


"""simple docstring"""
from typing import Optional, Union

from ...file_utils import TensorType
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, TruncationStrategy





class   __A  (snake_case__):





							'''simple docstring'''

							__lowercase:		str				   =     """MarkupLMFeatureExtractor"""
							__lowercase:		Tuple				   =     ("""MarkupLMTokenizer""", """MarkupLMTokenizerFast""")
							__lowercase:		Tuple				   =     True



							def __call__(					self				:   List[Any]		,							UpperCAmelCase_				:   List[str]=None		,							UpperCAmelCase_				:   Any=None		,							UpperCAmelCase_				:   List[Any]=None		,							UpperCAmelCase_				:   int=None		,							UpperCAmelCase_				:   Optional[int]=None		,							UpperCAmelCase_				:   bool = True		,							UpperCAmelCase_				:   Union[bool, str, PaddingStrategy] = False		,							UpperCAmelCase_				:   Union[bool, str, TruncationStrategy] = None		,							UpperCAmelCase_				:   Optional[int] = None		,							UpperCAmelCase_				:   int = 0		,							UpperCAmelCase_				:   Optional[int] = None		,							UpperCAmelCase_				:   Optional[bool] = None		,							UpperCAmelCase_				:   Optional[bool] = None		,							UpperCAmelCase_				:   bool = False		,							UpperCAmelCase_				:   bool = False		,							UpperCAmelCase_				:   bool = False		,							UpperCAmelCase_				:   bool = False		,							UpperCAmelCase_				:   bool = True		,							UpperCAmelCase_				:   Optional[Union[str, TensorType]] = None		,							**UpperCAmelCase_				:   List[Any]		,							)       ->BatchEncoding:



														"""simple docstring"""



														if self.parse_html:
																					if html_strings is None:
																												raise ValueError("""Make sure to pass HTML strings in case `parse_html` is set to `True`"""							)

																					if nodes is not None or xpaths is not None or node_labels is not None:
																												raise ValueError(
																												    """Please don\'t pass nodes, xpaths nor node labels in case `parse_html` is set to `True`"""							)

																					snake_case_     							=		self.feature_extractor(UpperCamelCase_							)
																					snake_case_     							=		features['nodes']
																					snake_case_     							=		features['xpaths']
														else:
																					if html_strings is not None:
																												raise ValueError("""You have passed HTML strings but `parse_html` is set to `False`."""							)
																					if nodes is None or xpaths is None:
																												raise ValueError("""Make sure to pass nodes and xpaths in case `parse_html` is set to `False`"""							)

        # # second, apply the tokenizer
														if questions is not None and self.parse_html:
																					if isinstance(UpperCamelCase_		,							UpperCamelCase_							):
																												snake_case_     							=		[questions]  # add batch dimension (as the feature extractor always adds a batch dimension)

														snake_case_     							=		self.tokenizer(
														    text=questions if questions is not None else nodes		,							text_pair=nodes if questions is not None else None		,							xpaths=UpperCamelCase_		,							node_labels=UpperCamelCase_		,							add_special_tokens=UpperCamelCase_		,							padding=UpperCamelCase_		,							truncation=UpperCamelCase_		,							max_length=UpperCamelCase_		,							stride=UpperCamelCase_		,							pad_to_multiple_of=UpperCamelCase_		,							return_token_type_ids=UpperCamelCase_		,							return_attention_mask=UpperCamelCase_		,							return_overflowing_tokens=UpperCamelCase_		,							return_special_tokens_mask=UpperCamelCase_		,							return_offsets_mapping=UpperCamelCase_		,							return_length=UpperCamelCase_		,							verbose=UpperCamelCase_		,							return_tensors=UpperCamelCase_		,							**UpperCamelCase_		,							)

														return encoded_inputs



							def 		lowerCAmelCase							(					self				:   str		,							*UpperCAmelCase_				:   List[Any]		,							**UpperCAmelCase_				:   Tuple							)       ->Optional[Any]:



														"""simple docstring"""



														return self.tokenizer.batch_decode(*UpperCamelCase_		,							**UpperCamelCase_							)



							def 		lowerCAmelCase							(					self				:   List[Any]		,							*UpperCAmelCase_				:   Optional[int]		,							**UpperCAmelCase_				:   Dict							)       ->Optional[Any]:



														"""simple docstring"""



														return self.tokenizer.decode(*UpperCamelCase_		,							**UpperCamelCase_							)



							@property
							def 		lowerCAmelCase							(					self				:   Optional[int]							)       ->Any:



														"""simple docstring"""



														snake_case_     							=		self.tokenizer.model_input_names
														return tokenizer_input_names








'''simple docstring'''

from __future__ import annotations



class 		lowerCamelCase__   :




					'''simple docstring'''



					def __init__(	self					:						str  ,	UpperCamelCase_					:						int       )	->							None:



						'''simple docstring'''





						_lowercase       :							Any  	=		value
						_lowercase       :							Node | None  	=		None
						_lowercase       :							Node | None  	=		None






class 		lowerCamelCase__   :




					'''simple docstring'''



					A_         =    42




					def __init__(	self					:						List[Any]       )	->							None:



						'''simple docstring'''





						_lowercase       :							Optional[int]  	=		0




					def     __UpperCAmelCase  (	self					:						str  ,	UpperCamelCase_					:						Node | None  ,	UpperCamelCase_					:						int       )	->							None:



						'''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     __UpperCAmelCase  (	self					:						Optional[int]  ,	UpperCamelCase_					:						Node | None  ,	UpperCamelCase_					:						int | None = None       )	->							int:



						'''simple docstring'''





						if node is None:
							return 0
						if target is not None:
							_lowercase       :							Union[str, Any]  	=		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()
