UpperCamelCase  							=						[0, 2, 4, 6, 8]
UpperCamelCase  							=						[1, 3, 5, 7, 9]

def 			lowercase_				(			_lowerCamelCase							:       int		,	_lowerCamelCase							:       int		,	_lowerCamelCase							:       list[int]		,	_lowerCamelCase							:       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

        lowercase__ :   str    					=				0
        for digit in range(10):
            lowercase__ :   str    					=				digit
            result += reversible_numbers(
                0		,	(remainder + 2 * digit) // 10		,	_lowerCamelCase		,	_lowerCamelCase)
        return result

    lowercase__ :   Dict    					=				0
    for digita in range(10):
        lowercase__ :   int    					=				digita

        if (remainder + digita) % 2 == 0:
            lowercase__ :   Optional[Any]    					=				ODD_DIGITS
        else:
            lowercase__ :   str    					=				EVEN_DIGITS

        for digita in other_parity_digits:
            lowercase__ :   List[str]    					=				digita
            result += reversible_numbers(
                remaining_length - 2		,	(remainder + digita + digita) // 10		,	_lowerCamelCase		,	_lowerCamelCase		,	)
    return result

def 			lowercase_				(			_lowerCamelCase							:       int = 9):
    lowercase__ :   Tuple    					=				0
    for length in range(1		,	max_power + 1):
        result += reversible_numbers(_lowerCamelCase		,	0		,	[0] * length		,	_lowerCamelCase)
    return result


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






from typing import TYPE_CHECKING

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


if is_sentencepiece_available():
						from ..ta.tokenization_ta import TaTokenizer
else:
						from ...utils.dummy_sentencepiece_objects import TaTokenizer

lowerCAmelCase							:  Any   	=						TaTokenizer

if is_tokenizers_available():
						from ..ta.tokenization_ta_fast import TaTokenizerFast
else:
						from ...utils.dummy_tokenizers_objects import TaTokenizerFast

lowerCAmelCase							:  Dict   	=						TaTokenizerFast

lowerCAmelCase							:  Optional[int]   	=						{"""configuration_mt5""": ["""MT5Config""", """MT5OnnxConfig"""]}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase							:  int   	=						[
						    """MT5EncoderModel""",
						    """MT5ForConditionalGeneration""",
						    """MT5ForQuestionAnswering""",
						    """MT5Model""",
						    """MT5PreTrainedModel""",
						    """MT5Stack""",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase							:  Tuple   	=						["""TFMT5EncoderModel""", """TFMT5ForConditionalGeneration""", """TFMT5Model"""]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase							:  List[str]   	=						["""FlaxMT5EncoderModel""", """FlaxMT5ForConditionalGeneration""", """FlaxMT5Model"""]


if TYPE_CHECKING:
						from .configuration_mta import MTaConfig, MTaOnnxConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_mta import (
												    MTaEncoderModel,
												    MTaForConditionalGeneration,
												    MTaForQuestionAnswering,
												    MTaModel,
												    MTaPreTrainedModel,
												    MTaStack,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_mta import TFMTaEncoderModel, TFMTaForConditionalGeneration, TFMTaModel

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_mta import FlaxMTaEncoderModel, FlaxMTaForConditionalGeneration, FlaxMTaModel

else:
						import sys

						lowerCAmelCase							:  Optional[Any]   	=						_LazyModule(
						    __name__,
						    globals()["""__file__"""],
						    _import_structure,
						    extra_objects={"""MT5Tokenizer""": MTaTokenizer, """MT5TokenizerFast""": MTaTokenizerFast},
						    module_spec=__spec__,
						)






