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https://issues.apache.org/jira/browse/SINGA-413?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16706150#comment-16706150
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Ngin Yun Chuan edited comment on SINGA-413 at 12/2/18 9:26 AM:
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Hi [~wangwei.cs], I've pushed the API changes to the [`improve_knob_api`
branch|https://github.com/nginyc/rafiki/compare/improve_knob_api]. Do you have
any feedback on the revised model knob configuration API before I finish it up?
The worker-side implementation for this improvement is not complete yet -
wanted to get your feedback first.
was (Author: nginyc):
Hi [~wangwei.cs], I've pushed the API changes to the [`improve_knob_api`
branch|https://github.com/nginyc/rafiki/compare/improve_knob_api]. Do you have
any feedback on the revised model knob configuration API before continuing? The
worker-side implementation for this improvement is not complete yet - wanted to
get your feedback first.
> Hyper-parameter configuration API
> ---------------------------------
>
> Key: SINGA-413
> URL: https://issues.apache.org/jira/browse/SINGA-413
> Project: Singa
> Issue Type: Improvement
> Reporter: wangwei
> Priority: Major
>
> 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}
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