code: 
  
  
  '''simple docstring'''
  
  
  
  
  def 							a_       (						lowercase							,						lowercase    )			->List[str]:
  
  
  
  
  
  
  				'''simple docstring'''
  
  				if not root or root not in binary_tree_mirror_dictionary:
  								return
  				__lowerCamelCase						,					__lowerCamelCase		:      List[str]											=					binary_tree_mirror_dictionary[root][:2]
  				__lowerCamelCase		:      Dict											=					[right_child, left_child]
  				binary_tree_mirror_dict(lowercase							,						lowercase    )
  				binary_tree_mirror_dict(lowercase							,						lowercase    )
  
  
  
  
  
  def 							a_       (						lowercase							,						lowercase = 1    )			->dict:
  
  
  
  
  
  
  				'''simple docstring'''
  
  				if not binary_tree:
  								raise ValueError("binary tree cannot be empty"    )
  				if root not in binary_tree:
  								__lowerCamelCase		:      int											=					F'root {root} is not present in the binary_tree'
  								raise ValueError(lowercase    )
  				__lowerCamelCase		:      Union[str, Any]											=					dict(lowercase    )
  				binary_tree_mirror_dict(lowercase							,						lowercase    )
  				return binary_tree_mirror_dictionary
  
  
  if __name__ == "__main__":
  				__lowercase  :      int      		=				{1: [2, 3], 2: [4, 5], 3: [6, 7], 7: [8, 9]}
  				print(f"Binary tree: {binary_tree}")
  				__lowercase  :      Optional[int]      		=				binary_tree_mirror(binary_tree, 5)
  				print(f"Binary tree mirror: {binary_tree_mirror_dictionary}")
  
  
  
  
  
  
style_context: 
  
  
  '''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
  
  
  __lowercase  :      str      		=				logging.get_logger(__name__)
  
  __lowercase  :      Any      		=				{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}
  
  __lowercase  :      Optional[Any]      		=				{
      """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"""
          ),
      },
  }
  
  __lowercase  :      Tuple      		=				{
      """allenai/longformer-base-4096""": 40_96,
      """allenai/longformer-large-4096""": 40_96,
      """allenai/longformer-large-4096-finetuned-triviaqa""": 40_96,
      """allenai/longformer-base-4096-extra.pos.embd.only""": 40_96,
      """allenai/longformer-large-4096-extra.pos.embd.only""": 40_96,
  }
  
  
  
  
  
  class _snake_case   ( a__   ):
  							"""simple docstring"""
  
  
  
  
  
  							__a												=     VOCAB_FILES_NAMES
  							__a												=     PRETRAINED_VOCAB_FILES_MAP
  							__a												=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  							__a												=     ['''input_ids''', '''attention_mask''']
  							__a												=     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			,				)     ->Dict:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											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		:      int											=					json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()	)
  											if pre_tok_state.get("add_prefix_space"			,				__A	) != add_prefix_space:
  															__lowerCamelCase		:      Any											=					getattr(__A			,				pre_tok_state.pop("type"	)	)
  															__lowerCamelCase		:      Any											=					add_prefix_space
  															__lowerCamelCase		:      Union[str, Any]											=					pre_tok_class(**__A	)
  
  											__lowerCamelCase		:      Any											=					add_prefix_space
  
  											__lowerCamelCase		:      int											=					"post_processor"
  											__lowerCamelCase		:      Optional[int]											=					getattr(self.backend_tokenizer			,				__A			,				__A	)
  											if tokenizer_component_instance:
  															__lowerCamelCase		:      Tuple											=					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		:      Dict											=					tuple(state["sep"]	)
  															if "cls" in state:
  																			__lowerCamelCase		:      Union[str, Any]											=					tuple(state["cls"]	)
  
  															__lowerCamelCase		:      Union[str, Any]											=					False
  
  															if state.get("add_prefix_space"			,				__A	) != add_prefix_space:
  																			__lowerCamelCase		:      Dict											=					add_prefix_space
  																			__lowerCamelCase		:      str											=					True
  
  															if state.get("trim_offsets"			,				__A	) != trim_offsets:
  																			__lowerCamelCase		:      Tuple											=					trim_offsets
  																			__lowerCamelCase		:      Optional[int]											=					True
  
  															if changes_to_apply:
  																			__lowerCamelCase		:      List[Any]											=					getattr(__A			,				state.pop("type"	)	)
  																			__lowerCamelCase		:      int											=					component_class(**__A	)
  																			setattr(self.backend_tokenizer			,				__A			,				__A	)
  
  
  
  
  
  
  
  							@property
  							def 		__SCREAMING_SNAKE_CASE(   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 		__SCREAMING_SNAKE_CASE(   self			,				__A	)     ->int:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											__lowerCamelCase		:      List[Any]											=					AddedToken(__A			,				lstrip=__A			,				rstrip=__A	) if isinstance(__A			,				__A	) else value
  											__lowerCamelCase		:      Optional[int]											=					value
  
  
  
  
  
  
  
  							def 		__SCREAMING_SNAKE_CASE(   self			,				*__A			,				**__A	)     ->BatchEncoding:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											__lowerCamelCase		:      Optional[int]											=					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:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											__lowerCamelCase		:      str											=					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]:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											__lowerCamelCase		:      List[str]											=					self._tokenizer.model.save(__A			,				name=__A	)
  											return tuple(__A	)
  
  
  
  
  
  
  
  							def 		__SCREAMING_SNAKE_CASE(   self			,				__A			,				__A=None	)     ->Union[str, Any]:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											__lowerCamelCase		:      Any											=					[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]:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											__lowerCamelCase		:      List[str]											=					[self.sep_token_id]
  											__lowerCamelCase		:      Tuple											=					[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]
  
  
  
  
  
  