




'''simple docstring'''


import random
from typing import Any
def 		snake_case_   (UpperCamelCase	:  list				):





							'''simple docstring'''


							for _ in range(len(UpperCamelCase				)				):
														_a     					=    random.randint(0			,						len(UpperCamelCase				) - 1				)
														_a     					=    random.randint(0			,						len(UpperCamelCase				) - 1				)
														_a					,							_a     					=    data[b], data[a]
							return data


if __name__ == "__main__":
				_snake_case				:				Optional[Any]       							=		[0, 1, 2, 3, 4, 5, 6, 7]
				_snake_case				:				str       							=		['python', 'says', 'hello', '!']
				print('Fisher-Yates Shuffle:')
				print('List', integers, strings)
				print('FY Shuffle', fisher_yates_shuffle(integers), fisher_yates_shuffle(strings))







'''simple docstring'''


from typing import TYPE_CHECKING

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


_snake_case				:				int       							=		{'configuration_yolos': ['YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP', 'YolosConfig', 'YolosOnnxConfig']}

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_snake_case				:				List[str]       							=		['YolosFeatureExtractor']
				_snake_case				:				Optional[int]       							=		['YolosImageProcessor']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_snake_case				:				Tuple       							=		[
				    'YOLOS_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'YolosForObjectDetection',
				    'YolosModel',
				    'YolosPreTrainedModel',
				]


if TYPE_CHECKING:
				from .configuration_yolos import YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP, YolosConfig, YolosOnnxConfig

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .feature_extraction_yolos import YolosFeatureExtractor
								from .image_processing_yolos import YolosImageProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_yolos import (
								    YOLOS_PRETRAINED_MODEL_ARCHIVE_LIST,
								    YolosForObjectDetection,
								    YolosModel,
								    YolosPreTrainedModel,
								)


else:
				import sys

				_snake_case				:				Dict       							=		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

