

def a(lowercase__      ,			lowercase__						):





	'''simple docstring'''
	snake_case_   		=			int(lowercase__						)

	# Initialize Result
	snake_case_   		=			[]

	# Traverse through all denomination
	for denomination in reversed(lowercase__						):
		# Find denominations
		while int(lowercase__						) >= int(lowercase__						):
			total_value -= int(lowercase__						)
			answer.append(lowercase__						)  # Append the "answers" array

	return answer


# Driver Code
if __name__ == "__main__":
		A									=  []
		A									=  '0'

		if (
		    input('Do you want to enter your denominations ? (yY/n): ').strip().lower()
		    == "y"
		):
				A									=  int(input('Enter the number of denominations you want to add: ').strip())

				for i in range(0, n):
						denominations.append(int(input(f"""Denomination {i}: """).strip()))
				A									=  input('Enter the change you want to make in Indian Currency: ').strip()
		else:
				# All denominations of Indian Currency if user does not enter
				A									=  [1, 2, 5, 10, 20, 50, 100, 500, 2000]
				A									=  input('Enter the change you want to make: ').strip()

		if int(value) == 0 or int(value) < 0:
				print('The total value cannot be zero or negative.')

		else:
				print(f"""Following is minimal change for {value}: """)
				A									=  find_minimum_change(denominations, value)
				# Print result
				for i in range(len(answer)):
						print(answer[i], end=' ')



from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


A									=  logging.get_logger(__name__)

A									=  {
    'google/bit-50': 'https://huggingface.co/google/bit-50/resolve/main/config.json',
}


class SCREAMING_SNAKE_CASE	(		__snake_case				,    __snake_case				):






			"""simple docstring"""




			__A    	=	"""bit"""
			__A    	=	["""preactivation""", """bottleneck"""]
			__A    	=	["""SAME""", """VALID"""]


			def __init__(     self			,					__UpperCamelCase=3			,					__UpperCamelCase=64			,					__UpperCamelCase=[2_56, 5_12, 10_24, 20_48]			,					__UpperCamelCase=[3, 4, 6, 3]			,					__UpperCamelCase="preactivation"			,					__UpperCamelCase="relu"			,					__UpperCamelCase=None			,					__UpperCamelCase=32			,					__UpperCamelCase=0.0			,					__UpperCamelCase=False			,					__UpperCamelCase=32			,					__UpperCamelCase=1			,					__UpperCamelCase=None			,					__UpperCamelCase=None			,					**__UpperCamelCase			,					):

				"""simple docstring"""


				super().__init__(**__UpperCamelCase				)
				if layer_type not in self.layer_types:
					raise ValueError(f"""layer_type={layer_type} is not one of {','.join(self.layer_types				)}"""				)
				if global_padding is not None:
					if global_padding.upper() in self.supported_padding:
						snake_case_   		=			global_padding.upper()
					else:
						raise ValueError(f"""Padding strategy {global_padding} not supported"""				)
				snake_case_   		=			num_channels
				snake_case_   		=			embedding_size
				snake_case_   		=			hidden_sizes
				snake_case_   		=			depths
				snake_case_   		=			layer_type
				snake_case_   		=			hidden_act
				snake_case_   		=			global_padding
				snake_case_   		=			num_groups
				snake_case_   		=			drop_path_rate
				snake_case_   		=			embedding_dynamic_padding
				snake_case_   		=			output_stride
				snake_case_   		=			width_factor

				snake_case_   		=			['stem'] + [f"""stage{idx}""" for idx in range(1			,					len(__UpperCamelCase				) + 1				)]
				snake_case_		,							snake_case_   		=			get_aligned_output_features_output_indices(
				    out_features=__UpperCamelCase			,					out_indices=__UpperCamelCase			,					stage_names=self.stage_names				)
