






def      __A					(     _lowercase					,			_lowercase ):

					'''simple docstring'''







					_A								= int(_lowercase )

					# Initialize Result
					_A								= []

					# 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 typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


__A      =				{
    'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__A      =				[
				    'MEGA_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'MegaForCausalLM',
				    'MegaForMaskedLM',
				    'MegaForMultipleChoice',
				    'MegaForQuestionAnswering',
				    'MegaForSequenceClassification',
				    'MegaForTokenClassification',
				    'MegaModel',
				    'MegaPreTrainedModel',
				]

if TYPE_CHECKING:
				from .configuration_mega import MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP, MegaConfig, MegaOnnxConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_mega import (
								    MEGA_PRETRAINED_MODEL_ARCHIVE_LIST,
								    MegaForCausalLM,
								    MegaForMaskedLM,
								    MegaForMultipleChoice,
								    MegaForQuestionAnswering,
								    MegaForSequenceClassification,
								    MegaForTokenClassification,
								    MegaModel,
								    MegaPreTrainedModel,
								)

else:
				import sys

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



