelCase   )

					SCREAMING_SNAKE_CASE_						   =							[]
					SCREAMING_SNAKE_CASE_						   =							len(_lowerCamelCase   ) * [False]

					for i in range(len(_lowerCamelCase   )   ):
										SCREAMING_SNAKE_CASE_						   =							order[len(_lowerCamelCase   ) - i - 1]
										if not visited[vert]:
															SCREAMING_SNAKE_CASE_						   =							find_components(_lowerCamelCase					,_lowerCamelCase					,_lowerCamelCase   )
															components_list.append(_lowerCamelCase   )

					return components_list








'''simple docstring'''



import json
from typing import Dict, List, Optional, Tuple, Union

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_led import LEDTokenizer


UpperCAmelCase_							:	Any	     =		logging.get_logger(__name__)


UpperCAmelCase_							:	str	     =		{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

UpperCAmelCase_							:	str	     =		{
    '''vocab_file''': {
        '''allenai/led-base-16384''': '''https://huggingface.co/allenai/led-base-16384/resolve/main/vocab.json''',
    },
    '''merges_file''': {
        '''allenai/led-base-16384''': '''https://huggingface.co/allenai/led-base-16384/resolve/main/merges.txt''',
    },
    '''tokenizer_file''': {
        '''allenai/led-base-16384''': '''https://huggingface.co/allenai/led-base-16384/resolve/main/tokenizer.json''',
    },
}

UpperCAmelCase_							:	Union[str, Any]	     =		{
    '''allenai/led-base-16384''': 1_6_3_8_4,
}





class      lowerCAmelCase (			__lowerCAmelCase):
       __lowercase	:   Dict										=      VOCAB_FILES_NAMES
       __lowercase	:   Dict										=      PRETRAINED_VOCAB_FILES_MAP
       __lowercase	:   Tuple										=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       __lowercase	:   Union[str, Any]										=      LEDTokenizer
       __lowercase	:   int										=      ['''input_ids''', '''attention_mask''']


       def __init__( self     ,	__SCREAMING_SNAKE_CASE=None     ,	__SCREAMING_SNAKE_CASE=None     ,	__SCREAMING_SNAKE_CASE=None     ,	__SCREAMING_SNAKE_CASE="replace"     ,	__SCREAMING_SNAKE_CASE="<s>"     ,	__SCREAMING_SNAKE_CASE="</s>"     ,	__SCREAMING_SNAKE_CASE="</s>"     ,	__SCREAMING_SNAKE_CASE="<s>"     ,	__SCREAMING_SNAKE_CASE="<unk>"     ,	__SCREAMING_SNAKE_CASE="<pad>"     ,	__SCREAMING_SNAKE_CASE="<mask>"     ,	__SCREAMING_SNAKE_CASE=False     ,	__SCREAMING_SNAKE_CASE=True     ,	**__SCREAMING_SNAKE_CASE     ,	)   ->	List[Any]:



            '''simple docstring'''




            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     ,	sep_token=__SCREAMING_SNAKE_CASE     ,	cls_token=__SCREAMING_SNAKE_CASE     ,	unk_token=__SCREAMING_SNAKE_CASE     ,	pad_token=__SCREAMING_SNAKE_CASE     ,	mask_token=__SCREAMING_SNAKE_CASE     ,	add_prefix_space=__SCREAMING_SNAKE_CASE     ,	trim_offsets=__SCREAMING_SNAKE_CASE     ,	**__SCREAMING_SNAKE_CASE     ,	)

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

            __snake_case            =	add_prefix_space

            # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
            __snake_case            =	'''post_processor'''
            __snake_case            =	getattr(self.backend_tokenizer     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE	)
            if tokenizer_component_instance:
                 __snake_case            =	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:
                      __snake_case            =	tuple(state['''sep''']	)
                 if "cls" in state:
                      __snake_case            =	tuple(state['''cls''']	)

