





# limitations under the License.


from typing import Optional, Tuple, Union

import torch

from diffusers import DiffusionPipeline, ImagePipelineOutput

class 							__SCREAMING_SNAKE_CASE       (  _a							):






							def __init__(    self	,			__lowerCAmelCase	,			__lowerCAmelCase	):
														super().__init__()
														self.register_modules(unet=__lowerCAmelCase	,			scheduler=__lowerCAmelCase	)







							@torch.no_grad()
							def __call__(    self	,			__lowerCAmelCase = 1	,			__lowerCAmelCase = None	,			__lowerCAmelCase = 50	,			__lowerCAmelCase = "pil"	,			__lowerCAmelCase = True	,			**__lowerCAmelCase	,			):
														UpperCamelCase__					  =      torch.randn(
														    (batch_size, self.unet.config.in_channels, self.unet.config.sample_size, self.unet.config.sample_size)	,			generator=__lowerCAmelCase	,			)
														UpperCamelCase__					  =      image.to(self.device	)

														# set step values
														self.scheduler.set_timesteps(__lowerCAmelCase	)

														for t in self.progress_bar(self.scheduler.timesteps	):
																					# 1. predict noise model_output
																					UpperCamelCase__					  =      self.unet(__lowerCAmelCase	,			__lowerCAmelCase	).sample

																					# 2. predict previous mean of image x_t-1 and add variance depending on eta
																					# eta corresponds to η in paper and should be between [0, 1]
																					# do x_t -> x_t-1
																					UpperCamelCase__					  =      self.scheduler.step(__lowerCAmelCase	,			__lowerCAmelCase	,			__lowerCAmelCase	).prev_sample

														UpperCamelCase__					  =      (image / 2 + 0.5).clamp(0	,			1	)
														UpperCamelCase__					  =      image.cpu().permute(0	,			2	,			3	,			1	).numpy()
														if output_type == "pil":
																					UpperCamelCase__					  =      self.numpy_to_pil(__lowerCAmelCase	)

														if not return_dict:
																					return (image,), "This is a local test"

														return ImagePipelineOutput(images=__lowerCAmelCase	), "This is a local test"











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__           =			10





def      _UpperCamelCase  (a__ :int ,      a__ :int ,      a__ :list[int] ,      a__ :int							):






							"""simple docstring"""





							for i in range(a__ ,      a__							):
														if array[i] == target:
																					return i
							return -1





def      _UpperCamelCase  (a__ :list[int] ,      a__ :int							):






							"""simple docstring"""





							UpperCamelCase__					  =      0
							UpperCamelCase__					  =      len(a__							)
							while left <= right:
														if right - left < precision:
																					return lin_search(a__ ,      a__ ,      a__ ,      a__							)

														UpperCamelCase__					  =      (left + right) // 3 + 1
														UpperCamelCase__					  =      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]:
																					UpperCamelCase__					  =      one_third - 1
														elif array[two_third] < target:
																					UpperCamelCase__					  =      two_third + 1

														else:
																					UpperCamelCase__					  =      one_third + 1
																					UpperCamelCase__					  =      two_third - 1
							else:
														return -1





def      _UpperCamelCase  (a__ :int ,      a__ :int ,      a__ :list[int] ,      a__ :int							):






							"""simple docstring"""





							if left < right:
														if right - left < precision:
																					return lin_search(a__ ,      a__ ,      a__ ,      a__							)
														UpperCamelCase__					  =      (left + right) // 3 + 1
														UpperCamelCase__					  =      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(a__ ,      one_third - 1 ,      a__ ,      a__							)
														elif array[two_third] < target:
																					return rec_ternary_search(two_third + 1 ,      a__ ,      a__ ,      a__							)
														else:
																					return rec_ternary_search(one_third + 1 ,      two_third - 1 ,      a__ ,      a__							)
							else:
														return -1


if __name__ == "__main__":
					import doctest

					doctest.testmod()

					UpperCamelCase__           =			input("Enter numbers separated by comma:\n").strip()
					UpperCamelCase__           =			[int(item.strip()) for item in user_input.split(",")]
					assert collection == sorted(collection), f"List must be ordered.\n{collection}."
					UpperCamelCase__           =			int(input("Enter the number to be found in the list:\n").strip())
					UpperCamelCase__           =			ite_ternary_search(collection, target)
					UpperCamelCase__           =			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")




