





import unittest
from dataclasses import dataclass
from typing import List, Union

import numpy as np
import PIL.Image

from diffusers.utils.outputs import BaseOutput



@dataclass
class  _a  (					lowercase__				):






							"""simple docstring"""

							snake_case_							=    42







class  _a  (					unittest.TestCase				):






							"""simple docstring"""

							def   A_	(   self					:  Union[str, Any]     )						->Dict:
													SCREAMING_SNAKE_CASE__  :					Optional[Any] =       CustomOutput(images=np.random.rand(1				,						3				,						4				,						4     )     )

													# check every way of getting the attribute
													assert isinstance(outputs.images				,						np.ndarray     )
													assert outputs.images.shape == (1, 3, 4, 4)
													assert isinstance(outputs["images"]				,						np.ndarray     )
													assert outputs["images"].shape == (1, 3, 4, 4)
													assert isinstance(outputs[0]				,						np.ndarray     )
													assert outputs[0].shape == (1, 3, 4, 4)

													# test with a non-tensor attribute
													SCREAMING_SNAKE_CASE__  :					Optional[int] =       CustomOutput(images=[PIL.Image.new("RGB"				,						(4, 4)     )]     )

													# check every way of getting the attribute
													assert isinstance(outputs.images				,						a     )
													assert isinstance(outputs.images[0]				,						PIL.Image.Image     )
													assert isinstance(outputs["images"]				,						a     )
													assert isinstance(outputs["images"][0]				,						PIL.Image.Image     )
													assert isinstance(outputs[0]				,						a     )
													assert isinstance(outputs[0][0]				,						PIL.Image.Image     )






							def   A_	(   self					:  int     )						->Optional[Any]:
													# test output reinitialization with a `dict` for compatibility with `accelerate`
													SCREAMING_SNAKE_CASE__  :					Any =       CustomOutput({"images": np.random.rand(1				,						3				,						4				,						4     )}     )

													# check every way of getting the attribute
													assert isinstance(outputs.images				,						np.ndarray     )
													assert outputs.images.shape == (1, 3, 4, 4)
													assert isinstance(outputs["images"]				,						np.ndarray     )
													assert outputs["images"].shape == (1, 3, 4, 4)
													assert isinstance(outputs[0]				,						np.ndarray     )
													assert outputs[0].shape == (1, 3, 4, 4)

													# test with a non-tensor attribute
													SCREAMING_SNAKE_CASE__  :					Optional[Any] =       CustomOutput({"images": [PIL.Image.new("RGB"				,						(4, 4)     )]}     )

													# check every way of getting the attribute
													assert isinstance(outputs.images				,						a     )
													assert isinstance(outputs.images[0]				,						PIL.Image.Image     )
													assert isinstance(outputs["images"]				,						a     )
													assert isinstance(outputs["images"][0]				,						PIL.Image.Image     )
													assert isinstance(outputs[0]				,						a     )
													assert isinstance(outputs[0][0]				,						PIL.Image.Image     )






from itertools import combinations_with_replacement







def    UpperCAmelCase				(  _lowerCamelCase   :	int = 100  ):





						'''simple docstring'''


						SCREAMING_SNAKE_CASE__  :					list[int] =       [*list(range(1      , 21  )  ), 25]
						SCREAMING_SNAKE_CASE__  :					list[int] =       [2 * x for x in range(1      , 21  )] + [50]
						SCREAMING_SNAKE_CASE__  :					list[int] =       [3 * x for x in range(1      , 21  )]
						SCREAMING_SNAKE_CASE__  :					list[int] =       singles + doubles + triples + [0]

						SCREAMING_SNAKE_CASE__  :					int =       0
						SCREAMING_SNAKE_CASE__  :					int
						SCREAMING_SNAKE_CASE__  :					int
						SCREAMING_SNAKE_CASE__  :					int
						SCREAMING_SNAKE_CASE__  :					int

						for double in doubles:
												for throwa, throwa in combinations_with_replacement(_lowerCamelCase      , 2  ):
																		SCREAMING_SNAKE_CASE__  :					int =       double + throwa + throwa
																		if checkout_total < limit:
																								num_checkouts += 1

						return num_checkouts


if __name__ == "__main__":
				print(f"{solution() = }")