






"""simple docstring"""



def 			_snake_case    (					lowerCamelCase__     :   list[list]  )    ->     list[list]:
							lowerCamelCase_	:							Optional[Any]									=current_set.copy()
							for row_index, row in enumerate(lowerCamelCase__  ):
														lowerCamelCase_	:							List[str]									=row[0]
														for column_index, column in enumerate(lowerCamelCase__  ):
																					if magnitude == 0:
																												lowerCamelCase_	:							Union[str, Any]									=column
																												continue
																					lowerCamelCase_	:							List[Any]									=column / magnitude
    # Subtract to cancel term
							lowerCamelCase_	:							Any									=current_set[0]
							lowerCamelCase_	:							Optional[Any]									=[first_row]
							lowerCamelCase_	:							str									=current_set[1::]
							for row in current_set:
														lowerCamelCase_	:							str									=[]
														# If first term is 0, it is already in form we want, so we preserve it
														if row[0] == 0:
																					final_set.append(lowerCamelCase__  )
																					continue
														for column_index in range(len(lowerCamelCase__  )  ):
																					temp_row.append(first_row[column_index] - row[column_index]  )
														final_set.append(lowerCamelCase__  )
							# Create next recursion iteration set
							if len(final_set[0]  ) != 3:
														lowerCamelCase_	:							str									=final_set[0]
														lowerCamelCase_	:							Optional[Any]									=[]
														lowerCamelCase_	:							List[Any]									=[]
														for row in final_set[1::]:
																					current_first_column.append(row[0]  )
																					next_iteration.append(row[1::]  )
														lowerCamelCase_	:							Dict									=simplify(lowerCamelCase__  )
														for i in range(len(lowerCamelCase__  )  ):
																					resultant[i].insert(0    ,						current_first_column[i]  )
														resultant.insert(0    ,						lowerCamelCase__  )
														lowerCamelCase_	:							Union[str, Any]									=resultant
							return final_set

def 			_snake_case    (					lowerCamelCase__     :   list[list]  )    ->     list:
							if len(lowerCamelCase__  ) == 0:
														raise IndexError("solve_simultaneous() requires n lists of length n+1"  )
							lowerCamelCase_	:							List[str]									=len(lowerCamelCase__  ) + 1
							if any(len(lowerCamelCase__  ) != _length for item in equations  ):
														raise IndexError("solve_simultaneous() requires n lists of length n+1"  )
							for row in equations:
														if any(not isinstance(lowerCamelCase__    ,						(int, float)  ) for column in row  ):
																					raise ValueError("solve_simultaneous() requires lists of integers"  )
							if len(lowerCamelCase__  ) == 1:
														return [equations[0][-1] / equations[0][0]]
							lowerCamelCase_	:							List[Any]									=equations.copy()
							if any(0 in row for row in data_set  ):
														lowerCamelCase_	:							Optional[int]									=data_set.copy()
														lowerCamelCase_	:							Union[str, Any]									=[]
														for row_index, row in enumerate(lowerCamelCase__  ):
																					if 0 not in row:
																												lowerCamelCase_	:							Optional[int]									=data_set.pop(lowerCamelCase__  )
																												break
														if not full_row:
																					raise ValueError("solve_simultaneous() requires at least 1 full equation"  )
														data_set.insert(0    ,						lowerCamelCase__  )
							lowerCamelCase_	:							Optional[Any]									=data_set.copy()
							lowerCamelCase_	:							List[str]									=simplify(lowerCamelCase__  )
							lowerCamelCase_	:							Optional[Any]									=simplified[::-1]
							lowerCamelCase_	:							list									=[]
							for row in simplified:
														lowerCamelCase_	:							List[str]									=row[-1]
														if not solutions:
																					if row[-2] == 0:
																												solutions.append(0  )
																												continue
																					solutions.append(current_solution / row[-2]  )
																					continue
														lowerCamelCase_	:							Any									=row.copy()[: len(lowerCamelCase__  ) - 1 :]
														while temp_row[0] == 0:
																					temp_row.pop(0  )
														if len(lowerCamelCase__  ) == 0:
																					solutions.append(0  )
																					continue
														lowerCamelCase_	:							int									=temp_row[1::]
														lowerCamelCase_	:							List[Any]									=temp_row[::-1]
														for column_index, column in enumerate(lowerCamelCase__  ):
																					current_solution -= column * solutions[column_index]
														solutions.append(lowerCamelCase__  )
							lowerCamelCase_	:							Tuple									=[]
							for item in solutions:
														final.append(float(round(lowerCamelCase__    ,						5  )  )  )
							return final[::-1]


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						A__	:    Optional[int]			 = [
						    [2, 1, 1, 1, 1, 4],
						    [1, 2, 1, 1, 1, 5],
						    [1, 1, 2, 1, 1, 6],
						    [1, 1, 1, 2, 1, 7],
						    [1, 1, 1, 1, 2, 8],
						]
						print(solve_simultaneous(eq))
						print(solve_simultaneous([[4, 2]]))











"""simple docstring"""



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


A__	:    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__":
						A__	:    str			 = 'hopper-medium-v2'
						A__	:    Dict			 = gym.make(env_name)

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

						env.seed(0)
						A__	:    Dict			 = env.reset()
						A__	:    Optional[int]			 = 0
						A__	:    str			 = 0
						A__	:    List[Any]			 = 1_000
						A__	:    Tuple			 = [obs.copy()]
						try:
												for t in tqdm.tqdm(range(T)):
																		# call the policy
																		A__	:    Union[str, Any]			 = pipeline(obs, planning_horizon=32)

																		# execute action in environment
																		A__ ,						A__ ,						A__ ,						A__	:    Any			 = env.step(denorm_actions)
																		A__	:    List[Any]			 = 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())

																		A__	:    Optional[Any]			 = next_observation
						except KeyboardInterrupt:
												pass

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



