




'''simple docstring'''





def     __magic_name__       (				A	:      list[int],						A	:      str     ):






			'''simple docstring'''







			a					=    int(A     )

			# Initialize Result
			a					=    []

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

			return answer


# Driver Code
if __name__ == "__main__":
		__lowerCAmelCase	:       Any     =	[]
		__lowerCAmelCase	:       Optional[int]     =	'0'

		if (
		    input('Do you want to enter your denominations ? (yY/n): ').strip().lower()
		    == "y"
		):
				__lowerCAmelCase	:       List[str]     =	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()))
				__lowerCAmelCase	:       int     =	input('Enter the change you want to make in Indian Currency: ').strip()
		else:
				# All denominations of Indian Currency if user does not enter
				__lowerCAmelCase	:       Dict     =	[1, 2, 5, 10, 20, 50, 100, 500, 2000]
				__lowerCAmelCase	:       str     =	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}: ''')
				__lowerCAmelCase	:       int     =	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_tokenizers_available, is_torch_available


__lowerCAmelCase	:       Any     =	{
    'configuration_roc_bert': ['ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RoCBertConfig'],
    'tokenization_roc_bert': ['RoCBertTokenizer'],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		pass

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCAmelCase	:       Optional[Any]     =	[
		    'ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'RoCBertForCausalLM',
		    'RoCBertForMaskedLM',
		    'RoCBertForMultipleChoice',
		    'RoCBertForPreTraining',
		    'RoCBertForQuestionAnswering',
		    'RoCBertForSequenceClassification',
		    'RoCBertForTokenClassification',
		    'RoCBertLayer',
		    'RoCBertModel',
		    'RoCBertPreTrainedModel',
		    'load_tf_weights_in_roc_bert',
		]

if TYPE_CHECKING:
		from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
		from .tokenization_roc_bert import RoCBertTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				raise OptionalDependencyNotAvailable()

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_roc_bert import (
				    ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    RoCBertForCausalLM,
				    RoCBertForMaskedLM,
				    RoCBertForMultipleChoice,
				    RoCBertForPreTraining,
				    RoCBertForQuestionAnswering,
				    RoCBertForSequenceClassification,
				    RoCBertForTokenClassification,
				    RoCBertLayer,
				    RoCBertModel,
				    RoCBertPreTrainedModel,
				    load_tf_weights_in_roc_bert,
				)


else:
		import sys

		__lowerCAmelCase	:       Union[str, Any]     =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






