




'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a__         =     {'''configuration_qdqbert''': ['''QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''QDQBertConfig''']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a__         =     [
		    '''QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''QDQBertForMaskedLM''',
		    '''QDQBertForMultipleChoice''',
		    '''QDQBertForNextSentencePrediction''',
		    '''QDQBertForQuestionAnswering''',
		    '''QDQBertForSequenceClassification''',
		    '''QDQBertForTokenClassification''',
		    '''QDQBertLayer''',
		    '''QDQBertLMHeadModel''',
		    '''QDQBertModel''',
		    '''QDQBertPreTrainedModel''',
		    '''load_tf_weights_in_qdqbert''',
		]


if TYPE_CHECKING:
		from .configuration_qdqbert import QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, QDQBertConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_qdqbert import (
				    QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    QDQBertForMaskedLM,
				    QDQBertForMultipleChoice,
				    QDQBertForNextSentencePrediction,
				    QDQBertForQuestionAnswering,
				    QDQBertForSequenceClassification,
				    QDQBertForTokenClassification,
				    QDQBertLayer,
				    QDQBertLMHeadModel,
				    QDQBertModel,
				    QDQBertPreTrainedModel,
				    load_tf_weights_in_qdqbert,
				)


else:
		import sys

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



"""simple docstring"""







from .stack import Stack
def _A		(		lowercase						):







    """simple docstring"""
    a											=Stack()
    a											={'''(''': ''')''', '''[''': ''']''', '''{''': '''}'''}
    for bracket in parentheses:
        if bracket in bracket_pairs:
            stack.push(lowercase						)
        elif bracket in (")", "]", "}"):
            if stack.is_empty() or bracket_pairs[stack.pop()] != bracket:
                return False
    return stack.is_empty()


if __name__ == "__main__":
       from doctest import testmod

       testmod()

       lowerCamelCase_  :  List[str]     		=    ["""((()))""", """((())""", """(()))"""]
       print("""Balanced parentheses demonstration:\n""")
       for example in examples:
              lowerCamelCase_  :  str     		=    """""" if balanced_parentheses(example) else """not """
              print(F'{example} is {not_str}balanced')