wangwei created SINGA-413:
-----------------------------
Summary: Hyper-parameter configuration API
Key: SINGA-413
URL: https://issues.apache.org/jira/browse/SINGA-413
Project: Singa
Issue Type: Improvement
Reporter: wangwei
The current API for hyper-parameter configuration in Rafiki requires the model
contributor to implement
{code:java}
def get_knob_config(self):
{
'knobs': {
'hidden_layer_units': {
'type': 'int',
'range': [2, 128]
},
...
}
def init(self, knobs):
self.hidden_layer_units = knobs.get(hidden_layer_units){code}
The json style can be replaced by
{code}
def check(knobs, val):
if knobs[0].value() == 4 and val == 4:
return False
else:
return True
def register_knobs(self):
self.hidden_layer_units = Knob(32, kInt, range=(2, 128))
self.learning_rate = Knob(0.02, kExpFloat, range=(1e-1, 1e-4))
self.batch_size = Knob(8, kIntCat, range = [4, 8, 16]))
self.num_epoch = Knob(4, kIntCat, range = [4, 8, 16],
depends=self.batch_size, callback=check()))
def train(self):
for i in range(self.num_epoch.value()):
...{code}
The worker's workflow is like
{code:java}
for trial in range(total_trials):
model = Model()
model.register_knobs()
knobs = [x for x, y in model.__dict__.getitems() if isinstance(y, Knob)]
if trial == 0:
reigster_knobs_to_advisor(knobs)
get_knobs_from_advisor(knobs){code}
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
