





def 							SCREAMING_SNAKE_CASE__  (      __a				,	__a				):
	snake_case_						:     Optional[int]     =		int(__a				)

	# Initialize Result
	snake_case_						:     Tuple     =		[]

	# 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__":
			_SCREAMING_SNAKE_CASE 		=						[]
			_SCREAMING_SNAKE_CASE 		=						"""0"""

			if (
			    input("""Do you want to enter your denominations ? (yY/n): """).strip().lower()
			    == "y"
			):
						_SCREAMING_SNAKE_CASE 		=						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()))
						_SCREAMING_SNAKE_CASE 		=						input("""Enter the change you want to make in Indian Currency: """).strip()
			else:
						# All denominations of Indian Currency if user does not enter
						_SCREAMING_SNAKE_CASE 		=						[1, 2, 5, 10, 20, 50, 1_00, 5_00, 20_00]
						_SCREAMING_SNAKE_CASE 		=						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}: ''')
						_SCREAMING_SNAKE_CASE 		=						find_minimum_change(denominations, value)
						# Print result
						for i in range(len(answer)):
									print(answer[i], end=""" """)








_SCREAMING_SNAKE_CASE 		=						{
    """Pillow""": """Pillow""",
    """accelerate""": """accelerate>=0.11.0""",
    """compel""": """compel==0.1.8""",
    """black""": """black~=23.1""",
    """datasets""": """datasets""",
    """filelock""": """filelock""",
    """flax""": """flax>=0.4.1""",
    """hf-doc-builder""": """hf-doc-builder>=0.3.0""",
    """huggingface-hub""": """huggingface-hub>=0.13.2""",
    """requests-mock""": """requests-mock==1.10.0""",
    """importlib_metadata""": """importlib_metadata""",
    """invisible-watermark""": """invisible-watermark""",
    """isort""": """isort>=5.5.4""",
    """jax""": """jax>=0.2.8,!=0.3.2""",
    """jaxlib""": """jaxlib>=0.1.65""",
    """Jinja2""": """Jinja2""",
    """k-diffusion""": """k-diffusion>=0.0.12""",
    """torchsde""": """torchsde""",
    """note_seq""": """note_seq""",
    """librosa""": """librosa""",
    """numpy""": """numpy""",
    """omegaconf""": """omegaconf""",
    """parameterized""": """parameterized""",
    """protobuf""": """protobuf>=3.20.3,<4""",
    """pytest""": """pytest""",
    """pytest-timeout""": """pytest-timeout""",
    """pytest-xdist""": """pytest-xdist""",
    """ruff""": """ruff>=0.0.241""",
    """safetensors""": """safetensors""",
    """sentencepiece""": """sentencepiece>=0.1.91,!=0.1.92""",
    """scipy""": """scipy""",
    """onnx""": """onnx""",
    """regex""": """regex!=2019.12.17""",
    """requests""": """requests""",
    """tensorboard""": """tensorboard""",
    """torch""": """torch>=1.4""",
    """torchvision""": """torchvision""",
    """transformers""": """transformers>=4.25.1""",
    """urllib3""": """urllib3<=2.0.0""",
}

