




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,
)


__magic_name__	:       Dict     =	{'configuration_mbart': ['MBART_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MBartConfig', 'MBartOnnxConfig']}

try:
		if not is_sentencepiece_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__	:       Optional[int]     =	['MBartTokenizer']

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__	:       int     =	['MBartTokenizerFast']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__	:       List[Any]     =	[
		    'MBART_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'MBartForCausalLM',
		    'MBartForConditionalGeneration',
		    'MBartForQuestionAnswering',
		    'MBartForSequenceClassification',
		    'MBartModel',
		    'MBartPreTrainedModel',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__	:       Tuple     =	[
		    'TFMBartForConditionalGeneration',
		    'TFMBartModel',
		    'TFMBartPreTrainedModel',
		]

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__magic_name__	:       Dict     =	[
		    'FlaxMBartForConditionalGeneration',
		    'FlaxMBartForQuestionAnswering',
		    'FlaxMBartForSequenceClassification',
		    'FlaxMBartModel',
		    'FlaxMBartPreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_mbart import MBART_PRETRAINED_CONFIG_ARCHIVE_MAP, MBartConfig, MBartOnnxConfig

		try:
				if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_mbart import MBartTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_mbart_fast import MBartTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_mbart import (
				    MBART_PRETRAINED_MODEL_ARCHIVE_LIST,
				    MBartForCausalLM,
				    MBartForConditionalGeneration,
				    MBartForQuestionAnswering,
				    MBartForSequenceClassification,
				    MBartModel,
				    MBartPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_mbart import TFMBartForConditionalGeneration, TFMBartModel, TFMBartPreTrainedModel

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_mbart import (
				    FlaxMBartForConditionalGeneration,
				    FlaxMBartForQuestionAnswering,
				    FlaxMBartForSequenceClassification,
				    FlaxMBartModel,
				    FlaxMBartPreTrainedModel,
				)

else:
		import sys

		__magic_name__	:       int     =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)












__lowerCAmelCase	:       List[Any]     =	{str(digit): digit**5 for digit in range(10)}




def     __magic_name__       (				A	:      int     ):






			'''simple docstring'''







			return sum(DIGITS_FIFTH_POWER[digit] for digit in str(A     )     )




def     __magic_name__       (				):






			'''simple docstring'''







			return sum(
			    number
			    for number in range(1000,						1000000     )
			    if number == digits_fifth_powers_sum(A     )     )


if __name__ == "__main__":
		print(solution())






