"""simple docstring"""


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


a							=False






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

				def 		_a	(      self      ):
										# clean up the VRAM after each test
										super().tearDown()
										gc.collect()
										torch.cuda.empty_cache()

				def 		_a	(      self      ):
										lowerCamelCase__					=VersatileDiffusionDualGuidedPipeline.from_pretrained("shi-labs/versatile-diffusion"      )
										# remove text_unet
										pipe.remove_unused_weights()
										pipe.to(lowerCamelCase__      )
										pipe.set_progress_bar_config(disable=lowerCamelCase__      )

										lowerCamelCase__					=load_image(
										    "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg"      )

										lowerCamelCase__					=torch.manual_seed(0      )
										lowerCamelCase__					=pipe(
										    prompt="first prompt"	, image=lowerCamelCase__	, text_to_image_strength=0.7_5	, generator=lowerCamelCase__	, guidance_scale=7.5	, num_inference_steps=2	, output_type="numpy"	, ).images

										with tempfile.TemporaryDirectory() as tmpdirname:
																pipe.save_pretrained(lowerCamelCase__      )
																lowerCamelCase__					=VersatileDiffusionDualGuidedPipeline.from_pretrained(lowerCamelCase__      )

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

										lowerCamelCase__					=generator.manual_seed(0      )
										lowerCamelCase__					=pipe(
										    prompt="first prompt"	, image=lowerCamelCase__	, text_to_image_strength=0.7_5	, generator=lowerCamelCase__	, 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 		_a	(      self      ):
										lowerCamelCase__					=VersatileDiffusionDualGuidedPipeline.from_pretrained("shi-labs/versatile-diffusion"      )
										pipe.remove_unused_weights()
										pipe.to(lowerCamelCase__      )
										pipe.set_progress_bar_config(disable=lowerCamelCase__      )

										lowerCamelCase__					="cyberpunk 2077"
										lowerCamelCase__					=load_image(
										    "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg"      )
										lowerCamelCase__					=torch.manual_seed(0      )
										lowerCamelCase__					=pipe(
										    prompt=lowerCamelCase__	, image=lowerCamelCase__	, text_to_image_strength=0.7_5	, generator=lowerCamelCase__	, guidance_scale=7.5	, num_inference_steps=50	, output_type="numpy"	, ).images

										lowerCamelCase__					=image[0, 253:256, 253:256, -1]

										assert image.shape == (1, 512, 512, 3)
										lowerCamelCase__					=np.array([0.0_7_8_7, 0.0_8_4_9, 0.0_8_2_6, 0.0_8_1_2, 0.0_8_0_7, 0.0_7_9_5, 0.0_8_1_8, 0.0_7_9_8, 0.0_7_7_9]      )

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







"""simple docstring"""
from .stack import Stack



def 				lowerCAmelCase_(      lowercase_   :							str							)		->				bool:
				_lowerCamelCase					     = Stack()
				_lowerCamelCase					     = {'''(''': ''')''', '''[''': ''']''', '''{''': '''}'''}
				for bracket in parentheses:
								if bracket in bracket_pairs:
												stack.push(lowercase_							)
								elif bracket in (")", "]", "}"):
												if stack.is_empty() or bracket_pairs[stack.pop()] != bracket:
																return False
				return stack.is_empty()


if __name__ == "__main__":
			from doctest import testmod

			testmod()

			__SCREAMING_SNAKE_CASE     :  Optional[Any]										=					['''((()))''', '''((())''', '''(()))''']
			print('''Balanced parentheses demonstration:\n''')
			for example in examples:
						__SCREAMING_SNAKE_CASE     :  Any										=					'''''' if balanced_parentheses(example) else '''not '''
						print(F"""{example} is {not_str}balanced""")
