public
/
ottertune
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

delete unused algorithm 3

This commit is contained in:
Dongsheng Yang 2019-09-26 21:50:04 -04:00 committed by Dana Van Aken
parent a3fcf59f07
commit 5ad0e8c44e
3 changed files with 7 additions and 22 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
server/website/website/migrations/0006_added_algorithm_selection.py
View File

@ -16,7 +16,9 @@ class Migration(migrations.Migration):
migrations.AddField(
model_name='session',
name='algorithm',
field=models.IntegerField(choices=[(1, 'Ottertune Default'), (2, 'Algorithm 1'), (3, 'Algorithm 2'), (4, 'Algorithm 3')], default=1),
field=models.IntegerField(choices=[(1, 'Ottertune Default'),
(2, 'Deep Deterministic Policy Gradients'),
(3, 'Deep Neural Network')], default=1),
),
migrations.AlterField(
model_name='pipelinedata',

10
server/website/website/types.py
View File

@ -174,13 +174,11 @@ class LabelStyleType(BaseType):
class AlgorithmType(BaseType):
OTTERTUNE = 1
ALGORITHM1 = 2
ALGORITHM2 = 3
ALGORITHM3 = 4
DDPG = 2
DNN = 3
TYPE_NAMES = {
OTTERTUNE: 'Ottertune Default',
ALGORITHM1: 'Algorithm 1',
ALGORITHM2: 'Algorithm 2',
ALGORITHM3: 'Algorithm 3'
DDPG: 'Deep Deterministic Policy Gradients',
DNN: 'Deep Neural Network',
}

15
server/website/website/utils.py
View File

@ -110,21 +110,6 @@ class DataUtil(object):
maxvals.append(maxval)
return np.array(minvals), np.array(maxvals)
@staticmethod
def denormalize_knob_data(knob_values, knob_labels, session):
for i, knob in enumerate(knob_labels):
knob_object = KnobCatalog.objects.get(dbms=session.dbms, name=knob, tunable=True)
knob_session_object = SessionKnob.objects.filter(knob=knob_object, session=session,
tunable=True)
if knob_session_object.exists():
minval = float(knob_session_object[0].minval)
maxval = float(knob_session_object[0].maxval)
else:
minval = float(knob_object.minval)
maxval = float(knob_object.maxval)
knob_values[i] = knob_values[i] * (maxval - minval) + minval
return knob_values
@staticmethod
def aggregate_data(results):
knob_labels = list(JSONUtil.loads(results[0].knob_data.data).keys())