Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Fix join logp for multivariate RVs #7215

Merged
merged 1 commit into from
Apr 8, 2024
Merged

Fix join logp for multivariate RVs #7215

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 4 additions & 2 deletions pymc/logprob/tensor.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -188,10 +188,12 @@ def logprob_join(op, values, axis, *base_rvs, **kwargs):
# If the stacked variables depend on each other, we have to replace them by the respective values
logps = replace_rvs_by_values(logps, rvs_to_values=base_rvs_to_split_values)

base_vars_ndim_supp = split_values[0].ndim - logps[0].ndim
# Make axis positive and adjust for multivariate logp fewer dimensions to the right
axis = pt.switch(axis >= 0, axis, value.ndim + axis)
axis = pt.minimum(axis, logps[0].ndim - 1)
join_logprob = pt.concatenate(
[pt.atleast_1d(logp) for logp in logps],
axis=axis - base_vars_ndim_supp,
axis=axis,
)

return join_logprob
Expand Down
54 changes: 21 additions & 33 deletions tests/logprob/test_tensor.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -269,34 +269,23 @@ def test_measurable_join_univariate(size1, size2, axis, concatenate):


@pytest.mark.parametrize(
"size1, supp_size1, size2, supp_size2, axis, concatenate",
"size1, supp_size1, size2, supp_size2, axis, concatenate, logp_axis",
[
(None, 2, None, 2, 0, True),
(None, 2, None, 2, -1, True),
((5,), 2, (3,), 2, 0, True),
((5,), 2, (3,), 2, -2, True),
((2,), 5, (2,), 3, 1, True),
pytest.param(
(2,),
5,
(2,),
5,
0,
False,
marks=pytest.mark.xfail(reason="cannot measure dimshuffled multivariate RVs"),
),
pytest.param(
(2,),
5,
(2,),
5,
1,
False,
marks=pytest.mark.xfail(reason="cannot measure dimshuffled multivariate RVs"),
),
(None, 2, None, 2, 0, True, 0),
(None, 2, None, 2, -1, True, 0),
((5,), 2, (3,), 2, 0, True, 0),
((5,), 2, (3,), 2, -2, True, 0),
((2,), 5, (2,), 3, 1, True, 0),
((5, 6), 10, (5, 1), 10, 1, True, 1),
((5, 6), 10, (5, 1), 10, -2, True, 1),
((2,), 5, (2,), 5, 0, False, 0),
((2,), 5, (2,), 5, 1, False, 1),
((5, 6), 10, (5, 6), 10, 2, False, 2),
Comment on lines +281 to +283
Copy link
Member Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

These graphs were actually supported for a while now, but the logic to test them was wrong so the tests still xfailed

],
)
def test_measurable_join_multivariate(size1, supp_size1, size2, supp_size2, axis, concatenate):
def test_measurable_join_multivariate(
size1, supp_size1, size2, supp_size2, axis, concatenate, logp_axis
):
base1_rv = pt.random.multivariate_normal(
np.zeros(supp_size1), np.eye(supp_size1), size=size1, name="base1"
)
Expand All @@ -310,19 +299,18 @@ def test_measurable_join_multivariate(size1, supp_size1, size2, supp_size2, axis
base1_vv = base1_rv.clone()
base2_vv = base2_rv.clone()
y_vv = y_rv.clone()

y_logp = logp(y_rv, y_vv)
assert_no_rvs(y_logp)

base_logps = [
pt.atleast_1d(logp)
for logp in conditional_logp({base1_rv: base1_vv, base2_rv: base2_vv}).values()
]

if concatenate:
axis_norm = np.core.numeric.normalize_axis_index(axis, base1_rv.ndim)
base_logps = pt.concatenate(base_logps, axis=axis_norm - 1)
expected_logp = pt.concatenate(base_logps, axis=logp_axis)
else:
axis_norm = np.core.numeric.normalize_axis_index(axis, base1_rv.ndim + 1)
base_logps = pt.stack(base_logps, axis=axis_norm - 1)
y_logp = y_logp = logp(y_rv, y_vv)
assert_no_rvs(y_logp)
expected_logp = pt.stack(base_logps, axis=logp_axis)

base1_testval = base1_rv.eval()
base2_testval = base2_rv.eval()
Expand All @@ -331,7 +319,7 @@ def test_measurable_join_multivariate(size1, supp_size1, size2, supp_size2, axis
else:
y_testval = np.stack((base1_testval, base2_testval), axis=axis)
np.testing.assert_allclose(
base_logps.eval({base1_vv: base1_testval, base2_vv: base2_testval}),
expected_logp.eval({base1_vv: base1_testval, base2_vv: base2_testval}),
y_logp.eval({y_vv: y_testval}),
)

Expand Down
Loading