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)
