def test_load_data2(self):
surrogate = 'data2'
l = lookup.load(surrogate)
lrs = l.get_accuracies_per_epoch()
self.assertEqual(20000, len(lrs))
lr = lrs.ix[0].tolist()
self.assertEqual(15, len(lr))
def add(self, args):
job_id = None
# TODO: validate parameters
try:
dataset = args['dataset'] # e.g. MNIST, CIFAR-10,
model = args['model'] # LeNet, VGG, LSTM, ...
hpv = args['hyperparams'] # refer to data*.json for keys
cfg = args['config'] # max_iter, ...
f = TrainingJobFactory(self.worker, self.jobs)
job = f.create(dataset, model, hpv, cfg)
job_id = job['job_id']
self.jobs.append(job)
debug("Job appended properly.")
worker = None
if self.use_surrogate and "surrogate" in cfg:
s = cfg['surrogate']
l = lookup.load(s)
ffr = None
if "ffr" in cfg:
ffr = cfg['ffr']
worker = SurrogateEvaluator(s, l, time_slip_rate=ffr)
else:
worker = self.worker
max_epoch = None
if "max_epoch" in cfg:
max_epoch = cfg['max_epoch']
worker.set_max_iters(max_epoch, "epoch")
elif "max_iter" in cfg:
max_iter = cfg['max_iter']
iter_unit = "epoch"
if "iter_unit" in cfg:
iter_unit = cfg['iter_unit']
worker.set_max_iters(max_iter, iter_unit)
cand_index = None
if 'cand_index' in cfg:
cand_index = cfg['cand_index']
if worker.set_job_description(hpv, cand_index, job_id):
job['status'] = 'assigned'
self.work_item = {
"worker": worker,
"job_id": job_id,
"cand_index": cand_index,
"hyperparams": hpv
}
debug("Work item created properly.")
else:
debug("Invalid hyperparam vector: {}".format(hpv))
raise ValueError("Invalid hyperparameters")
except Exception as ex:
#debug("invalid arguments: {}, {}, {}, {}".format(dataset, model, hpv, cfg))
warn("Adding job {} failed: {}".format(job, ex))
raise ValueError("Invalid job description")
finally:
return job_id
def create_surrogate_space(surrogate, grid_order=None, one_hot=False):
l = lookup.load(surrogate, grid_order=grid_order)
s = SurrogatesSpace(l, one_hot=one_hot)
debug("Surrogate model created: {}".format(surrogate))
return s
def __init__(self, surrogate, **kwargs):
self.name = "LR_{}".format(surrogate)
l = lookup.load(surrogate)
if l == None:
raise TypeError("Fail to load surrogate")
self.lrs = l.get_accuracies_per_epoch()
def create_space_from_table(surrogate_name, grid_order=None):
l = lookup.load(surrogate_name, grid_order=grid_order)
s = SurrogatesSpace(l)
debug("Surrogate model created: {}".format(surrogate_name))
return s