from itertools import count




def     UpperCamelCase						(	__lowercase						:			int = 50     ):
		'''simple docstring'''




		A_		:    Optional[Any]         =				[1] * min_block_length

		for n in count(__lowercase     ):
				fill_count_functions.append(1     )

				for block_length in range(__lowercase						,n + 1     ):
						for block_start in range(n - block_length     ):
								fill_count_functions[n] += fill_count_functions[
								    n - block_start - block_length - 1
								]

						fill_count_functions[n] += 1

				if fill_count_functions[n] > 1_00_00_00:
						break

		return n


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







import warnings

from ...utils import logging
from .image_processing_donut import DonutImageProcessor


_UpperCAmelCase            =		logging.get_logger(__name__)





class UpperCAmelCase						( __A  ):


				'''simple docstring'''






				def __init__(						self		,     *lowercase		,     **lowercase ):



						"""simple docstring"""





						warnings.warn(
						    'The class DonutFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
						    ' use DonutImageProcessor instead.'		,     lowercase		,     )
						super().__init__(*lowercase		,     **lowercase )






