def test_independent_reparametrization_sampler_sample_is_repeatable() -> None:
sampler = IndependentReparametrizationSampler(100, _dim_two_gp())
xs = tf.random.uniform([100, 1, 2],
minval=-10.0,
maxval=10.0,
dtype=tf.float64)
npt.assert_allclose(sampler.sample(xs), sampler.sample(xs))
def test_independent_reparametrization_sampler_sample_raises_for_invalid_at_shape(
shape: ShapeLike, ) -> None:
sampler = IndependentReparametrizationSampler(1,
QuadraticMeanAndRBFKernel())
with pytest.raises(TF_DEBUGGING_ERROR_TYPES):
sampler.sample(tf.zeros(shape))
def test_independent_reparametrization_sampler_sample_is_continuous() -> None:
sampler = IndependentReparametrizationSampler(100, _dim_two_gp())
xs = tf.random.uniform([100, 1, 2],
minval=-10.0,
maxval=10.0,
dtype=tf.float64)
npt.assert_array_less(
tf.abs(sampler.sample(xs + 1e-20) - sampler.sample(xs)), 1e-20)
def test_independent_reparametrization_sampler_samples_approximate_expected_distribution() -> None:
sample_size = 1000
x = tf.random.uniform([100, 1, 2], minval=-10.0, maxval=10.0, dtype=tf.float64)
model = _dim_two_gp()
samples = IndependentReparametrizationSampler(sample_size, model).sample(x) # [N, S, 1, L]
assert samples.shape == [len(x), sample_size, 1, 2]
mean, var = model.predict(tf.squeeze(x, -2)) # [N, L], [N, L]
_assert_kolmogorov_smirnov_95(
tf.linalg.matrix_transpose(tf.squeeze(samples, -2)),
tfp.distributions.Normal(mean[..., None], tf.sqrt(var[..., None])),
)
def test_independent_reparametrization_sampler_samples_are_distinct_for_new_instances(
) -> None:
sampler1 = IndependentReparametrizationSampler(100, _dim_two_gp())
sampler2 = IndependentReparametrizationSampler(100, _dim_two_gp())
xs = tf.random.uniform([100, 1, 2],
minval=-10.0,
maxval=10.0,
dtype=tf.float64)
npt.assert_array_less(1e-9,
tf.abs(sampler2.sample(xs) - sampler1.sample(xs)))
def test_independent_reparametrization_sampler_raises_for_invalid_sample_size(
sample_size: int, ) -> None:
with pytest.raises(TF_DEBUGGING_ERROR_TYPES):
IndependentReparametrizationSampler(sample_size,
QuadraticMeanAndRBFKernel())