


'''simple docstring'''





from typing import TYPE_CHECKING

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


__lowerCamelCase												=						{
    '''configuration_distilbert''': [
        '''DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''DistilBertConfig''',
        '''DistilBertOnnxConfig''',
    ],
    '''tokenization_distilbert''': ['''DistilBertTokenizer'''],
}

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

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase												=						[
        '''DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''DistilBertForMaskedLM''',
        '''DistilBertForMultipleChoice''',
        '''DistilBertForQuestionAnswering''',
        '''DistilBertForSequenceClassification''',
        '''DistilBertForTokenClassification''',
        '''DistilBertModel''',
        '''DistilBertPreTrainedModel''',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase												=						[
        '''TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''TFDistilBertForMaskedLM''',
        '''TFDistilBertForMultipleChoice''',
        '''TFDistilBertForQuestionAnswering''',
        '''TFDistilBertForSequenceClassification''',
        '''TFDistilBertForTokenClassification''',
        '''TFDistilBertMainLayer''',
        '''TFDistilBertModel''',
        '''TFDistilBertPreTrainedModel''',
    ]

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase												=						[
        '''FlaxDistilBertForMaskedLM''',
        '''FlaxDistilBertForMultipleChoice''',
        '''FlaxDistilBertForQuestionAnswering''',
        '''FlaxDistilBertForSequenceClassification''',
        '''FlaxDistilBertForTokenClassification''',
        '''FlaxDistilBertModel''',
        '''FlaxDistilBertPreTrainedModel''',
    ]


if TYPE_CHECKING:
    from .configuration_distilbert import (
        DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
        DistilBertConfig,
        DistilBertOnnxConfig,
    )
    from .tokenization_distilbert import DistilBertTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_distilbert_fast import DistilBertTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_distilbert import (
            DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            DistilBertForMaskedLM,
            DistilBertForMultipleChoice,
            DistilBertForQuestionAnswering,
            DistilBertForSequenceClassification,
            DistilBertForTokenClassification,
            DistilBertModel,
            DistilBertPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_distilbert import (
            TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFDistilBertForMaskedLM,
            TFDistilBertForMultipleChoice,
            TFDistilBertForQuestionAnswering,
            TFDistilBertForSequenceClassification,
            TFDistilBertForTokenClassification,
            TFDistilBertMainLayer,
            TFDistilBertModel,
            TFDistilBertPreTrainedModel,
        )

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_distilbert import (
            FlaxDistilBertForMaskedLM,
            FlaxDistilBertForMultipleChoice,
            FlaxDistilBertForQuestionAnswering,
            FlaxDistilBertForSequenceClassification,
            FlaxDistilBertForTokenClassification,
            FlaxDistilBertModel,
            FlaxDistilBertPreTrainedModel,
        )

else:
    import sys

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







'''simple docstring'''





class 				UpperCAmelCase			:


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


 def        __SCREAMING_SNAKE_CASE					(      self							:	Optional[int]			,       __lowerCamelCase							:	list[str] ):
    for word in words:
       self.insert(__lowerCamelCase )


 def        __SCREAMING_SNAKE_CASE					(      self							:	Dict			,       __lowerCamelCase							:	str ):
    UpperCAmelCase__	:Tuple      =      self
    for char in word:
       if char not in curr.nodes:
          UpperCAmelCase__	:Optional[int]      =      TrieNode()
       UpperCAmelCase__	:Dict      =      curr.nodes[char]
    UpperCAmelCase__	:Optional[int]      =      True


 def        __SCREAMING_SNAKE_CASE					(      self							:	Any			,       __lowerCamelCase							:	str ):
    UpperCAmelCase__	:str      =      self
    for char in word:
       if char not in curr.nodes:
          return False
       UpperCAmelCase__	:Dict      =      curr.nodes[char]
    return curr.is_leaf





 def        __SCREAMING_SNAKE_CASE					(      self							:	Optional[Any]			,       __lowerCamelCase							:	str ):

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

    _delete(self			,       __lowerCamelCase			,       0 )


def        a__     (					UpperCamelCase_						:      TrieNode,   UpperCamelCase_						:      str						):
   if node.is_leaf:
      print(UpperCamelCase_,   end=''' '''						)

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


def        a__     (					):
   UpperCAmelCase__	:Union[str, Any]      =      '''banana bananas bandana band apple all beast'''.split()
   UpperCAmelCase__	:Union[str, Any]      =      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        a__     (					UpperCamelCase_						:      str,   UpperCamelCase_						:      bool						):
   print(str(UpperCamelCase_						),   '''works!''' if passes else '''doesn\'t work :('''						)


def        a__     (					):
   assert test_trie()


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


if __name__ == "__main__":
    main()



