
'''simple docstring'''






class     __snake_case		:
					def __init__(     self      ):

									"""simple docstring"""


									lowerCamelCase					:			dict[str, TrieNode]									= {}  # Mapping from char to TrieNode
									lowerCamelCase					:			Union[str, Any]									= False
					def     UpperCAmelCase_							(     self,    A      ):

									"""simple docstring"""


									for word in words:
													self.insert(A      )
					def     UpperCAmelCase_							(     self,    A      ):

									"""simple docstring"""


									lowerCamelCase					:			Optional[int]									= self
									for char in word:
													if char not in curr.nodes:
																	lowerCamelCase					:			Tuple									= TrieNode()
													lowerCamelCase					:			str									= curr.nodes[char]
									lowerCamelCase					:			List[str]									= True
					def     UpperCAmelCase_							(     self,    A      ):

									"""simple docstring"""


									lowerCamelCase					:			str									= self
									for char in word:
													if char not in curr.nodes:
																	return False
													lowerCamelCase					:			Optional[int]									= curr.nodes[char]
									return curr.is_leaf




					def     UpperCAmelCase_							(     self,    A      ):

									"""simple docstring"""


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

									_delete(self,    A,    0      )





def    UpperCAmelCase							(  UpperCAmelCase__							:							TrieNode       ,							UpperCAmelCase__							:							str):
				if node.is_leaf:
								print(UpperCAmelCase__       ,							end=' ')

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





def    UpperCAmelCase							(  ):
				lowerCamelCase					:			List[str]									= 'banana bananas bandana band apple all beast'.split()
				lowerCamelCase					:			List[str]									= TrieNode()
				root.insert_many(UpperCAmelCase__)
				# print_words(root, "")
				assert all(root.find(UpperCAmelCase__) 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    UpperCAmelCase							(  UpperCAmelCase__							:							str       ,							UpperCAmelCase__							:							bool):
				print(str(UpperCAmelCase__)       ,							'works!' if passes else 'doesn\'t work :(')





def    UpperCAmelCase							(  ):
				assert test_trie()





def    UpperCAmelCase							(  ):
				print_results('Testing trie functionality'       ,							test_trie())


if __name__ == "__main__":
					main()

'''simple docstring'''






from typing import TYPE_CHECKING

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


A			      =      {
    'configuration_clip': [
        'CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'CLIPConfig',
        'CLIPOnnxConfig',
        'CLIPTextConfig',
        'CLIPVisionConfig',
    ],
    'processing_clip': ['CLIPProcessor'],
    'tokenization_clip': ['CLIPTokenizer'],
}

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

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A			      =      ['CLIPFeatureExtractor']
					A			      =      ['CLIPImageProcessor']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A			      =      [
					    'CLIP_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'CLIPModel',
					    'CLIPPreTrainedModel',
					    'CLIPTextModel',
					    'CLIPTextModelWithProjection',
					    'CLIPVisionModel',
					    'CLIPVisionModelWithProjection',
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A			      =      [
					    'TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'TFCLIPModel',
					    'TFCLIPPreTrainedModel',
					    'TFCLIPTextModel',
					    'TFCLIPVisionModel',
					]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A			      =      [
					    'FlaxCLIPModel',
					    'FlaxCLIPPreTrainedModel',
					    'FlaxCLIPTextModel',
					    'FlaxCLIPTextPreTrainedModel',
					    'FlaxCLIPVisionModel',
					    'FlaxCLIPVisionPreTrainedModel',
					]


if TYPE_CHECKING:
					from .configuration_clip import (
					    CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    CLIPConfig,
					    CLIPOnnxConfig,
					    CLIPTextConfig,
					    CLIPVisionConfig,
					)
					from .processing_clip import CLIPProcessor
					from .tokenization_clip import CLIPTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_clip_fast import CLIPTokenizerFast

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_clip import CLIPFeatureExtractor
										from .image_processing_clip import CLIPImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_clip import (
										    CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
										    CLIPModel,
										    CLIPPreTrainedModel,
										    CLIPTextModel,
										    CLIPTextModelWithProjection,
										    CLIPVisionModel,
										    CLIPVisionModelWithProjection,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_clip import (
										    TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFCLIPModel,
										    TFCLIPPreTrainedModel,
										    TFCLIPTextModel,
										    TFCLIPVisionModel,
										)

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_clip import (
										    FlaxCLIPModel,
										    FlaxCLIPPreTrainedModel,
										    FlaxCLIPTextModel,
										    FlaxCLIPTextPreTrainedModel,
										    FlaxCLIPVisionModel,
										    FlaxCLIPVisionPreTrainedModel,
										)


else:
					import sys

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