
"""simple docstring"""


from __future__ import annotations







class 	lowerCamelCase__      :





			'''simple docstring'''



			def __init__(							self  ,  __UpperCAmelCase						)				->  None:
				_lowerCAmelCase			=value
				_lowerCAmelCase			=None
				_lowerCAmelCase			=None







class 	lowerCamelCase__      :





			'''simple docstring'''
			lowerCamelCase						      =	42



			def __init__(							self						)				->  None:
				_lowerCAmelCase			=0



			def       _lowerCAmelCase	(							self  ,  __UpperCAmelCase  ,  __UpperCAmelCase						)				->  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       _lowerCAmelCase	(							self  ,  __UpperCAmelCase  ,  __UpperCAmelCase = None						)				->  int:
				if node is None:
					return 0
				if target is not None:
					_lowerCAmelCase			=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()





"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__A 		= {
    'configuration_led': ['LED_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LEDConfig'],
    'tokenization_led': ['LEDTokenizer'],
}

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__A 		= ['LEDTokenizerFast']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__A 		= [
			    'LED_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'LEDForConditionalGeneration',
			    'LEDForQuestionAnswering',
			    'LEDForSequenceClassification',
			    'LEDModel',
			    'LEDPreTrainedModel',
			]


try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__A 		= ['TFLEDForConditionalGeneration', 'TFLEDModel', 'TFLEDPreTrainedModel']


if TYPE_CHECKING:
			from .configuration_led import LED_PRETRAINED_CONFIG_ARCHIVE_MAP, LEDConfig
			from .tokenization_led import LEDTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_led_fast import LEDTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_led import (
						    LED_PRETRAINED_MODEL_ARCHIVE_LIST,
						    LEDForConditionalGeneration,
						    LEDForQuestionAnswering,
						    LEDForSequenceClassification,
						    LEDModel,
						    LEDPreTrainedModel,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_led import TFLEDForConditionalGeneration, TFLEDModel, TFLEDPreTrainedModel

else:
			import sys

			__A 		= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



