
'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


__SCREAMING_SNAKE_CASE		:  Tuple        =      {
    'configuration_sam': [
        'SAM_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'SamConfig',
        'SamMaskDecoderConfig',
        'SamPromptEncoderConfig',
        'SamVisionConfig',
    ],
    'processing_sam': ['SamProcessor'],
}


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__SCREAMING_SNAKE_CASE		:  Tuple        =      [
					    'SAM_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'SamModel',
					    'SamPreTrainedModel',
					]
try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__SCREAMING_SNAKE_CASE		:  int        =      [
					    'TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'TFSamModel',
					    'TFSamPreTrainedModel',
					]
try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__SCREAMING_SNAKE_CASE		:  Optional[int]        =      ['SamImageProcessor']


if TYPE_CHECKING:
					from .configuration_sam import (
					    SAM_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    SamConfig,
					    SamMaskDecoderConfig,
					    SamPromptEncoderConfig,
					    SamVisionConfig,
					)
					from .processing_sam import SamProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_sam import SAM_PRETRAINED_MODEL_ARCHIVE_LIST, SamModel, SamPreTrainedModel

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_sam import TF_SAM_PRETRAINED_MODEL_ARCHIVE_LIST, TFSamModel, TFSamPreTrainedModel

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .image_processing_sam import SamImageProcessor

else:
					import sys

					__SCREAMING_SNAKE_CASE		:  Any        =      _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

'''simple docstring'''







def 				_snake_case (		lowercase = 1_0_0_0						)       ->       int:
				__a       :     Any								=	[]
				__a       :     List[Any]								=	[]
				__a       :     Any								=	3
				__a       :     Optional[Any]								=	5
				__a       :     Optional[Any]								=	1
				while True:
								__a       :     List[str]								=	z * temp
								if result < n:
												zmulti.append(lowercase						)
												temp += 1
								else:
												__a       :     Any								=	1
												break
				while True:
								__a       :     Optional[int]								=	x * temp
								if result < n:
												xmulti.append(lowercase						)
												temp += 1
								else:
												break
				__a       :     Any								=	list(set(xmulti + zmulti						)						)
				return sum(lowercase						)


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