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Dec 7, 2020
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uncomment test from #4297 #4302

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8076a26
uncomment test
MarcoGorelli Dec 5, 2020
c7b552a
:art:
MarcoGorelli Dec 5, 2020
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12 changes: 7 additions & 5 deletions pymc3/distributions/distribution.py
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Original file line number Diff line number Diff line change
Expand Up @@ -54,6 +54,8 @@
"vectorized_ppc", default=None
) # type: contextvars.ContextVar[Optional[Callable]]

PLATFORM = sys.platform


class _Unpickling:
pass
Expand Down Expand Up @@ -510,17 +512,17 @@ def __init__(
super().__init__(shape, dtype, testval, *args, **kwargs)
self.logp = logp
if type(self.logp) == types.MethodType:
if sys.platform != "linux":
if PLATFORM != "linux":
warnings.warn(
"You are passing a bound method as logp for DensityDist, this can lead to "
+ "errors when sampling on platforms other than Linux. Consider using a "
+ "plain function instead, or subclass Distribution."
"errors when sampling on platforms other than Linux. Consider using a "
"plain function instead, or subclass Distribution."
)
elif type(multiprocessing.get_context()) != multiprocessing.context.ForkContext:
warnings.warn(
"You are passing a bound method as logp for DensityDist, this can lead to "
+ "errors when sampling when multiprocessing cannot rely on forking. Consider using a "
+ "plain function instead, or subclass Distribution."
"errors when sampling when multiprocessing cannot rely on forking. Consider using a "
"plain function instead, or subclass Distribution."
)
self.rand = random
self.wrap_random_with_dist_shape = wrap_random_with_dist_shape
Expand Down
24 changes: 11 additions & 13 deletions pymc3/tests/test_parallel_sampling.py
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Expand Up @@ -172,24 +172,23 @@ def func(x):
trace = pm.sample(draws=10, tune=10, step=pm.Metropolis(), cores=2, mp_ctx="spawn")


@pytest.mark.xfail(raises=ValueError)
def test_spawn_densitydist_bound_method():
with pm.Model() as model:
mu = pm.Normal("mu", 0, 1)
normal_dist = pm.Normal.dist(mu, 1)
obs = pm.DensityDist("density_dist", normal_dist.logp, observed=np.random.randn(100))
trace = pm.sample(draws=10, tune=10, step=pm.Metropolis(), cores=2, mp_ctx="spawn")
msg = "logp for DensityDist is a bound method, leading to RecursionError while serializing"
with pytest.raises(ValueError, match=msg):
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I considered pytest.raises, but the code in DensityDist is not guaranteed to raise the error. It will try to serialize as normal, and only if a RecursionError occurs (at the moment, expected to happen), it's wrapped and re-raised. It's possible that a later fix in dill or so will prevent the error from happening altogether. So I decided on xfail instead.

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ah, I see - thanks for explaining!

It's possible that a later fix in dill or so will prevent the error from happening altogether

If that happens, maybe it's good that this test fails (i.e. doesn't raise a ValueError) because then we will get a loud and clear notice that the error no longer happens and then we can set a minimum dill version?

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Yep, sounds good to me :)

trace = pm.sample(draws=10, tune=10, step=pm.Metropolis(), cores=2, mp_ctx="spawn")


# cannot test this properly: monkeypatching sys.platform messes up Theano
# def test_spawn_densitydist_syswarning(monkeypatch):
# monkeypatch.setattr(sys, "platform", "win32")
# with pm.Model() as model:
# mu = pm.Normal('mu', 0, 1)
# normal_dist = pm.Normal.dist(mu, 1)
# with pytest.warns(UserWarning) as w:
# obs = pm.DensityDist('density_dist', normal_dist.logp, observed=np.random.randn(100))
# assert len(w) == 1 and "errors when sampling on platforms" in w[0].message.args[0]
def test_spawn_densitydist_syswarning(monkeypatch):
monkeypatch.setattr("pymc3.distributions.distribution.PLATFORM", "win32")
with pm.Model() as model:
mu = pm.Normal("mu", 0, 1)
normal_dist = pm.Normal.dist(mu, 1)
with pytest.warns(UserWarning, match="errors when sampling on platforms"):
obs = pm.DensityDist("density_dist", normal_dist.logp, observed=np.random.randn(100))


def test_spawn_densitydist_mpctxwarning(monkeypatch):
Expand All @@ -198,6 +197,5 @@ def test_spawn_densitydist_mpctxwarning(monkeypatch):
with pm.Model() as model:
mu = pm.Normal("mu", 0, 1)
normal_dist = pm.Normal.dist(mu, 1)
with pytest.warns(UserWarning) as w:
with pytest.warns(UserWarning, match="errors when sampling when multiprocessing"):
obs = pm.DensityDist("density_dist", normal_dist.logp, observed=np.random.randn(100))
assert len(w) == 1 and "errors when sampling when multiprocessing" in w[0].message.args[0]