code: from __future__ import annotations
  
  
  
  class        lowerCAmelCase_	:
         def __init__(    self,    SCREAMING_SNAKE_CASE_ )  ->	None:
            UpperCamelCase					:						Any					=			value
            UpperCamelCase					:						Node | None					=			None
            UpperCamelCase					:						Node | None					=			None
  
  
  
  
  
  
  class        lowerCAmelCase_	:
         UpperCAmelCase__       :      int
         def __init__(    self )  ->	None:
            UpperCamelCase					:						Optional[Any]					=			0
         def       snake_case_ (    self,    SCREAMING_SNAKE_CASE_,    SCREAMING_SNAKE_CASE_ )  ->	None:
            if node is None:
               return
  
            if path_sum == self.target:
               self.paths += 1
  
            if node.left:
               self.depth_first_search(node.left,    path_sum + node.left.value )
            if node.right:
               self.depth_first_search(node.right,    path_sum + node.right.value )
  
  
  
  
  
  
         def       snake_case_ (    self,    SCREAMING_SNAKE_CASE_,    SCREAMING_SNAKE_CASE_ = None )  ->	int:
            if node is None:
               return 0
            if target is not None:
               UpperCamelCase					:						Union[str, Any]					=			target
  
            self.depth_first_search(SCREAMING_SNAKE_CASE_,    node.value )
            self.path_sum(node.left )
            self.path_sum(node.right )
  
            return self.paths
  
  
  if __name__ == "__main__":
      import doctest
  
      doctest.testmod()
  
  
  
  
style_context: 
  
  
  
  from typing import Optional, Tuple
  
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import logging
  from .tokenization_openai import OpenAIGPTTokenizer
  
  
  __UpperCAmelCase      = logging.get_logger(__name__)
  
  __UpperCAmelCase      = {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}
  
  __UpperCAmelCase      = {
      '''vocab_file''': {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/vocab.json'''},
      '''merges_file''': {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/merges.txt'''},
      '''tokenizer_file''': {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/tokenizer.json'''},
  }
  
  __UpperCAmelCase      = {
      '''openai-gpt''': 512,
  }
  
  
  
  class        lowerCAmelCase_	(						a__							):
         UpperCAmelCase__       :      Union[str, Any]       =						VOCAB_FILES_NAMES
         UpperCAmelCase__       :      int       =						PRETRAINED_VOCAB_FILES_MAP
         UpperCAmelCase__       :      Optional[int]       =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
         UpperCAmelCase__       :      Optional[int]       =						["input_ids", "attention_mask"]
         UpperCAmelCase__       :      Tuple       =						OpenAIGPTTokenizer
         def __init__(    self,    SCREAMING_SNAKE_CASE_=None,    SCREAMING_SNAKE_CASE_=None,    SCREAMING_SNAKE_CASE_=None,    SCREAMING_SNAKE_CASE_="<unk>",    **SCREAMING_SNAKE_CASE_ )  ->	List[str]:
            super().__init__(SCREAMING_SNAKE_CASE_,    SCREAMING_SNAKE_CASE_,    tokenizer_file=SCREAMING_SNAKE_CASE_,    unk_token=SCREAMING_SNAKE_CASE_,    **SCREAMING_SNAKE_CASE_ )
         @property
         def       snake_case_ (    self )  ->	Dict:
            return True
  
  
  
  
  
  
         def       snake_case_ (    self,    SCREAMING_SNAKE_CASE_,    SCREAMING_SNAKE_CASE_ = None )  ->	Tuple[str]:
            UpperCamelCase					:						List[Any]					=			self._tokenizer.model.save(SCREAMING_SNAKE_CASE_,    name=SCREAMING_SNAKE_CASE_ )
            return tuple(SCREAMING_SNAKE_CASE_ )
  
  
  
  