



'''simple docstring'''



import sys
from collections import defaultdict
class 	lowerCamelCase_							:







						def __init__(  self   :      List[Any]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Any     					=			[]







						def 					__lowercase    (  self   :      Any				,    lowerCAmelCase__   :      Union[str, Any]				):

													"""simple docstring"""
													return self.node_position[vertex]







						def 					__lowercase    (  self   :      int				,    lowerCAmelCase__   :      Optional[int]				,    lowerCAmelCase__   :      List[Any]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			pos







						def 					__lowercase    (  self   :      int				,    lowerCAmelCase__   :      Dict				,    lowerCAmelCase__   :      int				,    lowerCAmelCase__   :      Union[str, Any]				,    lowerCAmelCase__   :      Union[str, Any]				):

													"""simple docstring"""
													if start > size // 2 - 1:
																				return
													else:
																				if 2 * start + 2 >= size:
																											SCREAMING_SNAKE_CASE					:      List[Any]     					=			2 * start + 1
																				else:
																											if heap[2 * start + 1] < heap[2 * start + 2]:
																																		SCREAMING_SNAKE_CASE					:      Optional[int]     					=			2 * start + 1
																											else:
																																		SCREAMING_SNAKE_CASE					:      Optional[int]     					=			2 * start + 2
																				if heap[smallest_child] < heap[start]:
																											SCREAMING_SNAKE_CASE					,SCREAMING_SNAKE_CASE					:      Tuple     					=			heap[smallest_child], positions[smallest_child]
																											SCREAMING_SNAKE_CASE					,SCREAMING_SNAKE_CASE					:      Any     					=			(
																											    heap[start],
																											    positions[start],
																											)
																											SCREAMING_SNAKE_CASE					,SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			temp, tempa

																											SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			self.get_position(positions[smallest_child]				)
																											self.set_position(
																											    positions[smallest_child]				,    self.get_position(positions[start]				)				)
																											self.set_position(positions[start]				,    lowerCAmelCase__				)

																											self.top_to_bottom(lowerCAmelCase__				,    lowerCAmelCase__				,    lowerCAmelCase__				,    lowerCAmelCase__				)







						def 					__lowercase    (  self   :      List[Any]				,    lowerCAmelCase__   :      Dict				,    lowerCAmelCase__   :      List[str]				,    lowerCAmelCase__   :      int				,    lowerCAmelCase__   :      List[str]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Any     					=			position[index]

													while index != 0:
																				SCREAMING_SNAKE_CASE					:      int     					=			int((index - 2) / 2				) if index % 2 == 0 else int((index - 1) / 2				)

																				if val < heap[parent]:
																											SCREAMING_SNAKE_CASE					:      Tuple     					=			heap[parent]
																											SCREAMING_SNAKE_CASE					:      Any     					=			position[parent]
																											self.set_position(position[parent]				,    lowerCAmelCase__				)
																				else:
																											SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			val
																											SCREAMING_SNAKE_CASE					:      Dict     					=			temp
																											self.set_position(lowerCAmelCase__				,    lowerCAmelCase__				)
																											break
																				SCREAMING_SNAKE_CASE					:      Tuple     					=			parent
													else:
																				SCREAMING_SNAKE_CASE					:      Tuple     					=			val
																				SCREAMING_SNAKE_CASE					:      List[Any]     					=			temp
																				self.set_position(lowerCAmelCase__				,    0				)







						def 					__lowercase    (  self   :      Any				,    lowerCAmelCase__   :      Any				,    lowerCAmelCase__   :      Dict				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Tuple     					=			len(lowerCAmelCase__				) // 2 - 1
													for i in range(lowerCAmelCase__				,    -1				,    -1				):
																				self.top_to_bottom(lowerCAmelCase__				,    lowerCAmelCase__				,    len(lowerCAmelCase__				)				,    lowerCAmelCase__				)







						def 					__lowercase    (  self   :      List[Any]				,    lowerCAmelCase__   :      Union[str, Any]				,    lowerCAmelCase__   :      Optional[int]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			positions[0]
													SCREAMING_SNAKE_CASE					:      Dict     					=			sys.maxsize
													self.top_to_bottom(lowerCAmelCase__				,    0				,    len(lowerCAmelCase__				)				,    lowerCAmelCase__				)
													return temp


def 					UpperCAmelCase   (						A  :				Dict				):
							SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			Heap()

