

from __future__ import annotations

class 					__UpperCamelCase					:







	def __init__( self:			int	,			__UpperCamelCase:			int   ):

						'''simple docstring'''





						__magic_name__				=     value
						__magic_name__				=     None
						__magic_name__				=     None




class 					__UpperCamelCase					:
	_lowercase	: int







	def __init__( self:			List[Any]   ):

						'''simple docstring'''





						__magic_name__				=     0







	def 						_SCREAMING_SNAKE_CASE				( self:			Any	,			__UpperCamelCase:			Node | None	,			__UpperCamelCase:			int   ):

						'''simple docstring'''





						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 						_SCREAMING_SNAKE_CASE				( self:			Optional[Any]	,			__UpperCamelCase:			Node | None	,			__UpperCamelCase:			int | None = None   ):

						'''simple docstring'''





						if node is None:
											return 0
						if target is not None:
											__magic_name__				=     target

						self.depth_first_search(__UpperCamelCase	,			node.value   )
						self.path_sum(node.left   )
						self.path_sum(node.right   )

						return self.paths


if __name__ == "__main__":
						import doctest

						doctest.testmod()







from ...configuration_utils import PretrainedConfig
from ...utils import logging


A__							=				logging.get_logger(__name__)

A__							=				{
    "tau/splinter-base": "https://huggingface.co/tau/splinter-base/resolve/main/config.json",
    "tau/splinter-base-qass": "https://huggingface.co/tau/splinter-base-qass/resolve/main/config.json",
    "tau/splinter-large": "https://huggingface.co/tau/splinter-large/resolve/main/config.json",
    "tau/splinter-large-qass": "https://huggingface.co/tau/splinter-large-qass/resolve/main/config.json",
    # See all Splinter models at https://huggingface.co/models?filter=splinter
}

class 					__UpperCamelCase					(       SCREAMING_SNAKE_CASE      ):
	_lowercase	: int												=	"splinter"







	def __init__( self:			str	,			__UpperCamelCase:			Any=3_05_22	,			__UpperCamelCase:			List[Any]=7_68	,			__UpperCamelCase:			str=12	,			__UpperCamelCase:			Optional[Any]=12	,			__UpperCamelCase:			Optional[int]=30_72	,			__UpperCamelCase:			List[str]="gelu"	,			__UpperCamelCase:			Union[str, Any]=0.1	,			__UpperCamelCase:			Dict=0.1	,			__UpperCamelCase:			str=5_12	,			__UpperCamelCase:			Dict=2	,			__UpperCamelCase:			str=0.02	,			__UpperCamelCase:			Tuple=1E-12	,			__UpperCamelCase:			Optional[int]=True	,			__UpperCamelCase:			Union[str, Any]=0	,			__UpperCamelCase:			Optional[int]=1_04	,			**__UpperCamelCase:			Tuple	,			):

						'''simple docstring'''





						super().__init__(pad_token_id=__UpperCamelCase	,			**__UpperCamelCase   )

						__magic_name__				=     vocab_size
						__magic_name__				=     max_position_embeddings
						__magic_name__				=     hidden_size
						__magic_name__				=     num_hidden_layers
						__magic_name__				=     num_attention_heads
						__magic_name__				=     intermediate_size
						__magic_name__				=     hidden_act
						__magic_name__				=     hidden_dropout_prob
						__magic_name__				=     attention_probs_dropout_prob
						__magic_name__				=     initializer_range
						__magic_name__				=     type_vocab_size
						__magic_name__				=     layer_norm_eps
						__magic_name__				=     use_cache
						__magic_name__				=     question_token_id




