




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


UpperCamelCase__						=		{
    'configuration_mobilenet_v1': [
        'MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'MobileNetV1Config',
        'MobileNetV1OnnxConfig',
    ],
}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase__						=		['MobileNetV1FeatureExtractor']
							UpperCamelCase__						=		['MobileNetV1ImageProcessor']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase__						=		[
							    'MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'MobileNetV1ForImageClassification',
							    'MobileNetV1Model',
							    'MobileNetV1PreTrainedModel',
							    'load_tf_weights_in_mobilenet_v1',
							]


if TYPE_CHECKING:
							from .configuration_mobilenet_va import (
							    MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    MobileNetVaConfig,
							    MobileNetVaOnnxConfig,
							)

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_mobilenet_va import MobileNetVaFeatureExtractor
														from .image_processing_mobilenet_va import MobileNetVaImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_mobilenet_va import (
														    MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MobileNetVaForImageClassification,
														    MobileNetVaModel,
														    MobileNetVaPreTrainedModel,
														    load_tf_weights_in_mobilenet_va,
														)


else:
							import sys

							UpperCamelCase__						=		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





UpperCAmelCase__  =			10**8





def 				A      (	_UpperCAmelCase							:  int       )							->					bool:







			'''simple docstring'''
			if n % 10 == 0:
						return False
			_UpperCAmelCase									=  str(_UpperCAmelCase       )
			return s == s[::-1]





def 				A      (	)							->					int:







			'''simple docstring'''
			_UpperCAmelCase									=  set()
			_UpperCAmelCase									=  1
			_UpperCAmelCase									=  5
			while sum_squares < LIMIT:
						_UpperCAmelCase									=  first_square + 1
						while sum_squares < LIMIT:
									if is_palindrome(_UpperCAmelCase       ):
												answer.add(_UpperCAmelCase       )
									last_square += 1
									sum_squares += last_square**2
						first_square += 1
						_UpperCAmelCase									=  first_square**2 + (first_square + 1) ** 2

			return sum(_UpperCAmelCase       )


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