
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__a  			=					{
    'configuration_conditional_detr': [
        'CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'ConditionalDetrConfig',
        'ConditionalDetrOnnxConfig',
    ]
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a  			=					['ConditionalDetrFeatureExtractor']
						__a  			=					['ConditionalDetrImageProcessor']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a  			=					[
						    'CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'ConditionalDetrForObjectDetection',
						    'ConditionalDetrForSegmentation',
						    'ConditionalDetrModel',
						    'ConditionalDetrPreTrainedModel',
						]


if TYPE_CHECKING:
						from .configuration_conditional_detr import (
						    CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    ConditionalDetrConfig,
						    ConditionalDetrOnnxConfig,
						)

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_conditional_detr import ConditionalDetrFeatureExtractor
												from .image_processing_conditional_detr import ConditionalDetrImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_conditional_detr import (
												    CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
												    ConditionalDetrForObjectDetection,
												    ConditionalDetrForSegmentation,
												    ConditionalDetrModel,
												    ConditionalDetrPreTrainedModel,
												)

else:
						import sys

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












class __lowerCamelCase :





	"""simple docstring"""






	def __init__(							self    ):
							"""simple docstring"""







							_UpperCAmelCase									=			{}  # Mapping from char to TrieNode
							_UpperCAmelCase									=			False

	def        UpperCamelCase    (							self       ,    UpperCAmelCase    ):
							"""simple docstring"""







							for word in words:
													self.insert(UpperCAmelCase    )

	def        UpperCamelCase    (							self       ,    UpperCAmelCase    ):
							"""simple docstring"""







							_UpperCAmelCase									=			self
							for char in word:
													if char not in curr.nodes:
																			_UpperCAmelCase									=			TrieNode()
													_UpperCAmelCase									=			curr.nodes[char]
							_UpperCAmelCase									=			True

	def        UpperCamelCase    (							self       ,    UpperCAmelCase    ):
							"""simple docstring"""







							_UpperCAmelCase									=			self
							for char in word:
													if char not in curr.nodes:
																			return False
													_UpperCAmelCase									=			curr.nodes[char]
							return curr.is_leaf

	def        UpperCamelCase    (							self       ,    UpperCAmelCase    ):
							"""simple docstring"""







							def _delete(UpperCAmelCase       ,    UpperCAmelCase       ,    UpperCAmelCase    ) -> bool:
													if index == len(UpperCAmelCase    ):
																			# If word does not exist
																			if not curr.is_leaf:
																									return False
																			_UpperCAmelCase									=			False
																			return len(curr.nodes    ) == 0
													_UpperCAmelCase									=			word[index]
													_UpperCAmelCase									=			curr.nodes.get(UpperCAmelCase    )
													# If char not in current trie node
													if not char_node:
																			return False
													# Flag to check if node can be deleted
													_UpperCAmelCase									=			_delete(UpperCAmelCase       ,    UpperCAmelCase       ,    index + 1    )
													if delete_curr:
																			del curr.nodes[char]
																			return len(curr.nodes    ) == 0
													return delete_curr

							_delete(self       ,    UpperCAmelCase       ,    0    )



def __A    (      __lowerCAmelCase ,		__lowerCAmelCase	)->  None:





						"""simple docstring"""



						if node.is_leaf:
												print(__lowerCAmelCase ,		end=' '	)

						for key, value in node.nodes.items():
												print_words(__lowerCAmelCase ,		word + key	)


def __A    (      )->  bool:





						"""simple docstring"""



						_UpperCAmelCase									=			'banana bananas bandana band apple all beast'.split()
						_UpperCAmelCase									=			TrieNode()
						root.insert_many(__lowerCAmelCase	)
						# print_words(root, "")
						assert all(root.find(__lowerCAmelCase	) for word in words	)
						assert root.find('banana'	)
						assert not root.find('bandanas'	)
						assert not root.find('apps'	)
						assert root.find('apple'	)
						assert root.find('all'	)
						root.delete('all'	)
						assert not root.find('all'	)
						root.delete('banana'	)
						assert not root.find('banana'	)
						assert root.find('bananas'	)
						return True


def __A    (      __lowerCAmelCase ,		__lowerCAmelCase	)->  None:





						"""simple docstring"""



						print(str(__lowerCAmelCase	) ,		'works!' if passes else 'doesn\'t work :('	)


def __A    (      )->  None:





						"""simple docstring"""



						assert test_trie()


def __A    (      )->  None:





						"""simple docstring"""



						print_results('Testing trie functionality' ,		test_trie()	)


if __name__ == "__main__":
		main()
