import nest_asyncio nest_asyncio.apply() import asyncio from teeport import Teeport from opt.algorithms.pso import optimize teeport = Teeport('ws://lambda-sp3:8090/') teeport.run_optimizer(optimize, 'PSO', name='PSO', configs={ 'D': 8, 'N0': 30, 'method': 'lhs', 'Ng': 20 }) print('optimizer is running...') loop = asyncio.get_event_loop() loop.run_until_complete(teeport.optimizer.task)
import numpy as np import nest_asyncio nest_asyncio.apply() import asyncio from functools import partial from teeport import Teeport from opt.processors.gps_predictor import process params = dict(theta=np.array([[0.4]]), var='auto', sigma_n=np.array([[1e-4]]), C=1e9) teeport = Teeport('ws://lambda-sp3:8090/') teeport.run_processor(partial(process, params=params), 'GPS Predictor: no opt') print('processor is running...') loop = asyncio.get_event_loop() loop.run_until_complete(teeport.processors[0].task)
import nest_asyncio nest_asyncio.apply() import asyncio from teeport import Teeport from opt.evaluators.uf import evaluate teeport = Teeport('ws://lambda-sp3:8090/') teeport.run_evaluator(evaluate, 'UF2', name='UF2', configs={ 'prob_id': 2, 'D': 30, 'wall_time': 1 }) print('evaluator is running...') loop = asyncio.get_event_loop() loop.run_until_complete(teeport.evaluator.task)
import nest_asyncio nest_asyncio.apply() import asyncio from teeport import Teeport from opt.evaluators.rosenbrock import evaluate teeport = Teeport('ws://lambda-sp3:8090/') teeport.run_evaluator(evaluate, 'Rosenbrock', name='Rosenbrock Noise 0.001', configs={ 'vrange': [-2, 2], 'wall_time': 1, 'noise_level': 1e-3, 'ret_origin': True }) print('evaluator is running...') loop = asyncio.get_event_loop() loop.run_until_complete(teeport.evaluator.task)
import nest_asyncio nest_asyncio.apply() import asyncio from teeport import Teeport from opt.evaluators.lossrate_sim import evaluator_generator teeport = Teeport('ws://lambda-sp3:8090/') evaluate = evaluator_generator('/home/jupyter-zhezhang/loss_rate_model.json', (-20, 20), 0, 0.5) teeport.run_evaluator(evaluate, 'Lossrate NN') print('evaluator is running...') loop = asyncio.get_event_loop() loop.run_until_complete(teeport.evaluator.task)
import nest_asyncio nest_asyncio.apply() import asyncio from teeport import Teeport from opt.algorithms.ego import optimize teeport = Teeport('ws://lambda-sp3:8090/') teeport.run_optimizer( optimize, 'EGO', name='EGO', configs={ # initialization 'D': 13, 'N0': 30, 'method': 'lhs', 'vrange': [0, 1], 'add_center': False, # hyper-parameters 'criterion': 'UCB', # termination 'T': 300 }) print('optimizer is running...') loop = asyncio.get_event_loop() loop.run_until_complete(teeport.optimizer.task)
import nest_asyncio nest_asyncio.apply() import asyncio from teeport import Teeport from opt.processors.gpy_predictor import process teeport = Teeport('ws://lambda-sp3:8090/') teeport.run_processor(process, 'GPy-Pred', name='GPy Predictor', configs={ 'theta': None, 'var': None, 'sigma_n': None, 'ret_grad': False }) print('processor is running...') loop = asyncio.get_event_loop() loop.run_until_complete(teeport.processors[0].task)
import nest_asyncio nest_asyncio.apply() import asyncio from teeport import Teeport from opt.evaluators.prob_pymoo import evaluate teeport = Teeport('ws://lambda-sp3:8090/') teeport.run_evaluator(evaluate, 'pymoo', name='pymoo Test Suite', configs={ 'prob_id': 'zdt1', 'vrange': [0, 1], 'wall_time': 1 }) print('evaluator is running...') loop = asyncio.get_event_loop() loop.run_until_complete(teeport.evaluator.task)
import numpy as np import nest_asyncio nest_asyncio.apply() import asyncio from functools import partial from teeport import Teeport from opt.processors.gpy_predictor import process teeport = Teeport('ws://lambda-sp3:8090/') teeport.run_processor(partial(process, configs={}), 'GPy Predictor') print('processor is running...') loop = asyncio.get_event_loop() loop.run_until_complete(teeport.processors[0].task)
import numpy as np import nest_asyncio nest_asyncio.apply() import asyncio from functools import partial from teeport import Teeport from opt.processors.gpy_predictor import process teeport = Teeport('ws://lambda-sp3:8090/') teeport.run_processor(partial(process, configs={'ret_grad': True}), 'GPy Predictor with Grad') print('processor is running...') loop = asyncio.get_event_loop() loop.run_until_complete(teeport.processors[0].task)
import nest_asyncio nest_asyncio.apply() import asyncio from teeport import Teeport from opt.algorithms.nsgaii import optimize teeport = Teeport('ws://lambda-sp3:8090/') teeport.run_optimizer(optimize, 'NSGA-II', name='NSGA-II', configs={ 'D': 8, 'N0': 80, 'seed': None, 'Ng': 30 }) print('optimizer is running...') loop = asyncio.get_event_loop() loop.run_until_complete(teeport.optimizer.task)
import nest_asyncio nest_asyncio.apply() import asyncio from teeport import Teeport from opt.evaluators.zdt1 import evaluate teeport = Teeport('ws://lambda-sp3:8090/') teeport.run_evaluator(evaluate, 'ZDT1', name='ZDT1', configs={ 'vrange': [0, 1], 'wall_time': 1 }) print('evaluator is running...') loop = asyncio.get_event_loop() loop.run_until_complete(teeport.evaluator.task)