





"""simple docstring"""




import unittest

import torch

from diffusers import DDIMScheduler, TextToVideoZeroPipeline
from diffusers.utils import load_pt, require_torch_gpu, slow

from ..test_pipelines_common import assert_mean_pixel_difference




@slow
@require_torch_gpu
class  _a						(      unittest.TestCase				):






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




										'''simple docstring'''



										_UpperCamelCase			:					List[str]     =    '''runwayml/stable-diffusion-v1-5'''
										_UpperCamelCase			:					str     =    TextToVideoZeroPipeline.from_pretrained(lowerCAmelCase__, torch_dtype=torch.floataa							).to('''cuda'''							)
										_UpperCamelCase			:					Dict     =    DDIMScheduler.from_config(pipe.scheduler.config							)
										_UpperCamelCase			:					int     =    torch.Generator(device='''cuda'''							).manual_seed(0							)

										_UpperCamelCase			:					str     =    '''A bear is playing a guitar on Times Square'''
										_UpperCamelCase			:					Optional[int]     =    pipe(prompt=lowerCAmelCase__, generator=lowerCAmelCase__							).images

										_UpperCamelCase			:					List[str]     =    load_pt(
										    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/text-to-video/A bear is playing a guitar on Times Square.pt'''							)

										assert_mean_pixel_difference(lowerCAmelCase__, lowerCAmelCase__							)










"""simple docstring"""




from functools import lru_cache





@lru_cache
def        a_				(							_lowercase   ):
						if not isinstance(_lowercase       ,						_lowercase   ):
												raise TypeError('''k must be an integer.'''   )
						if k < 0:
												raise ValueError('''k integer must be greater or equal to zero.'''   )
						if k == 0:
												return 0
						elif k == 1:
												return 1
						else:
												return fibonacci(k - 1   ) + fibonacci(k - 2   )





def        a_				(							_lowercase       ,						_lowercase   ):
						_UpperCamelCase			:					Any     =    len(_lowercase   )
						# Find m such that F_m >= n where F_i is the i_th fibonacci number.
						_UpperCamelCase			:					Optional[int]     =    0
						while True:
												if fibonacci(_lowercase   ) >= len_list:
																		_UpperCamelCase			:					List[Any]     =    i
																		break
												i += 1
						_UpperCamelCase			:					Tuple     =    0
						while fibb_k > 0:
												_UpperCamelCase			:					Union[str, Any]     =    min(
												    offset + fibonacci(fibb_k - 1   )       ,						len_list - 1   )  # Prevent out of range
												_UpperCamelCase			:					Any     =    arr[index_k]
												if item_k_1 == val:
																		return index_k
												elif val < item_k_1:
																		fibb_k -= 1
												elif val > item_k_1:
																		offset += fibonacci(fibb_k - 1   )
																		fibb_k -= 2
						else:
												return -1


if __name__ == "__main__":
						import doctest

						doctest.testmod()