							SCREAMING_SNAKE_CASE					:      str     					=			[0] * len(A				)
							SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			[-1] * len(A				)  # Neighboring Tree Vertex of selected vertex
							# Minimum Distance of explored vertex with neighboring vertex of partial tree
							# formed in graph
							SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			[]  # Heap of Distance of vertices from their neighboring vertex
							SCREAMING_SNAKE_CASE					:      Tuple     					=			[]

							for vertex in range(len(A				)				):
														distance_tv.append(sys.maxsize				)
														positions.append(A				)
														heap.node_position.append(A				)

							SCREAMING_SNAKE_CASE					:      Dict     					=			[]
							SCREAMING_SNAKE_CASE					:      Any     					=			1
							SCREAMING_SNAKE_CASE					:      int     					=			sys.maxsize
							for neighbor, distance in adjacency_list[0]:
														SCREAMING_SNAKE_CASE					:      Tuple     					=			0
														SCREAMING_SNAKE_CASE					:      Any     					=			distance
							heap.heapify(A					,		A				)

							for _ in range(1					,		len(A				)				):
														SCREAMING_SNAKE_CASE					:      Optional[int]     					=			heap.delete_minimum(A					,		A				)
														if visited[vertex] == 0:
																					tree_edges.append((nbr_tv[vertex], vertex)				)
																					SCREAMING_SNAKE_CASE					:      Dict     					=			1
																					for neighbor, distance in adjacency_list[vertex]:
																												if (
																												    visited[neighbor] == 0
																												    and distance < distance_tv[heap.get_position(A				)]
																												):
																																			SCREAMING_SNAKE_CASE					:      List[str]     					=			distance
																																			heap.bottom_to_top(
																																			    A					,		heap.get_position(A				)					,		A					,		A				)
																																			SCREAMING_SNAKE_CASE					:      List[Any]     					=			vertex
							return tree_edges


if __name__ == "__main__":  # pragma: no cover
							# < --------- Prims Algorithm --------- >
							lowerCAmelCase_     :       str								=						int(input('Enter number of edges: ').strip())
							lowerCAmelCase_     :       Any								=						defaultdict(list)
							for _ in range(edges_number):
														lowerCAmelCase_     :       Union[str, Any]								=						[int(x) for x in input().strip().split()]
														adjacency_list[edge[0]].append([edge[1], edge[2]])
														adjacency_list[edge[1]].append([edge[0], edge[2]])
							print(prisms_algorithm(adjacency_list))









'''simple docstring'''



import darl  # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline


lowerCAmelCase_     :       int								=						{
    'n_samples': 64,
    'horizon': 32,
    'num_inference_steps': 20,
    'n_guide_steps': 2,  # can set to 0 for faster sampling, does not use value network
    'scale_grad_by_std': True,
    'scale': 0.1,
    'eta': 0.0,
    't_grad_cutoff': 2,
    'device': 'cpu',
}


if __name__ == "__main__":
							lowerCAmelCase_     :       int								=						'hopper-medium-v2'
							lowerCAmelCase_     :       str								=						gym.make(env_name)

							lowerCAmelCase_     :       Union[str, Any]								=						ValueGuidedRLPipeline.from_pretrained(
							    'bglick13/hopper-medium-v2-value-function-hor32',
							    env=env,
							)

							env.seed(0)
							lowerCAmelCase_     :       Any								=						env.reset()
							lowerCAmelCase_     :       Any								=						0
							lowerCAmelCase_     :       Tuple								=						0
							lowerCAmelCase_     :       str								=						1000
							lowerCAmelCase_     :       int								=						[obs.copy()]
							try:
														for t in tqdm.tqdm(range(T)):
																					# call the policy
																					lowerCAmelCase_     :       int								=						pipeline(obs, planning_horizon=32)

																					# execute action in environment
																					lowerCAmelCase_			,							lowerCAmelCase_			,							lowerCAmelCase_			,							lowerCAmelCase_     :       Union[str, Any]								=						env.step(denorm_actions)
																					lowerCAmelCase_     :       Optional[int]								=						env.get_normalized_score(total_reward)

																					# update return
																					total_reward += reward
																					total_score += score
																					print(
																					    f'Step: {t}, Reward: {reward}, Total Reward: {total_reward}, Score: {score}, Total Score:'
																					    f' {total_score}'
																					)

																					# save observations for rendering
																					rollout.append(next_observation.copy())

																					lowerCAmelCase_     :       Union[str, Any]								=						next_observation
							except KeyboardInterrupt:
														pass

							print(f'Total reward: {total_reward}')




