



'''simple docstring'''

from typing import TYPE_CHECKING

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


UpperCAmelCase     		=   {
    'configuration_bert': ['BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BertConfig', 'BertOnnxConfig'],
    'tokenization_bert': ['BasicTokenizer', 'BertTokenizer', 'WordpieceTokenizer'],
}

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

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase     		=   [
				    'BERT_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'BertForMaskedLM',
				    'BertForMultipleChoice',
				    'BertForNextSentencePrediction',
				    'BertForPreTraining',
				    'BertForQuestionAnswering',
				    'BertForSequenceClassification',
				    'BertForTokenClassification',
				    'BertLayer',
				    'BertLMHeadModel',
				    'BertModel',
				    'BertPreTrainedModel',
				    'load_tf_weights_in_bert',
				]

try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase     		=   [
				    'TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'TFBertEmbeddings',
				    'TFBertForMaskedLM',
				    'TFBertForMultipleChoice',
				    'TFBertForNextSentencePrediction',
				    'TFBertForPreTraining',
				    'TFBertForQuestionAnswering',
				    'TFBertForSequenceClassification',
				    'TFBertForTokenClassification',
				    'TFBertLMHeadModel',
				    'TFBertMainLayer',
				    'TFBertModel',
				    'TFBertPreTrainedModel',
				]
try:
				if not is_tensorflow_text_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase     		=   ['TFBertTokenizer']

try:
				if not is_flax_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase     		=   [
				    'FlaxBertForCausalLM',
				    'FlaxBertForMaskedLM',
				    'FlaxBertForMultipleChoice',
				    'FlaxBertForNextSentencePrediction',
				    'FlaxBertForPreTraining',
				    'FlaxBertForQuestionAnswering',
				    'FlaxBertForSequenceClassification',
				    'FlaxBertForTokenClassification',
				    'FlaxBertModel',
				    'FlaxBertPreTrainedModel',
				]

if TYPE_CHECKING:
				from .configuration_bert import BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, BertConfig, BertOnnxConfig
				from .tokenization_bert import BasicTokenizer, BertTokenizer, WordpieceTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_bert_fast import BertTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_bert import (
								    BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    BertForMaskedLM,
								    BertForMultipleChoice,
								    BertForNextSentencePrediction,
								    BertForPreTraining,
								    BertForQuestionAnswering,
								    BertForSequenceClassification,
								    BertForTokenClassification,
								    BertLayer,
								    BertLMHeadModel,
								    BertModel,
								    BertPreTrainedModel,
								    load_tf_weights_in_bert,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_bert import (
								    TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    TFBertEmbeddings,
								    TFBertForMaskedLM,
								    TFBertForMultipleChoice,
								    TFBertForNextSentencePrediction,
								    TFBertForPreTraining,
								    TFBertForQuestionAnswering,
								    TFBertForSequenceClassification,
								    TFBertForTokenClassification,
								    TFBertLMHeadModel,
								    TFBertMainLayer,
								    TFBertModel,
								    TFBertPreTrainedModel,
								)

				try:
								if not is_tensorflow_text_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_bert_tf import TFBertTokenizer

				try:
								if not is_flax_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_flax_bert import (
								    FlaxBertForCausalLM,
								    FlaxBertForMaskedLM,
								    FlaxBertForMultipleChoice,
								    FlaxBertForNextSentencePrediction,
								    FlaxBertForPreTraining,
								    FlaxBertForQuestionAnswering,
								    FlaxBertForSequenceClassification,
								    FlaxBertForTokenClassification,
								    FlaxBertModel,
								    FlaxBertPreTrainedModel,
								)

else:
				import sys

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




'''simple docstring'''

class __snake_case:


						'''simple docstring'''



						def __init__( self				)     ->     None:
							lowerCAmelCase   =     {}  # Mapping from char to TrieNode
							lowerCAmelCase   =     False


						def     __snake_case   ( self     ,	A_				)     ->     None:
							for word in words:
								self.insert(A_				)


						def     __snake_case   ( self     ,	A_				)     ->     None:
							lowerCAmelCase   =     self
							for char in word:
								if char not in curr.nodes:
									lowerCAmelCase   =     TrieNode()
								lowerCAmelCase   =     curr.nodes[char]
							lowerCAmelCase   =     True


						def     __snake_case   ( self     ,	A_				)     ->     bool:
							lowerCAmelCase   =     self
							for char in word:
								if char not in curr.nodes:
									return False
								lowerCAmelCase   =     curr.nodes[char]
							return curr.is_leaf




						def     __snake_case   ( self     ,	A_				)     ->     None:

							def _delete(A_     ,	A_     ,	A_				) -> bool:
								if index == len(A_				):
									# If word does not exist
									if not curr.is_leaf:
										return False
									lowerCAmelCase   =     False
									return len(curr.nodes				) == 0
								lowerCAmelCase   =     word[index]
								lowerCAmelCase   =     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   =     _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 		_snake_case		( _SCREAMING_SNAKE_CASE					:						TrieNode							,		_SCREAMING_SNAKE_CASE					:						str							)      ->						None:







	"""simple docstring"""
	if node.is_leaf:
		print(_SCREAMING_SNAKE_CASE							,		end=""" """							)

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






def 		_snake_case		( )      ->						bool:







	"""simple docstring"""
	lowerCAmelCase   =     """banana bananas bandana band apple all beast""".split()
	lowerCAmelCase   =     TrieNode()
	root.insert_many(_SCREAMING_SNAKE_CASE							)
	# print_words(root, "")
	assert all(root.find(_SCREAMING_SNAKE_CASE							) 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 		_snake_case		( _SCREAMING_SNAKE_CASE					:						str							,		_SCREAMING_SNAKE_CASE					:						bool							)      ->						None:







	"""simple docstring"""
	print(str(_SCREAMING_SNAKE_CASE							)							,		"""works!""" if passes else """doesn't work :("""							)






def 		_snake_case		( )      ->						None:







	"""simple docstring"""
	assert test_trie()






def 		_snake_case		( )      ->						None:







	"""simple docstring"""
	print_results("""Testing trie functionality"""							,		test_trie()							)


if __name__ == "__main__":
				main()