


'''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_bart import BartTokenizer


__UpperCAmelCase       =							logging.get_logger(__name__)


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

# See all BART models at https://huggingface.co/models?filter=bart
__UpperCAmelCase       =							{
    '''vocab_file''': {
        '''facebook/bart-base''': '''https://huggingface.co/facebook/bart-base/resolve/main/vocab.json''',
        '''facebook/bart-large''': '''https://huggingface.co/facebook/bart-large/resolve/main/vocab.json''',
        '''facebook/bart-large-mnli''': '''https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json''',
        '''facebook/bart-large-cnn''': '''https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json''',
        '''facebook/bart-large-xsum''': '''https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json''',
        '''yjernite/bart_eli5''': '''https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json''',
    },
    '''merges_file''': {
        '''facebook/bart-base''': '''https://huggingface.co/facebook/bart-base/resolve/main/merges.txt''',
        '''facebook/bart-large''': '''https://huggingface.co/facebook/bart-large/resolve/main/merges.txt''',
        '''facebook/bart-large-mnli''': '''https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt''',
        '''facebook/bart-large-cnn''': '''https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt''',
        '''facebook/bart-large-xsum''': '''https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt''',
        '''yjernite/bart_eli5''': '''https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt''',
    },
    '''tokenizer_file''': {
        '''facebook/bart-base''': '''https://huggingface.co/facebook/bart-base/resolve/main/tokenizer.json''',
        '''facebook/bart-large''': '''https://huggingface.co/facebook/bart-large/resolve/main/tokenizer.json''',
        '''facebook/bart-large-mnli''': '''https://huggingface.co/facebook/bart-large-mnli/resolve/main/tokenizer.json''',
        '''facebook/bart-large-cnn''': '''https://huggingface.co/facebook/bart-large-cnn/resolve/main/tokenizer.json''',
        '''facebook/bart-large-xsum''': '''https://huggingface.co/facebook/bart-large-xsum/resolve/main/tokenizer.json''',
        '''yjernite/bart_eli5''': '''https://huggingface.co/yjernite/bart_eli5/resolve/main/tokenizer.json''',
    },
}

__UpperCAmelCase       =							{
    '''facebook/bart-base''': 1_024,
    '''facebook/bart-large''': 1_024,
    '''facebook/bart-large-mnli''': 1_024,
    '''facebook/bart-large-cnn''': 1_024,
    '''facebook/bart-large-xsum''': 1_024,
    '''yjernite/bart_eli5''': 1_024,
}




class 		a__    (							snake_case_  ):





							'''simple docstring'''






							lowercase__      :       List[str]     						=				VOCAB_FILES_NAMES
							lowercase__      :       Union[str, Any]     						=				PRETRAINED_VOCAB_FILES_MAP
							lowercase__      :       Union[str, Any]     						=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase__      :       Union[str, Any]     						=				["input_ids", "attention_mask"]
							lowercase__      :       Any     						=				BartTokenizer







							def __init__(		self ,   lowerCamelCase_=None ,   lowerCamelCase_=None ,   lowerCamelCase_=None ,   lowerCamelCase_="replace" ,   lowerCamelCase_="<s>" ,   lowerCamelCase_="</s>" ,   lowerCamelCase_="</s>" ,   lowerCamelCase_="<s>" ,   lowerCamelCase_="<unk>" ,   lowerCamelCase_="<pad>" ,   lowerCamelCase_="<mask>" ,   lowerCamelCase_=False ,   lowerCamelCase_=True ,   **lowerCamelCase_ ,   )	->							Dict:
														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 ,   )

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

														lowerCAmelCase__	       =     add_prefix_space

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

																					lowerCAmelCase__	       =     False

																					if state.get('''add_prefix_space''' ,   _A       ) != add_prefix_space:
																												lowerCAmelCase__	       =     add_prefix_space
																												lowerCAmelCase__	       =     True

																					if state.get('''trim_offsets''' ,   _A       ) != trim_offsets:
																												lowerCAmelCase__	       =     trim_offsets
																												lowerCAmelCase__	       =     True

																					if changes_to_apply:
																												lowerCAmelCase__	       =     getattr(_A ,   state.pop('''type'''       )       )
																												lowerCAmelCase__	       =     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 ,   lowerCamelCase_       )	->							Tuple:
														lowerCAmelCase__	       =     AddedToken(_A ,   lstrip=_A ,   rstrip=_A       ) if isinstance(_A ,   _A       ) else value
														lowerCAmelCase__	       =     value







							def   __SCREAMING_SNAKE_CASE							(		self ,   *lowerCamelCase_ ,   **lowerCamelCase_       )	->							BatchEncoding:
														lowerCAmelCase__	       =     kwargs.get('''is_split_into_words''' ,   _A       )

														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(*_A ,   **_A       )







							def   __SCREAMING_SNAKE_CASE							(		self ,   *lowerCamelCase_ ,   **lowerCamelCase_       )	->							BatchEncoding:
														lowerCAmelCase__	       =     kwargs.get('''is_split_into_words''' ,   _A       )

														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(*_A ,   **_A       )







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_ ,   lowerCamelCase_ = None       )	->							Tuple[str]:
														lowerCAmelCase__	       =     self._tokenizer.model.save(_A ,   name=_A       )
														return tuple(_A       )







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_ ,   lowerCamelCase_=None       )	->							Optional[Any]:
														lowerCAmelCase__	       =     [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 ,   lowerCamelCase_ ,   lowerCamelCase_ = None       )	->							List[int]:
														lowerCAmelCase__	       =     [self.sep_token_id]
														lowerCAmelCase__	       =     [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'''






from __future__ import annotations


def  _snake_case       (					A			,   A	)						->   float:
							lowerCAmelCase__	       =     sorted(numsa + numsa	)
							lowerCAmelCase__       , lowerCAmelCase__	       =     divmod(len(A	)			,   2	)
							if mod == 1:
														return all_numbers[div]
							else:
														return (all_numbers[div] + all_numbers[div - 1]) / 2


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		__UpperCAmelCase       =							[float(x) for x in input('''Enter the elements of first array: ''').split()]
		__UpperCAmelCase       =							[float(x) for x in input('''Enter the elements of second array: ''').split()]
		print(f"""The median of two arrays is: {median_of_two_arrays(array_a, array_a)}""")