
from typing import List, Optional, Tuple, Union

import torch

from ...models import UNetaDModel
from ...schedulers import PNDMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput







class 							UpperCAmelCase	(   __lowerCamelCase					):
					a__: UNetaDModel
					a__: PNDMScheduler

					def __init__(			self      :					List[str] ,      lowerCAmelCase      :					UNetaDModel ,      lowerCAmelCase      :					PNDMScheduler					):
											super().__init__()

											lowercase       :    int											=  PNDMScheduler.from_config(scheduler.config					)

											self.register_modules(unet=lowerCAmelCase ,      scheduler=lowerCAmelCase					)




					@torch.no_grad()
					def __call__(			self      :					List[str] ,      lowerCAmelCase      :					int = 1 ,      lowerCAmelCase      :					int = 50 ,      lowerCAmelCase      :					Optional[Union[torch.Generator, List[torch.Generator]]] = None ,      lowerCAmelCase      :					Optional[str] = "pil" ,      lowerCAmelCase      :					bool = True ,      **lowerCAmelCase      :					int ,      ):
											lowercase       :    Tuple											=  randn_tensor(
											    (batch_size, self.unet.config.in_channels, self.unet.config.sample_size, self.unet.config.sample_size) ,      generator=lowerCAmelCase ,      device=self.device ,      )

											self.scheduler.set_timesteps(lowerCAmelCase					)
											for t in self.progress_bar(self.scheduler.timesteps					):
																	lowercase       :    Dict											=  self.unet(lowerCAmelCase ,      lowerCAmelCase					).sample

																	lowercase       :    Tuple											=  self.scheduler.step(lowerCAmelCase ,      lowerCAmelCase ,      lowerCAmelCase					).prev_sample

											lowercase       :    Optional[Any]											=  (image / 2 + 0.5).clamp(0 ,      1					)
											lowercase       :    Optional[int]											=  image.cpu().permute(0 ,      2 ,      3 ,      1					).numpy()
											if output_type == "pil":
																	lowercase       :    Union[str, Any]											=  self.numpy_to_pil(lowerCAmelCase					)

											if not return_dict:
																	return (image,)

											return ImagePipelineOutput(images=lowerCAmelCase					)




class 							UpperCAmelCase	:

					def __init__(			self      :					Any ,      lowerCAmelCase      :					int					):
											lowercase       :    Tuple											=  data
											lowercase       :    BinaryTreeNode | None											=  None
											lowercase       :    BinaryTreeNode | None											=  None





def        lowerCamelCase_      (			UpperCAmelCase_							:				BinaryTreeNode | None							,			UpperCAmelCase_							:				int       ):
						if node is None:
												lowercase       :    Union[str, Any]											=  BinaryTreeNode(UpperCAmelCase_       )
												return node

						# binary search tree is not empty,
						# so we will insert it into the tree
						# if new_value is less than value of data in node,
						#  add it to left subtree and proceed recursively
						if new_value < node.data:
												lowercase       :    List[Any]											=  insert(node.left_child							,			UpperCAmelCase_       )
						else:
												# if new_value is greater than value of data in node,
												#  add it to right subtree and proceed recursively
												lowercase       :    Dict											=  insert(node.right_child							,			UpperCAmelCase_       )
						return node

def        lowerCamelCase_      (			UpperCAmelCase_							:				None | BinaryTreeNode       ):  # if node is None,return
						if node:
												lowercase       :    Optional[Any]											=  inorder(node.left_child       )
												lowercase       :    Tuple											=  [*inorder_array, node.data]
												lowercase       :    Optional[Any]											=  inorder_array + inorder(node.right_child       )
						else:
												lowercase       :    Optional[int]											=  []
						return inorder_array

def        lowerCamelCase_      (			):
						lowercase       :    Any											=  insert(UpperCAmelCase_							,			15       )
						insert(UpperCAmelCase_							,			10       )
						insert(UpperCAmelCase_							,			25       )
						insert(UpperCAmelCase_							,			6       )
						insert(UpperCAmelCase_							,			14       )
						insert(UpperCAmelCase_							,			20       )
						insert(UpperCAmelCase_							,			60       )
						return root

def        lowerCamelCase_      (			):
						# main function
						lowercase       :    Any											=  make_tree()
						print('''Printing values of binary search tree in Inorder Traversal.'''       )
						inorder(UpperCAmelCase_       )


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				main()


