


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


lowerCamelCase__							:						List[Any]							     =   logging.get_logger(__name__)


lowerCamelCase__							:						Optional[int]							     =   {"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

# See all BART models at https://huggingface.co/models?filter=bart
lowerCamelCase__							:						Optional[Any]							     =   {
    """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""",
    },
}

lowerCamelCase__							:						Dict							     =   {
    """facebook/bart-base""": 1_0_2_4,
    """facebook/bart-large""": 1_0_2_4,
    """facebook/bart-large-mnli""": 1_0_2_4,
    """facebook/bart-large-cnn""": 1_0_2_4,
    """facebook/bart-large-xsum""": 1_0_2_4,
    """yjernite/bart_eli5""": 1_0_2_4,
}
class 		__magic_name__						(snake_case_				):





     '''simple docstring'''



     __lowercase				:							int	   =       VOCAB_FILES_NAMES
     __lowercase				:							List[str]	   =       PRETRAINED_VOCAB_FILES_MAP
     __lowercase				:							Tuple	   =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __lowercase				:							int	   =       ['input_ids', 'attention_mask']
     __lowercase				:							int	   =       BartTokenizer

     def __init__(					self:int     ,		_a:Any=None     ,		_a:Dict=None     ,		_a:Any=None     ,		_a:str="replace"     ,		_a:Dict="<s>"     ,		_a:Any="</s>"     ,		_a:List[str]="</s>"     ,		_a:Optional[Any]="<s>"     ,		_a:List[Any]="<unk>"     ,		_a:Optional[Any]="<pad>"     ,		_a:str="<mask>"     ,		_a:Tuple=False     ,		_a:Optional[Any]=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     ,		)

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

       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     ,		_a     ,		_a   )
       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'''     ,		_a   ) != add_prefix_space:
           snake_case__						= add_prefix_space
           snake_case__						= True

         if state.get('''trim_offsets'''     ,		_a   ) != trim_offsets:
           snake_case__						= trim_offsets
           snake_case__						= True

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

     @property
     def 	SCREAMING_SNAKE_CASE__						(					self:Any   ):
       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:Optional[int]     ,		_a:Union[str, Any]   ):
       snake_case__						= AddedToken(_a     ,		lstrip=_a     ,		rstrip=_a   ) if isinstance(_a     ,		_a   ) else value
       snake_case__						= value

     def 	SCREAMING_SNAKE_CASE__						(					self:Tuple     ,		*_a:int     ,		**_a:Tuple   ):
       snake_case__						= 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:str     ,		*_a:Dict     ,		**_a:Tuple   ):
       snake_case__						= 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:str     ,		_a:str     ,		_a:Optional[str] = None   ):
       snake_case__						= self._tokenizer.model.save(_a     ,		name=_a   )
       return tuple(_a   )

     def 	SCREAMING_SNAKE_CASE__						(					self:Optional[int]     ,		_a:Optional[int]     ,		_a:Tuple=None   ):
       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 	SCREAMING_SNAKE_CASE__						(					self:str     ,		_a:List[int]     ,		_a:Optional[List[int]] = None   ):
       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]







from __future__ import annotations

from dataclasses import dataclass
@dataclass
class 						UpperCAmelCase  :







						'''simple docstring'''





						lowerCAmelCase_							=  42
						lowerCAmelCase_							=  None
						lowerCAmelCase_							=  None







def 		lowerCamelCase__       (						_A				):







	'''simple docstring'''





	def is_valid_tree(_A				) -> bool:
		if node is None:
			return True

		if not isinstance(_A	,      _A				):
			return False

		try:
			float(node.data				)
		except (TypeError, ValueError):
			return False

		return is_valid_tree(node.left				) and is_valid_tree(node.right				)

	if not is_valid_tree(_A				):
		raise ValueError(
		    "Each node should be type of TreeNode and data should be float."				)

	def is_binary_search_tree_recursive_check(
	    _A	,      _A	,      _A				) -> bool:

		if node is None:
			return True

		return (
		    left_bound < node.data < right_bound
		    and is_binary_search_tree_recursive_check(node.left	,      _A	,      node.data				)
		    and is_binary_search_tree_recursive_check(
		        node.right	,      node.data	,      _A				)
		)

	return is_binary_search_tree_recursive_check(_A	,      -float("inf"				)	,      float("inf"				)				)


if __name__ == "__main__":
		import doctest

		doctest.testmod()
