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add serialization functions for EPDTC

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Moreno 2018-03-05 12:14:31 +00:00
parent 592daced9b
commit f4ebae7425
2 changed files with 73 additions and 0 deletions
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34
GPy/testing/serialization_tests.py
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@ -116,11 +116,45 @@ class Test(unittest.TestCase):
np.testing.assert_array_equal(e1._ep_approximation[2].v[:], e1_r._ep_approximation[2].v[:])
np.testing.assert_array_equal(e1._ep_approximation[3][:], e1_r._ep_approximation[3][:])
e1 = GPy.inference.latent_function_inference.expectation_propagation.EPDTC(ep_mode="nested")
e1.ga_approx_old = GPy.inference.latent_function_inference.expectation_propagation.gaussianApproximation(np.random.rand(10),np.random.rand(10))
e1._ep_approximation = []
e1._ep_approximation.append(GPy.inference.latent_function_inference.expectation_propagation.posteriorParamsDTC(np.random.rand(10),np.random.rand(10)))
e1._ep_approximation.append(GPy.inference.latent_function_inference.expectation_propagation.gaussianApproximation(np.random.rand(10),np.random.rand(10)))
e1._ep_approximation.append(GPy.inference.latent_function_inference.expectation_propagation.cavityParams(10))
e1._ep_approximation[-1].v = np.random.rand(10)
e1._ep_approximation[-1].tau = np.random.rand(10)
e1._ep_approximation.append(np.random.rand(10))
e1_r = GPy.inference.latent_function_inference.LatentFunctionInference.from_dict(e1.to_dict())
assert type(e1) == type(e1_r)
assert e1.epsilon==e1_r.epsilon
assert e1.eta==e1_r.eta
assert e1.delta==e1_r.delta
assert e1.always_reset==e1_r.always_reset
assert e1.max_iters==e1_r.max_iters
assert e1.ep_mode==e1_r.ep_mode
assert e1.parallel_updates==e1_r.parallel_updates
np.testing.assert_array_equal(e1.ga_approx_old.tau[:], e1_r.ga_approx_old.tau[:])
np.testing.assert_array_equal(e1.ga_approx_old.v[:], e1_r.ga_approx_old.v[:])
np.testing.assert_array_equal(e1._ep_approximation[0].mu[:], e1_r._ep_approximation[0].mu[:])
np.testing.assert_array_equal(e1._ep_approximation[0].Sigma_diag[:], e1_r._ep_approximation[0].Sigma_diag[:])
np.testing.assert_array_equal(e1._ep_approximation[1].tau[:], e1_r._ep_approximation[1].tau[:])
np.testing.assert_array_equal(e1._ep_approximation[1].v[:], e1_r._ep_approximation[1].v[:])
np.testing.assert_array_equal(e1._ep_approximation[2].tau[:], e1_r._ep_approximation[2].tau[:])
np.testing.assert_array_equal(e1._ep_approximation[2].v[:], e1_r._ep_approximation[2].v[:])
np.testing.assert_array_equal(e1._ep_approximation[3][:], e1_r._ep_approximation[3][:])
e2 = GPy.inference.latent_function_inference.exact_gaussian_inference.ExactGaussianInference()
e2_r = GPy.inference.latent_function_inference.LatentFunctionInference.from_dict(e2.to_dict())
assert type(e2) == type(e2_r)
def test_serialize_deserialize_model(self):
np.random.seed(fixed_seed)
N = 20