





import random
import unittest

import torch

from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device

from ..pipeline_params import TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS, TEXT_GUIDED_IMAGE_VARIATION_PARAMS
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin
@skip_mps
class SCREAMING_SNAKE_CASE_  (   snake_case_    ,			snake_case_    ,			unittest.TestCase   ):
						__magic_name__:     str	 =    IFImgaImgSuperResolutionPipeline
						__magic_name__:     List[str]	 =    TEXT_GUIDED_IMAGE_VARIATION_PARAMS - {"width", "height"}
						__magic_name__:     Dict	 =    TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS.union({"original_image"}   )
						__magic_name__:     Tuple	 =    PipelineTesterMixin.required_optional_params - {"latents"}






						def UpperCAmelCase_			( self : Optional[int]		)							->      Optional[int]:







							"""simple docstring"""


							return self._get_superresolution_dummy_components()






						def UpperCAmelCase_			( self : List[str]						,				_A : Dict						,				_A : Optional[int]=0		)							->      Any:







							"""simple docstring"""


							if str(_A		).startswith('mps'		):
								snake_case_						:     List[Any]     =		torch.manual_seed(_A		)
							else:
								snake_case_						:     Optional[Any]     =		torch.Generator(device=_A		).manual_seed(_A		)

							snake_case_						:     Dict     =		floats_tensor((1, 3, 32, 32)						,				rng=random.Random(_A		)		).to(_A		)
							snake_case_						:     Any     =		floats_tensor((1, 3, 16, 16)						,				rng=random.Random(_A		)		).to(_A		)

							snake_case_						:     Tuple     =		{
							    'prompt': 'A painting of a squirrel eating a burger',
							    'image': image,
							    'original_image': original_image,
							    'generator': generator,
							    'num_inference_steps': 2,
							    'output_type': 'numpy',
							}

							return inputs






						@unittest.skipIf(
						    torch_device != 'cuda' or not is_xformers_available()						,				reason='XFormers attention is only available with CUDA and `xformers` installed'						,				)
						def UpperCAmelCase_			( self : Optional[int]		)							->      Tuple:







							"""simple docstring"""


							self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1E-3		)






						def UpperCAmelCase_			( self : List[str]		)							->      List[Any]:







							"""simple docstring"""


							self._test_save_load_optional_components()






						@unittest.skipIf(torch_device != 'cuda'						,				reason='float16 requires CUDA'		)
						def UpperCAmelCase_			( self : Optional[int]		)							->      Tuple:







							"""simple docstring"""


							super().test_save_load_floataa(expected_max_diff=1E-1		)






						def UpperCAmelCase_			( self : Union[str, Any]		)							->      str:







							"""simple docstring"""


							self._test_attention_slicing_forward_pass(expected_max_diff=1E-2		)






						def UpperCAmelCase_			( self : int		)							->      Optional[int]:







							"""simple docstring"""


							self._test_save_load_local()






						def UpperCAmelCase_			( self : List[Any]		)							->      Dict:







							"""simple docstring"""


							self._test_inference_batch_single_identical(
							    expected_max_diff=1E-2						,				)













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=""" """)

