

"""simple docstring"""




from typing import TYPE_CHECKING

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


UpperCAmelCase__   :					str												=				{
    'configuration_mobilenet_v2': [
        'MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'MobileNetV2Config',
        'MobileNetV2OnnxConfig',
    ],
}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCAmelCase__   :					Tuple												=				['MobileNetV2FeatureExtractor']
					UpperCAmelCase__   :					int												=				['MobileNetV2ImageProcessor']


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCAmelCase__   :					Tuple												=				[
					    'MOBILENET_V2_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'MobileNetV2ForImageClassification',
					    'MobileNetV2ForSemanticSegmentation',
					    'MobileNetV2Model',
					    'MobileNetV2PreTrainedModel',
					    'load_tf_weights_in_mobilenet_v2',
					]


if TYPE_CHECKING:
					from .configuration_mobilenet_va import (
					    MOBILENET_V2_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_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
										    MobileNetVaForImageClassification,
										    MobileNetVaForSemanticSegmentation,
										    MobileNetVaModel,
										    MobileNetVaPreTrainedModel,
										    load_tf_weights_in_mobilenet_va,
										)


else:
					import sys

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






"""simple docstring"""




UpperCAmelCase__   :					Dict												=				[
    (1_0_0_0, 'M'),
    (9_0_0, 'CM'),
    (5_0_0, 'D'),
    (4_0_0, 'CD'),
    (1_0_0, 'C'),
    (9_0, 'XC'),
    (5_0, 'L'),
    (4_0, 'XL'),
    (1_0, 'X'),
    (9, 'IX'),
    (5, 'V'),
    (4, 'IV'),
    (1, 'I'),
]

def lowercase_						(     _snake_case		):
							SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     {"""I""": 1, """V""": 5, """X""": 10, """L""": 50, """C""": 100, """D""": 500, """M""": 1_000}
							SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     0
							SCREAMING_SNAKE_CASE__		: Union[str, Any]     =     0
							while place < len(_snake_case		):
														if (place + 1 < len(_snake_case		)) and (vals[roman[place]] < vals[roman[place + 1]]):
																					total += vals[roman[place + 1]] - vals[roman[place]]
																					place += 2
														else:
																					total += vals[roman[place]]
																					place += 1
							return total

def lowercase_						(     _snake_case		):
							SCREAMING_SNAKE_CASE__		: Optional[Any]     =     []
							for arabic, roman in ROMAN:
														((SCREAMING_SNAKE_CASE__)   ,   (SCREAMING_SNAKE_CASE__))		: List[Any]     =     divmod(_snake_case     ,_snake_case		)
														result.append(roman * factor		)
														if number == 0:
																					break
							return "".join(_snake_case		)


if __name__ == "__main__":
					import doctest

					doctest.testmod()




