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Features/test deterministic guide return #1

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merged 2 commits into from
May 17, 2024
Merged

Features/test deterministic guide return #1

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182391d
Increased test coverage on deterministic guide return
Andrei-Treil May 15, 2024
0f8760b
reordered assertions
Andrei-Treil May 15, 2024
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35 changes: 30 additions & 5 deletions tests/infer/test_predictive.py
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Original file line number Diff line number Diff line change
Expand Up @@ -272,8 +272,14 @@ def model(y=None):
@pytest.mark.parametrize("with_plate", [True, False])
@pytest.mark.parametrize("event_shape", [(), (2,)])
@pytest.mark.parametrize("return_deterministic_guide_sites", [True, False])
@pytest.mark.parametrize("return_sites", [[], ["x4"]])
@pytest.mark.parametrize("use_determinisitic_guide", [True, False])
def test_deterministic_guide_return(
with_plate, event_shape, return_deterministic_guide_sites
with_plate,
event_shape,
return_deterministic_guide_sites,
return_sites,
use_determinisitic_guide,
):
def model(y=None):
with pyro.util.optional(pyro.plate("plate", 3), with_plate):
Expand All @@ -283,11 +289,21 @@ def model(y=None):
pyro.deterministic("x3", x2)
return pyro.sample("obs", dist.Normal(x2, 0.1).to_event(), obs=y)

def guide(y=None):
def determinisitic_guide(y=None):
with pyro.util.optional(pyro.plate("plate", 3), with_plate):
x = pyro.sample("x", dist.Normal(0, 1).expand(event_shape).to_event())
x = pyro.sample("x", dist.Normal(0, 2).expand(event_shape).to_event())
x4 = pyro.deterministic("x4", x**2, event_dim=len(event_shape))

pyro.deterministic("x5", x4)

def non_determinisitic_guide(y=None):
with pyro.util.optional(pyro.plate("plate", 3), with_plate):
pyro.sample("x", dist.Normal(0, 2).expand(event_shape).to_event())

pyro.deterministic("x4", x)
if use_determinisitic_guide:
guide = determinisitic_guide
else:
guide = non_determinisitic_guide

y = torch.tensor(4.0)
svi = SVI(model, guide, optim.Adam(dict(lr=0.1)), Trace_ELBO())
Expand All @@ -298,13 +314,22 @@ def guide(y=None):
model,
guide=guide,
num_samples=1000,
return_sites=return_sites,
return_deterministic_guide_sites=return_deterministic_guide_sites,
)()

if return_deterministic_guide_sites:
if return_deterministic_guide_sites and use_determinisitic_guide:
assert "x4" in actual
assert_close(actual["x4"].mean(), y, rtol=0.1)
# When return_sites is empty, include all deterministic guide sites
if len(return_sites) == 0:
assert "x5" in actual
assert_close(actual["x5"].mean(), y, rtol=0.1)
else:
assert "x5" not in actual
else:
assert "x4" not in actual
assert "x5" not in actual


def test_get_mask_optimization():
Expand Down