test_sample_partial test failure #609
Description
Hello,
I've seen this in GNU Guix CI:
=================================== FAILURES ===================================
___________________________ test_sample_partial[()] ____________________________
int_inputs = OrderedDict()
@pytest.mark.parametrize(
"int_inputs",
[
OrderedDict(),
OrderedDict([("i", Bint[2])]),
OrderedDict([("i", Bint[2]), ("j", Bint[3])]),
],
ids=id_from_inputs,
)
def test_sample_partial(int_inputs):
int_inputs = OrderedDict(sorted(int_inputs.items()))
real_inputs = OrderedDict(
[("w", Reals[2]), ("x", Reals[4]), ("y", Reals[2, 3]), ("z", Real)]
)
inputs = int_inputs.copy()
inputs.update(real_inputs)
flat = ops.cat(
[Variable(k, d).reshape((d.num_elements,)) for k, d in real_inputs.items()]
)
def compute_moments(samples):
flat_samples = flat(**extract_samples(samples))
assert set(flat_samples.inputs) == {"particle"} | set(int_inputs)
mean = flat_samples.reduce(ops.mean)
diff = flat_samples - mean
cov = (diff[:, None] - diff[None, :]).reduce(ops.mean)
return mean, cov
sample_inputs = OrderedDict(particle=Bint[50000])
rng_keys = [None] * 3
if get_backend() == "jax":
import jax.random
rng_keys = jax.random.split(np.array([0, 0], dtype=np.uint32), 3)
g = random_gaussian(inputs)
all_vars = frozenset("wxyz")
samples = g.sample(all_vars, sample_inputs, rng_keys[0])
expected_mean, expected_cov = compute_moments(samples)
subsets = "w x y z wx wy wz xy xz yz wxy wxz wyz xyz".split()
for sampled_vars in map(frozenset, subsets):
g2 = g.sample(sampled_vars, sample_inputs, rng_keys[1])
samples = g2.sample(all_vars, sample_inputs, rng_keys[2])
actual_mean, actual_cov = compute_moments(samples)
> assert_close(actual_mean, expected_mean, atol=1e-1, rtol=1e-1)
test/test_gaussian.py:843:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/gnu/store/zmr2dvs06mazgfnrxh2b9f5lvxxs1ylz-python-funsor-0.4.5/lib/python3.10/site-packages/funsor/testing.py:136: in assert_close
assert_close(actual.data, expected.data, atol=atol, rtol=rtol)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
actual = array([-1.00111884, -0.68092102, 0.69566841, -0.46268585, -1.07358358,
-0.24324944, -1.22855264, 0.21857192, -0.04263261, 1.09376803,
0.77507805, -0.01998961, -1.81863148])
expected = array([-0.99112969, -0.68268335, 0.69722302, -0.45905905, -1.08039513,
-0.24329676, -1.23492357, 0.2196864 , -0.04553655, 1.09680053,
0.77216647, -0.035942 , -1.81212992])
atol = 0.1, rtol = 0.1
def assert_close(actual, expected, atol=1e-6, rtol=1e-6):
msg = ActualExpected(actual, expected)
if is_array(actual):
assert is_array(expected), msg
elif isinstance(actual, Tensor) and is_array(actual.data):
assert isinstance(expected, Tensor) and is_array(expected.data), msg
elif (
isinstance(actual, Contraction)
and isinstance(actual.terms[0], Tensor)
and is_array(actual.terms[0].data)
):
assert isinstance(expected, Contraction) and is_array(
expected.terms[0].data
), msg
elif isinstance(actual, Contraction) and isinstance(actual.terms[0], Delta):
assert isinstance(expected, Contraction) and isinstance(
expected.terms[0], Delta
), msg
elif isinstance(actual, Gaussian):
assert isinstance(expected, Gaussian)
else:
assert type(actual) == type(expected), msg
if isinstance(actual, Funsor):
assert isinstance(expected, Funsor), msg
assert actual.inputs == expected.inputs, (actual.inputs, expected.inputs)
assert actual.output == expected.output, (actual.output, expected.output)
if isinstance(actual, (Number, Tensor)):
assert_close(actual.data, expected.data, atol=atol, rtol=rtol)
elif isinstance(actual, Delta):
assert frozenset(n for n, p in actual.terms) == frozenset(
n for n, p in expected.terms
)
actual = actual.align(tuple(n for n, p in expected.terms))
for (actual_name, (actual_point, actual_log_density)), (
expected_name,
(expected_point, expected_log_density),
) in zip(actual.terms, expected.terms):
assert actual_name == expected_name
assert_close(actual_point, expected_point, atol=atol, rtol=rtol)
assert_close(actual_log_density, expected_log_density, atol=atol, rtol=rtol)
elif isinstance(actual, Gaussian):
