




import gc
import tempfile
import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionDualGuidedPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device


UpperCamelCase__						=		False


@nightly
@require_torch_gpu
class 							__SCREAMING_SNAKE_CASE				(						unittest.TestCase    ):

					def       lowercase_				(							self   ):







						'''simple docstring'''




						super().tearDown()
						gc.collect()
						torch.cuda.empty_cache()

					def       lowercase_				(							self   ):







						'''simple docstring'''




						lowerCamelCase_				:						List[Any]				  =				VersatileDiffusionDualGuidedPipeline.from_pretrained('shi-labs/versatile-diffusion'   )
						# remove text_unet
						pipe.remove_unused_weights()
						pipe.to(__lowercase   )
						pipe.set_progress_bar_config(disable=__lowercase   )

						lowerCamelCase_				:						Optional[Any]				  =				load_image(
						    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'   )

						lowerCamelCase_				:						int				  =				torch.manual_seed(0   )
						lowerCamelCase_				:						List[Any]				  =				pipe(
						    prompt='first prompt'					,			image=__lowercase					,			text_to_image_strength=0.75					,			generator=__lowercase					,			guidance_scale=7.5					,			num_inference_steps=2					,			output_type='numpy'					,			).images

						with tempfile.TemporaryDirectory() as tmpdirname:
							pipe.save_pretrained(__lowercase   )
							lowerCamelCase_				:						Dict				  =				VersatileDiffusionDualGuidedPipeline.from_pretrained(__lowercase   )

						pipe.to(__lowercase   )
						pipe.set_progress_bar_config(disable=__lowercase   )

						lowerCamelCase_				:						Optional[Any]				  =				generator.manual_seed(0   )
						lowerCamelCase_				:						List[Any]				  =				pipe(
						    prompt='first prompt'					,			image=__lowercase					,			text_to_image_strength=0.75					,			generator=__lowercase					,			guidance_scale=7.5					,			num_inference_steps=2					,			output_type='numpy'					,			).images

						assert np.abs(image - new_image   ).sum() < 1E-5, "Models don't have the same forward pass"





					def       lowercase_				(							self   ):







						'''simple docstring'''




						lowerCamelCase_				:						Tuple				  =				VersatileDiffusionDualGuidedPipeline.from_pretrained('shi-labs/versatile-diffusion'   )
						pipe.remove_unused_weights()
						pipe.to(__lowercase   )
						pipe.set_progress_bar_config(disable=__lowercase   )

						lowerCamelCase_				:						Union[str, Any]				  =				'cyberpunk 2077'
						lowerCamelCase_				:						Optional[Any]				  =				load_image(
						    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'   )
						lowerCamelCase_				:						str				  =				torch.manual_seed(0   )
						lowerCamelCase_				:						Dict				  =				pipe(
						    prompt=__lowercase					,			image=__lowercase					,			text_to_image_strength=0.75					,			generator=__lowercase					,			guidance_scale=7.5					,			num_inference_steps=50					,			output_type='numpy'					,			).images

						lowerCamelCase_				:						Dict				  =				image[0, 253:256, 253:256, -1]

						assert image.shape == (1, 512, 512, 3)
						lowerCamelCase_				:						List[str]				  =				np.array([0.07_87, 0.08_49, 0.08_26, 0.08_12, 0.08_07, 0.07_95, 0.08_18, 0.07_98, 0.07_79]   )

						assert np.abs(image_slice.flatten() - expected_slice   ).max() < 1E-2








from __future__ import annotations







def 						_UpperCamelCase (     UpperCamelCase_							:       list[int]		)	-> list[int]:

						"""simple docstring"""



						if not list_of_ints:
												return []

						if min(UpperCamelCase_		) < 0:
												raise ValueError('All numbers must be positive'		)

						lowerCAmelCase__         =    max(len(bin(UpperCamelCase_		)[2:]		) for x in list_of_ints		)
						return _msd_radix_sort(UpperCamelCase_     ,							UpperCamelCase_		)







def 						_UpperCamelCase (     UpperCamelCase_							:       list[int]     ,							UpperCamelCase_							:       int		)	-> list[int]:

						"""simple docstring"""



						if bit_position == 0 or len(UpperCamelCase_		) in [0, 1]:
												return list_of_ints

						lowerCAmelCase__         =    []
						lowerCAmelCase__         =    []
						# Split numbers based on bit at bit_position from the right
						for number in list_of_ints:
												if (number >> (bit_position - 1)) & 1:
																		# number has a one at bit bit_position
																		ones.append(UpperCamelCase_		)
												else:
																		# number has a zero at bit bit_position
																		zeros.append(UpperCamelCase_		)

    # recursively split both lists further
						lowerCAmelCase__         =    _msd_radix_sort(UpperCamelCase_     ,							bit_position - 1		)
						lowerCAmelCase__         =    _msd_radix_sort(UpperCamelCase_     ,							bit_position - 1		)

						# recombine lists
						lowerCAmelCase__         =    zeros
						res.extend(UpperCamelCase_		)

						return res







def 						_UpperCamelCase (     UpperCamelCase_							:       list[int]		)	-> Any:

						"""simple docstring"""



						lowerCAmelCase__         =    len(UpperCamelCase_		)
						if not list_of_ints or length == 1:
												return

						if min(UpperCamelCase_		) < 0:
												raise ValueError('All numbers must be positive'		)

						lowerCAmelCase__         =    max(len(bin(UpperCamelCase_		)[2:]		) for x in list_of_ints		)
						_msd_radix_sort_inplace(UpperCamelCase_     ,							UpperCamelCase_     ,							0     ,							UpperCamelCase_		)







def 						_UpperCamelCase (     UpperCamelCase_							:       list[int]     ,							UpperCamelCase_							:       int     ,							UpperCamelCase_							:       int     ,							UpperCamelCase_							:       int		)	-> int:

						"""simple docstring"""



						if bit_position == 0 or end_index - begin_index <= 1:
												return

						bit_position -= 1

						lowerCAmelCase__         =    begin_index
						lowerCAmelCase__         =    end_index - 1
						while i <= j:
												lowerCAmelCase__         =    False
												if not (list_of_ints[i] >> bit_position) & 1:
																		# found zero at the beginning
																		i += 1
																		lowerCAmelCase__         =    True
												if (list_of_ints[j] >> bit_position) & 1:
																		# found one at the end
																		j -= 1
																		lowerCAmelCase__         =    True

												if changed:
																		continue

												lowerCAmelCase__    ,							lowerCAmelCase__         =    list_of_ints[j], list_of_ints[i]
												j -= 1
												if j != i:
																		i += 1

						_msd_radix_sort_inplace(UpperCamelCase_     ,							UpperCamelCase_     ,							UpperCamelCase_     ,							UpperCamelCase_		)
						_msd_radix_sort_inplace(UpperCamelCase_     ,							UpperCamelCase_     ,							UpperCamelCase_     ,							UpperCamelCase_		)


if __name__ == "__main__":
					import doctest

					doctest.testmod()





