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use gpflow in workload mapping

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This commit is contained in:
bohanjason
2020-01-22 07:38:18 -05:00
committed by Dana Van Aken
parent 25d1950e67
commit 6f0fcfd952
4 changed files with 72 additions and 78 deletions
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21
server/analysis/gpr/optimize.py
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@@ -16,13 +16,6 @@ from analysis.util import get_analysis_logger
LOG = get_analysis_logger(__name__)
class GPRResult():
def __init__(self, ypreds=None, sigmas=None):
self.ypreds = ypreds
self.sigmas = sigmas
class GPRGDResult():
def __init__(self, ypreds=None, sigmas=None, minl=None, minl_conf=None):
@@ -32,20 +25,6 @@ class GPRGDResult():
self.minl_conf = minl_conf
def gpflow_predict(model, Xin):
fmean, fvar, _, _, _ = model._build_predict(Xin) # pylint: disable=protected-access
y_mean_var = model.likelihood.predict_mean_and_var(fmean, fvar)
y_mean = y_mean_var[0]
y_var = y_mean_var[1]
y_std = tf.sqrt(y_var)
session = model.enquire_session(session=None)
with session.as_default():
y_mean_value = session.run(y_mean)
y_std_value = session.run(y_std)
return GPRResult(y_mean_value, y_std_value)
def tf_optimize(model, Xnew_arr, learning_rate=0.01, maxiter=100, ucb_beta=3.,
active_dims=None, bounds=None, debug=True):
Xnew_arr = check_array(Xnew_arr, copy=False, warn_on_dtype=True, dtype=FLOAT_DTYPES)

34
server/analysis/gpr/predict.py Normal file
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@@ -0,0 +1,34 @@
#
# OtterTune - analysis/optimize.py
#
# Copyright (c) 2017-18, Carnegie Mellon University Database Group
#
# Author: Dana Van Aken
import tensorflow as tf
from sklearn.utils import assert_all_finite, check_array
from sklearn.utils.validation import FLOAT_DTYPES
class GPRResult():
def __init__(self, ypreds=None, sigmas=None):
self.ypreds = ypreds
self.sigmas = sigmas
def gpflow_predict(model, Xin):
Xin = check_array(Xin, copy=False, warn_on_dtype=True, dtype=FLOAT_DTYPES)
fmean, fvar, _, _, _ = model._build_predict(Xin) # pylint: disable=protected-access
y_mean_var = model.likelihood.predict_mean_and_var(fmean, fvar)
y_mean = y_mean_var[0]
y_var = y_mean_var[1]
y_std = tf.sqrt(y_var)
session = model.enquire_session(session=None)
with session.as_default():
y_mean_value = session.run(y_mean)
y_std_value = session.run(y_std)
assert_all_finite(y_mean_value)
assert_all_finite(y_std_value)
return GPRResult(y_mean_value, y_std_value)