# Note white_vec and prec_sqrt are expected to agree only up to an
# orthogonal factor, but precision and info_vec should agree exactly.
assert_close(actual._info_vec, expected._info_vec, atol=atol, rtol=rtol)
assert_close(actual._precision, expected._precision, atol=atol, rtol=rtol)
elif isinstance(actual, Contraction):
assert actual.red_op == expected.red_op
assert actual.bin_op == expected.bin_op
assert actual.reduced_vars == expected.reduced_vars
assert len(actual.terms) == len(expected.terms)
for ta, te in zip(actual.terms, expected.terms):
assert_close(ta, te, atol, rtol)
elif type(actual).__name__ == "Tensor":
assert get_backend() == "torch"
import torch
assert actual.dtype == expected.dtype, msg
assert actual.shape == expected.shape, msg
if actual.dtype in (torch.long, torch.uint8, torch.bool):
assert (actual == expected).all(), msg
else:
eq = actual == expected
if eq.all():
return
if eq.any():
actual = actual[~eq]
expected = expected[~eq]
diff = (actual.detach() - expected.detach()).abs()
if rtol is not None:
assert (diff / (atol + expected.detach().abs())).max() < rtol, msg
elif atol is not None:
assert diff.max() < atol, msg
elif is_array(actual):
if get_backend() == "jax":
import jax
assert jax.numpy.result_type(actual.dtype) == jax.numpy.result_type(
expected.dtype
), msg
else:
assert actual.dtype == expected.dtype, msg
assert actual.shape == expected.shape, msg
if actual.dtype in (np.int32, np.int64, np.uint8, bool):
assert (actual == expected).all(), msg
else:
actual, expected = np.asarray(actual), np.asarray(expected)
eq = actual == expected
if eq.all():
return
if eq.any():
actual = actual[~eq]
expected = expected[~eq]
diff = abs(actual - expected)
if rtol is not None:
> assert (diff / (atol + abs(expected))).max() < rtol, msg
E AssertionError: Expected:
E [-0.99112969 -0.68268335 0.69722302 -0.45905905 -1.08039513 -0.24329676
E -1.23492357 0.2196864 -0.04553655 1.09680053 0.77216647 -0.035942
E -1.81212992]
E Actual:
E [-1.00111884 -0.68092102 0.69566841 -0.46268585 -1.07358358 -0.24324944
E -1.22855264 0.21857192 -0.04263261 1.09376803 0.77507805 -0.01998961
E -1.81863148]
/gnu/store/zmr2dvs06mazgfnrxh2b9f5lvxxs1ylz-python-funsor-0.4.5/lib/python3.10/site-packages/funsor/testing.py:204: AssertionError
=========================== short test summary info ============================
FAILED test/test_gaussian.py::test_sample_partial[()] - AssertionError: Expec...
= 1 failed, 7637 passed, 3859 skipped, 69 xfailed, 2 xpassed in 417.82s (0:06:57) =
error: in phase 'check': uncaught exception:
%exception #<&invoke-error program: "/gnu/store/m8li9l31vqfl7f3m4zmdqykc5madv2hr-python-pytest-7.1.3/bin/pytest" arguments: ("-vv") exit-status: 1 term-signal: #f stop-signal: #f>
phase `check' failed after 419.9 seconds
command "/gnu/store/m8li9l31vqfl7f3m4zmdqykc5madv2hr-python-pytest-7.1.3/bin/pytest" "-vv" failed with status 1
builder for `/gnu/store/z2mzsj06by0ffly2b8magk1vn1ics0dc-python-funsor-0.4.5.drv' failed with exit code 1
@ build-failed /gnu/store/z2mzsj06by0ffly2b8magk1vn1ics0dc-python-funsor-0.4.5.drv - 1 builder for `/gnu/store/z2mzsj06by0ffly2b8magk1vn1ics0dc-python-funsor-0.4.5.drv' failed with exit code 1
It seems the tolerances used for the test need to be relaxed.