


'''simple docstring'''






from .stack import Stack


def A_					(				__SCREAMING_SNAKE_CASE :					Optional[Any]       )     ->  Any:
					__SCREAMING_SNAKE_CASE					:							Optional[int]			   = Stack()
					__SCREAMING_SNAKE_CASE					:							Tuple			   = {'''(''': ''')''', '''[''': ''']''', '''{''': '''}'''}
					for bracket in parentheses:
										if bracket in bracket_pairs:
															stack.push(__A       )
										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()

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










'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_A      =     {
    """configuration_decision_transformer""": [
        """DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """DecisionTransformerConfig""",
    ],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_A      =     [
						    """DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """DecisionTransformerGPT2Model""",
						    """DecisionTransformerGPT2PreTrainedModel""",
						    """DecisionTransformerModel""",
						    """DecisionTransformerPreTrainedModel""",
						]


if TYPE_CHECKING:
						from .configuration_decision_transformer import (
						    DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    DecisionTransformerConfig,
						)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_decision_transformer import (
												    DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    DecisionTransformerGPTaModel,
												    DecisionTransformerGPTaPreTrainedModel,
												    DecisionTransformerModel,
												    DecisionTransformerPreTrainedModel,
												)


else:
						import sys

						_A      =     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


