def suggest_multiple_from_name(dbname, host, port, bandit_algo_names, bandit_names,
exp_keys, N, bandit_args_list, bandit_kwargs_list,
bandit_algo_args_list, bandit_algo_kwargs_list,
mql=1, refresh=False):
port = int(port)
trials = MongoTrials('mongo://%s:%d/%s/jobs' % (host, port, dbname),
refresh=False)
algos = []
for bn, ban, ba, bk, baa, bak, ek in zip(bandit_names, bandit_algo_names,
bandit_args_list, bandit_kwargs_list, bandit_algo_args_list, bandit_algo_kwargs_list,
exp_keys):
bandit = json_call(bn, ba, bk)
subtrials = MongoTrials('mongo://%s:%d/%s/jobs' % (host, port, dbname),
refresh=False, exp_key=ek)
if ba or bk:
subtrials.attachments['bandit_data_' + ek] = cPickle.dumps((bn, ba, bk))
bak['cmd'] = ('driver_attachment', 'bandit_data_' + ek)
else:
bak['cmd'] = ('bandit_json evaluate', bn)
algo = json_call(ban, (bandit,) + baa, bak)
algos.append(algo)
algo = InterleaveAlgo(algos, exp_keys)
exp = hyperopt.Experiment(trials, algo, poll_interval_secs=.1)
exp.max_queue_len = mql
if N is not None:
exp.run(N, block_until_done=True)
else:
return exp
def test_mongo_exp_is_picklable():
algo_jsons = []
algo_jsons.append('hyperopt.bandit_algos.Random')
algo_jsons.append('hyperopt.theano_gp.HGP')
algo_jsons.append('hyperopt.theano_gm.AdaptiveParzenGM')
for algo_json in algo_jsons:
with TempMongo() as tm:
# this triggers if an old stale mongo is running
assert len(TempMongo.mongo_jobs('foodb')) == 0
print 'pickling MongoExperiment with', algo_json
bandit = json_call('hyperopt.bandits.GaussWave2')
bandit_algo = json_call(algo_json, args=(bandit,))
exp = MongoExperiment(
bandit_algo=bandit_algo,
mongo_handle=tm.mongo_jobs('foodb'),
workdir=tm.workdir,
exp_key='exp_key',
poll_interval_secs=1.0,
cmd=('asdf', None))
exp_str = cPickle.dumps(exp)
cpy = cPickle.loads(exp_str)
def test_mongo_exp_with_threads():
def worker(host_id, n_jobs, timeout):
mw = MongoWorker(
mj=TempMongo.mongo_jobs('foodb'),
)
t0 = time.time()
while n_jobs:
mw.run_one(host_id, timeout)
print 'worker: ran job'
n_jobs -= 1
for bandit_json in ('hyperopt.bandits.GaussWave2',
'hyperopt.dbn.Dummy_DBN_Base',):
with TempMongo() as tm:
assert len(TempMongo.mongo_jobs('foodb')) == 0
bandit = json_call(bandit_json)
exp = MongoExperiment(
bandit_algo=HGP(bandit),
mongo_handle=tm.mongo_jobs('foodb'),
workdir=tm.workdir,
exp_key='exp_key',
poll_interval_secs=1.0,
cmd=('bandit_json evaluate', bandit_json))
exp.ddoc_init()
assert len(TempMongo.mongo_jobs('foodb')) == 0
for asdf in exp.mongo_handle:
print asdf
assert len(exp.mongo_handle) == 0
n_trials = 5
exp.bandit_algo.n_startup_jobs = 3
wthread = threading.Thread(target=worker,
args=(('hostname', 0), n_trials, 660.0))
wthread.start()
try:
print 'running experiment'
exp.run(n_trials, block_until_done=True)
finally:
print 'joining worker thread...'
wthread.join()
print exp.trials
print exp.results
assert len(exp.trials) == n_trials
assert len(exp.results) == n_trials
exp_str = cPickle.dumps(exp)