                 __snake_case            =	False

                 if state.get('''add_prefix_space'''     ,	__SCREAMING_SNAKE_CASE	) != add_prefix_space:
                      __snake_case            =	add_prefix_space
                      __snake_case            =	True

                 if state.get('''trim_offsets'''     ,	__SCREAMING_SNAKE_CASE	) != trim_offsets:
                      __snake_case            =	trim_offsets
                      __snake_case            =	True

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


       @property
       # Copied from transformers.models.bart.tokenization_bart_fast.BartTokenizerFast.mask_token with BART->LED
       def    lowerCAmelCase   ( self	)   ->	str:



            '''simple docstring'''




            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	)   ->	Dict:



            '''simple docstring'''




            __snake_case            =	AddedToken(__SCREAMING_SNAKE_CASE     ,	lstrip=__SCREAMING_SNAKE_CASE     ,	rstrip=__SCREAMING_SNAKE_CASE	) if isinstance(__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE	) else value
            __snake_case            =	value


       def    lowerCAmelCase   ( self     ,	*__SCREAMING_SNAKE_CASE     ,	**__SCREAMING_SNAKE_CASE	)   ->	BatchEncoding:



            '''simple docstring'''




            __snake_case            =	kwargs.get('''is_split_into_words'''     ,	__SCREAMING_SNAKE_CASE	)

            if is_split_into_words and not self.add_prefix_space:
                 raise ValueError(
                     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	)   ->	BatchEncoding:



            '''simple docstring'''




            __snake_case            =	kwargs.get('''is_split_into_words'''     ,	__SCREAMING_SNAKE_CASE	)

            if is_split_into_words and not self.add_prefix_space:
                 raise ValueError(
                     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	)   ->	Tuple[str]:



            '''simple docstring'''




            __snake_case            =	self._tokenizer.model.save(__SCREAMING_SNAKE_CASE     ,	name=__SCREAMING_SNAKE_CASE	)
            return tuple(__SCREAMING_SNAKE_CASE	)


       def    lowerCAmelCase   ( self     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE=None	)   ->	List[Any]:



            '''simple docstring'''




            __snake_case            =	[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    lowerCAmelCase   ( self     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE = None	)   ->	List[int]:



            '''simple docstring'''




            __snake_case            =	[self.sep_token_id]
            __snake_case            =	[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     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE = None     ,	__SCREAMING_SNAKE_CASE = PaddingStrategy.DO_NOT_PAD     ,	__SCREAMING_SNAKE_CASE = None     ,	__SCREAMING_SNAKE_CASE = None     ,	)   ->	dict:



            '''simple docstring'''




            __snake_case            =	super()._pad(
                encoded_inputs=__SCREAMING_SNAKE_CASE     ,	max_length=__SCREAMING_SNAKE_CASE     ,	padding_strategy=__SCREAMING_SNAKE_CASE     ,	pad_to_multiple_of=__SCREAMING_SNAKE_CASE     ,	return_attention_mask=__SCREAMING_SNAKE_CASE     ,	)

            # Load from model defaults
            if return_attention_mask is None:
                 __snake_case            =	'''attention_mask''' in self.model_input_names

            if return_attention_mask and "global_attention_mask" in encoded_inputs:
                 __snake_case            =	encoded_inputs[self.model_input_names[0]]
                 # `global_attention_mask` need to have the same length as other (sequential) inputs.
                 __snake_case            =	len(encoded_inputs['''global_attention_mask''']	) != len(__SCREAMING_SNAKE_CASE	)

                 if needs_to_be_padded:
                      __snake_case            =	len(__SCREAMING_SNAKE_CASE	) - len(encoded_inputs['''global_attention_mask''']	)

                      if self.padding_side == "right":
                           # Use `-1` since `0` in `global_attention_mask` means `local attention` instead of `not to attend`
                           __snake_case            =	(
                               encoded_inputs['''global_attention_mask'''] + [-1] * difference
                           )
                      elif self.padding_side == "left":
                           __snake_case            =	[-1] * difference + encoded_inputs[
                               '''global_attention_mask'''
                           ]
                      else:
                           raise ValueError('''Invalid padding strategy:''' + str(self.padding_side	)	)

            return encoded_inputs






