def test_prior_KL(self):
with self.test_context():
meanA = self.posteriorMean
varA = self.posteriorVariance
meanB = self.meanZero # Assumes a zero
varB = self.K
referenceKL = univariate_prior_KL(meanA, meanB, varA, varB)
for is_diagonal in [True, False]:
for is_whitened in [True, False]:
m = self.get_model(is_diagonal, is_whitened)
test_prior_KL = gpflow.autoflow()(m.build_prior_KL.__func__)(m)
assert_allclose(referenceKL - test_prior_KL, 0, atol=4)
def test_prior_KL(self):
with self.test_context():
meanA = self.posteriorMean
varA = self.posteriorVariance
meanB = self.meanZero # Assumes a zero
varB = self.K
referenceKL = univariate_prior_KL(meanA, meanB, varA, varB)
for is_diagonal in [True, False]:
for is_whitened in [True, False]:
m = self.get_model(is_diagonal, is_whitened)
test_prior_KL = gpflow.autoflow()(m.build_prior_KL.__func__)(m)
assert_allclose(referenceKL - test_prior_KL, 0, atol=4)
def test_prior_KL_fullQ(self):
with self.test_context():
covQ = np.dot(self.q_sqrt_full, self.q_sqrt_full.T)
mean_prior = np.zeros((self.nDimensions, 1))
for is_whitened in [True, False]:
m = self.get_model(False, is_whitened)
if is_whitened:
cov_prior = np.eye(self.nDimensions)
else:
cov_prior = referenceRbfKernel(
self.X, self.lengthScale, self.signalVariance)
referenceKL = multivariate_prior_KL(
self.q_mean, covQ, mean_prior, cov_prior)
# now get test KL.
test_prior_KL = gpflow.autoflow()(m.build_prior_KL.__func__)(m)
assert_allclose(referenceKL - test_prior_KL, 0, atol=4)
def test_prior_KL_fullQ(self):
with self.test_context():
covQ = np.dot(self.q_sqrt_full, self.q_sqrt_full.T)
mean_prior = np.zeros((self.nDimensions, 1))
for is_whitened in [True, False]:
m = self.get_model(False, is_whitened)
if is_whitened:
cov_prior = np.eye(self.nDimensions)
else:
cov_prior = referenceRbfKernel(
self.X, self.lengthScale, self.signalVariance)
referenceKL = multivariate_prior_KL(
self.q_mean, covQ, mean_prior, cov_prior)
# now get test KL.
test_prior_KL = gpflow.autoflow()(m.build_prior_KL.__func__)(m)
assert_allclose(referenceKL - test_prior_KL, 0, atol=4)