
def     a						(							snake_case__: list						,       snake_case__: int ):


				'''simple docstring'''
				for index, item in enumerate(snake_case__ ):
								if item == target:
												return index
				return -1




def     a						(							snake_case__: list						,       snake_case__: int						,       snake_case__: int						,       snake_case__: int ):


				'''simple docstring'''
				if not (0 <= high < len(snake_case__ ) and 0 <= low < len(snake_case__ )):
								raise Exception('''Invalid upper or lower bound!''' )
				if high < low:
								return -1
				if sequence[low] == target:
								return low
				if sequence[high] == target:
								return high
				return rec_linear_search(snake_case__						,       low + 1						,       high - 1						,       snake_case__ )


if __name__ == "__main__":
						__a        = input('Enter numbers separated by comma:\n').strip()
						__a        = [int(item.strip()) for item in user_input.split(',')]

						__a        = int(input('Enter a single number to be found in the list:\n').strip())
						__a        = linear_search(sequence, target)
						if result != -1:
												print(f"linear_search({sequence}, {target}) = {result}")
						else:
												print(f"{target} was not found in {sequence}")






from typing import TYPE_CHECKING

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


__a        = {
    'configuration_donut_swin': ['DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DonutSwinConfig'],
    'processing_donut': ['DonutProcessor'],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a        = [
						    'DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'DonutSwinModel',
						    'DonutSwinPreTrainedModel',
						]

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a        = ['DonutFeatureExtractor']
						__a        = ['DonutImageProcessor']


if TYPE_CHECKING:
						from .configuration_donut_swin import DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, DonutSwinConfig
						from .processing_donut import DonutProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_donut_swin import (
												    DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
												    DonutSwinModel,
												    DonutSwinPreTrainedModel,
												)

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_donut import DonutFeatureExtractor
												from .image_processing_donut import DonutImageProcessor

else:
						import sys

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




