"""simple docstring"""


from typing import TYPE_CHECKING

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


a							={
    "configuration_deberta_v2": ["DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP", "DebertaV2Config", "DebertaV2OnnxConfig"],
    "tokenization_deberta_v2": ["DebertaV2Tokenizer"],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a							=["DebertaV2TokenizerFast"]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a							=[
	    "TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "TFDebertaV2ForMaskedLM",
	    "TFDebertaV2ForQuestionAnswering",
	    "TFDebertaV2ForSequenceClassification",
	    "TFDebertaV2ForTokenClassification",
	    "TFDebertaV2Model",
	    "TFDebertaV2PreTrainedModel",
	]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a							=[
	    "DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "DebertaV2ForMaskedLM",
	    "DebertaV2ForMultipleChoice",
	    "DebertaV2ForQuestionAnswering",
	    "DebertaV2ForSequenceClassification",
	    "DebertaV2ForTokenClassification",
	    "DebertaV2Model",
	    "DebertaV2PreTrainedModel",
	]


if TYPE_CHECKING:
	from .configuration_deberta_va import (
	    DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    DebertaVaConfig,
	    DebertaVaOnnxConfig,
	)
	from .tokenization_deberta_va import DebertaVaTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_deberta_va_fast import DebertaVaTokenizerFast

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_deberta_va import (
		    TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFDebertaVaForMaskedLM,
		    TFDebertaVaForQuestionAnswering,
		    TFDebertaVaForSequenceClassification,
		    TFDebertaVaForTokenClassification,
		    TFDebertaVaModel,
		    TFDebertaVaPreTrainedModel,
		)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_deberta_va import (
		    DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DebertaVaForMaskedLM,
		    DebertaVaForMultipleChoice,
		    DebertaVaForQuestionAnswering,
		    DebertaVaForSequenceClassification,
		    DebertaVaForTokenClassification,
		    DebertaVaModel,
		    DebertaVaPreTrainedModel,
		)

else:
	import sys

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



"""simple docstring"""


class        __UpperCAmelCase						:

				def __init__(				self     ,			_lowerCamelCase				):
										lowerCamelCase__ =data
										lowerCamelCase__ =None
										lowerCamelCase__ =None





def       lowerCamelCase_			( __lowerCAmelCase       ,   __lowerCAmelCase    )							-> BinaryTreeNode | None:




						'''simple docstring'''



						if node is None:
												lowerCamelCase__ =BinaryTreeNode(__lowerCAmelCase    )
												return node

						# binary search tree is not empty,
						# so we will insert it into the tree
						# if new_value is less than value of data in node,
						#  add it to left subtree and proceed recursively
						if new_value < node.data:
												lowerCamelCase__ =insert(node.left_child       ,   __lowerCAmelCase    )
						else:
												# if new_value is greater than value of data in node,
												#  add it to right subtree and proceed recursively
												lowerCamelCase__ =insert(node.right_child       ,   __lowerCAmelCase    )
						return node





def       lowerCamelCase_			( __lowerCAmelCase    )							-> list[int]:  # if node is None,return




						'''simple docstring'''



						if node:
												lowerCamelCase__ =inorder(node.left_child    )
												lowerCamelCase__ =[*inorder_array, node.data]
												lowerCamelCase__ =inorder_array + inorder(node.right_child    )
						else:
												lowerCamelCase__ =[]
						return inorder_array





def       lowerCamelCase_			( )							-> BinaryTreeNode | None:




						'''simple docstring'''



						lowerCamelCase__ =insert(__lowerCAmelCase       ,   15    )
						insert(__lowerCAmelCase       ,   10    )
						insert(__lowerCAmelCase       ,   25    )
						insert(__lowerCAmelCase       ,   6    )
						insert(__lowerCAmelCase       ,   14    )
						insert(__lowerCAmelCase       ,   20    )
						insert(__lowerCAmelCase       ,   60    )
						return root





def       lowerCamelCase_			( )							-> None:




						'''simple docstring'''



						lowerCamelCase__ =make_tree()
						print("Printing values of binary search tree in Inorder Traversal."    )
						inorder(__lowerCAmelCase    )


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	main()


