





a__: List[str]							   =						[0, 2, 4, 6, 8]
a__: Optional[int]							   =						[1, 3, 5, 7, 9]


def       UpperCamelCase__(			UpperCamelCase__     :			int					,	UpperCamelCase__     :			int					,	UpperCamelCase__     :			list[int]					,	UpperCamelCase__     :			int    )->int:
       if remaining_length == 0:
              if digits[0] == 0 or digits[-1] == 0:
                     return 0

              for i in range(length // 2 - 1					,	-1					,	-1    ):
                     remainder += digits[i] + digits[length - i - 1]

                     if remainder % 2 == 0:
                            return 0

                     remainder //= 10

              return 1

       if remaining_length == 1:
              if remainder % 2 == 0:
                     return 0

              A__		   =		0
              for digit in range(10    ):
                     A__		   =		digit
                     result += reversible_numbers(
                         0					,	(remainder + 2 * digit) // 10					,	UpperCamelCase__					,	UpperCamelCase__    )
              return result

       A__		   =		0
       for digita in range(10    ):
              A__		   =		digita

              if (remainder + digita) % 2 == 0:
                     A__		   =		ODD_DIGITS
              else:
                     A__		   =		EVEN_DIGITS

              for digita in other_parity_digits:
                     A__		   =		digita
                     result += reversible_numbers(
                         remaining_length - 2					,	(remainder + digita + digita) // 10					,	UpperCamelCase__					,	UpperCamelCase__					,	)
       return result


def       UpperCamelCase__(			UpperCamelCase__     :			int = 9    )->int:
       A__		   =		0
       for length in range(1					,	max_power + 1    ):
              result += reversible_numbers(UpperCamelCase__					,	0					,	[0] * length					,	UpperCamelCase__    )
       return result


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












a__: str							   =						'0.21.0'

from .accelerator import Accelerator
from .big_modeling import (
    cpu_offload,
    cpu_offload_with_hook,
    disk_offload,
    dispatch_model,
    init_empty_weights,
    init_on_device,
    load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .launchers import debug_launcher, notebook_launcher
from .state import PartialState
from .utils import (
    DeepSpeedPlugin,
    DistributedDataParallelKwargs,
    DistributedType,
    FullyShardedDataParallelPlugin,
    GradScalerKwargs,
    InitProcessGroupKwargs,
    find_executable_batch_size,
    infer_auto_device_map,
    is_rich_available,
    load_checkpoint_in_model,
    synchronize_rng_states,
)


if is_rich_available():
       from .utils import rich





