


'''simple docstring'''






def A_					(				__SCREAMING_SNAKE_CASE :					int       )     ->  bool:
					__SCREAMING_SNAKE_CASE					:							Optional[Any]			   = 9

					while num > 0:
										if num % 10 != digit:
															return False
										num //= 1_00
										digit -= 1

					return True


def A_					(				)     ->  int:
					__SCREAMING_SNAKE_CASE					:							Union[str, Any]			   = 1_38_90_26_63

					while not is_square_form(num * num       ):
										if num % 10 == 3:
															num -= 6  # (3 - 6) % 10 = 7
										else:
															num -= 4  # (7 - 4) % 10 = 3

					return num * 10


if __name__ == "__main__":
						print(f'{solution() = }')






'''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__)


