

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 						__lowercase       (				UpperCAmelCase_			):




			"""simple docstring"""







			_UpperCAmelCase     :							UNetaDModel
			_UpperCAmelCase     :							PNDMScheduler



			def __init__(				self						:  Optional[int]     ,		lowerCAmelCase__						:  UNetaDModel     ,		lowerCAmelCase__						:  PNDMScheduler):
									super().__init__()

									SCREAMING_SNAKE_CASE_:				Dict							= PNDMScheduler.from_config(scheduler.config)

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




			@torch.no_grad()
			def __call__(				self						:  int     ,		lowerCAmelCase__						:  int = 1     ,		lowerCAmelCase__						:  int = 50     ,		lowerCAmelCase__						:  Optional[Union[torch.Generator, List[torch.Generator]]] = None     ,		lowerCAmelCase__						:  Optional[str] = "pil"     ,		lowerCAmelCase__						:  bool = True     ,		**lowerCAmelCase__						:  str     ,		):
									SCREAMING_SNAKE_CASE_:				Dict							= 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):
															SCREAMING_SNAKE_CASE_:				Union[str, Any]							= self.unet(lowerCAmelCase__     ,		lowerCAmelCase__).sample

															SCREAMING_SNAKE_CASE_:				Any							= self.scheduler.step(lowerCAmelCase__     ,		lowerCAmelCase__     ,		lowerCAmelCase__).prev_sample

									SCREAMING_SNAKE_CASE_:				Optional[Any]							= (image / 2 + 0.5).clamp(0     ,		1)
									SCREAMING_SNAKE_CASE_:				Dict							= image.cpu().permute(0     ,		2     ,		3     ,		1).numpy()
									if output_type == "pil":
															SCREAMING_SNAKE_CASE_:				Any							= self.numpy_to_pil(lowerCAmelCase__)

									if not return_dict:
															return (image,)

									return ImagePipelineOutput(images=lowerCAmelCase__)









import heapq







def     A_   (					_UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase					):
						SCREAMING_SNAKE_CASE_:				List[Any]							= [(0, start)]  # cost from start node,end node
						SCREAMING_SNAKE_CASE_:				Any							= set()
						while heap:
												((SCREAMING_SNAKE_CASE_)	,					(SCREAMING_SNAKE_CASE_)):				Tuple							= heapq.heappop(_UpperCAmelCase					)
												if u in visited:
																		continue
												visited.add(_UpperCAmelCase					)
												if u == end:
																		return cost
												for v, c in graph[u]:
																		if v in visited:
																								continue
																		SCREAMING_SNAKE_CASE_:				List[str]							= cost + c
																		heapq.heappush(_UpperCAmelCase       ,			(next_item, v)					)
						return -1


lowerCAmelCase							:						Optional[Any]     			=		{
    """A""": [["""B""", 2], ["""C""", 5]],
    """B""": [["""A""", 2], ["""D""", 3], ["""E""", 1], ["""F""", 1]],
    """C""": [["""A""", 5], ["""F""", 3]],
    """D""": [["""B""", 3]],
    """E""": [["""B""", 4], ["""F""", 3]],
    """F""": [["""C""", 3], ["""E""", 3]],
}
lowerCAmelCase							:						Tuple     			=		{
    """B""": [["""C""", 1]],
    """C""": [["""D""", 1]],
    """D""": [["""F""", 1]],
    """E""": [["""B""", 1], ["""F""", 3]],
    """F""": [],
}
lowerCAmelCase							:						str     			=		{
    """B""": [["""C""", 1]],
    """C""": [["""D""", 1]],
    """D""": [["""F""", 1]],
    """E""": [["""B""", 1], ["""G""", 2]],
    """F""": [],
    """G""": [["""F""", 1]],
}

lowerCAmelCase							:						Union[str, Any]     			=		dijkstra(G, """E""", """C""")
print(short_distance)  # E -- 3 --> F -- 3 --> C == 6

lowerCAmelCase							:						Tuple     			=		dijkstra(Ga, """E""", """F""")
print(short_distance)  # E -- 3 --> F == 3

lowerCAmelCase							:						Union[str, Any]     			=		dijkstra(Ga, """E""", """F""")
print(short_distance)  # E -- 2 --> G -- 1 --> F == 3

if __name__ == "__main__":
						import doctest

						doctest.testmod()






