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()








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_ )



