


import unittest

import torch

from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow


_UpperCAmelCase			:  List[Any]     =False







class 				snake_case__(							unittest.TestCase							):







						'''simple docstring'''




						def 						lowercase_ (				self   ,						__lowercase=3_2							)					->    int:
										set_seed(0							)
										lowerCAmelCase_ :      Union[str, Any]    				=				UNetaDModel(sample_size=__lowercase   ,						in_channels=3   ,						out_channels=3							)
										lowerCAmelCase_ :      Union[str, Any]    				=				torch.optim.SGD(model.parameters()   ,						lr=0.00_01							)
										return model, optimizer




						@slow
						def 						lowercase_ (				self							)					->    Tuple:
										lowerCAmelCase_ :      str    				=				'''cpu'''  # ensure full determinism without setting the CUBLAS_WORKSPACE_CONFIG env variable
										lowerCAmelCase_ :      Optional[int]    				=				DDPMScheduler(
										    num_train_timesteps=1_0_0_0   ,						beta_start=0.00_01   ,						beta_end=0.02   ,						beta_schedule='''linear'''   ,						clip_sample=__lowercase   ,						)
										lowerCAmelCase_ :      int    				=				DDIMScheduler(
										    num_train_timesteps=1_0_0_0   ,						beta_start=0.00_01   ,						beta_end=0.02   ,						beta_schedule='''linear'''   ,						clip_sample=__lowercase   ,						)

										assert ddpm_scheduler.config.num_train_timesteps == ddim_scheduler.config.num_train_timesteps

										# shared batches for DDPM and DDIM
										set_seed(0							)
										lowerCAmelCase_ :      int    				=				[torch.randn((4, 3, 3_2, 3_2)							).clip(-1   ,						1							).to(__lowercase							) for _ in range(4							)]
										lowerCAmelCase_ :      Union[str, Any]    				=				[torch.randn((4, 3, 3_2, 3_2)							).to(__lowercase							) for _ in range(4							)]
										lowerCAmelCase_ :      int    				=				[torch.randint(0   ,						1_0_0_0   ,						(4,)							).long().to(__lowercase							) for _ in range(4							)]

										# train with a DDPM scheduler
										lowerCAmelCase_				,  lowerCAmelCase_ :      Optional[Any]    				=				self.get_model_optimizer(resolution=3_2							)
										model.train().to(__lowercase							)
										for i in range(4							):
														optimizer.zero_grad()
														lowerCAmelCase_ :      int    				=				ddpm_scheduler.add_noise(clean_images[i]   ,						noise[i]   ,						timesteps[i]							)
														lowerCAmelCase_ :      Dict    				=				model(__lowercase   ,						timesteps[i]							).sample
														lowerCAmelCase_ :      Tuple    				=				torch.nn.functional.mse_loss(__lowercase   ,						noise[i]							)
														loss.backward()
														optimizer.step()
										del model, optimizer

										# recreate the model and optimizer, and retry with DDIM
										lowerCAmelCase_				,  lowerCAmelCase_ :      Union[str, Any]    				=				self.get_model_optimizer(resolution=3_2							)
										model.train().to(__lowercase							)
										for i in range(4							):
														optimizer.zero_grad()
														lowerCAmelCase_ :      Optional[Any]    				=				ddim_scheduler.add_noise(clean_images[i]   ,						noise[i]   ,						timesteps[i]							)
														lowerCAmelCase_ :      Union[str, Any]    				=				model(__lowercase   ,						timesteps[i]							).sample
														lowerCAmelCase_ :      Optional[int]    				=				torch.nn.functional.mse_loss(__lowercase   ,						noise[i]							)
														loss.backward()
														optimizer.step()
										del model, optimizer

										self.assertTrue(torch.allclose(__lowercase   ,						__lowercase   ,						atol=1e-5							)							)
										self.assertTrue(torch.allclose(__lowercase   ,						__lowercase   ,						atol=1e-5							)							)



from __future__ import annotations

# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
_UpperCAmelCase			:  Tuple     =10



def 			lowerCAmelCase (		lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ )-> int:
				for i in range(lowerCAmelCase_ ,   lowerCAmelCase_ ):
								if array[i] == target:
												return i
				return -1



def 			lowerCAmelCase (		lowerCAmelCase_ ,   lowerCAmelCase_ )-> int:
				lowerCAmelCase_ :      Any    				=				0
				lowerCAmelCase_ :      int    				=				len(lowerCAmelCase_ )
				while left <= right:
								if right - left < precision:
												return lin_search(lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ )

								lowerCAmelCase_ :      List[Any]    				=				(left + right) // 3 + 1
								lowerCAmelCase_ :      List[str]    				=				2 * (left + right) // 3 + 1

								if array[one_third] == target:
												return one_third
								elif array[two_third] == target:
												return two_third

								elif target < array[one_third]:
												lowerCAmelCase_ :      Dict    				=				one_third - 1
								elif array[two_third] < target:
												lowerCAmelCase_ :      List[Any]    				=				two_third + 1

								else:
												lowerCAmelCase_ :      Union[str, Any]    				=				one_third + 1
												lowerCAmelCase_ :      Tuple    				=				two_third - 1
				else:
								return -1



def 			lowerCAmelCase (		lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ )-> int:
				if left < right:
								if right - left < precision:
												return lin_search(lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ )
								lowerCAmelCase_ :      Union[str, Any]    				=				(left + right) // 3 + 1
								lowerCAmelCase_ :      Optional[int]    				=				2 * (left + right) // 3 + 1

								if array[one_third] == target:
												return one_third
								elif array[two_third] == target:
												return two_third

								elif target < array[one_third]:
												return rec_ternary_search(lowerCAmelCase_ ,   one_third - 1 ,   lowerCAmelCase_ ,   lowerCAmelCase_ )
								elif array[two_third] < target:
												return rec_ternary_search(two_third + 1 ,   lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ )
								else:
												return rec_ternary_search(one_third + 1 ,   two_third - 1 ,   lowerCAmelCase_ ,   lowerCAmelCase_ )
				else:
								return -1


if __name__ == "__main__":
						import doctest

						doctest.testmod()

						_UpperCAmelCase			:  Tuple     =input("""Enter numbers separated by comma:\n""").strip()
						_UpperCAmelCase			:  Union[str, Any]     =[int(item.strip()) for item in user_input.split(""",""")]
						assert collection == sorted(collection), f"List must be ordered.\n{collection}."
						_UpperCAmelCase			:  int     =int(input("""Enter the number to be found in the list:\n""").strip())
						_UpperCAmelCase			:  Optional[Any]     =ite_ternary_search(collection, target)
						_UpperCAmelCase			:  List[str]     =rec_ternary_search(0, len(collection) - 1, collection, target)
						if resulta != -1:
												print(f"""Iterative search: {target} found at positions: {resulta}""")
												print(f"""Recursive search: {target} found at positions: {resulta}""")
						else:
												print("""Not found""")