
import math




def     a						(							snake_case__: int ):


				'''simple docstring'''
				lowercase_					  = math.log(2						,       10 ) * number
				lowercase_					  = round((log_number - int(snake_case__ ))						,       15 )

				return difference




def     a						(							snake_case__: int = 678_910 ):


				'''simple docstring'''
				lowercase_					  = 90
				lowercase_					  = 0

				lowercase_					  = math.log(1.2_3						,       10 )
				lowercase_					  = math.log(1.2_4						,       10 )
				lowercase_					  = 0

				while position < number:
								lowercase_					  = log_difference(snake_case__ )

								if difference >= upper_limit:
												power_iterator += 93

								elif difference < lower_limit:
												power_iterator += 196

								else:
												lowercase_					  = power_iterator
												power_iterator += 196
												position += 1

				return previous_power


if __name__ == "__main__":
						import doctest

						doctest.testmod()

						print(f"{solution() = }")






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__)




