def testTrace(self, cls, value, kwargs):
def tracer(f, *fargs, **fkwargs):
name = fkwargs.get("name", None)
if name == "rv2":
fkwargs["value"] = value
return f(*fargs, **fkwargs)
rv1 = cls(value=value, name="rv1", **kwargs)
with ed.trace(tracer):
rv2 = cls(name="rv2", **kwargs)
rv1_value, rv2_value = self.evaluate([rv1.value, rv2.value])
self.assertEqual(rv1_value, value)
self.assertEqual(rv2_value, value)
def testTraceForwarding(self):
def double(f, *args, **kwargs):
return 2. * ed.traceable(f)(*args, **kwargs)
def set_xy(f, *args, **kwargs):
if kwargs.get("name") == "x":
kwargs["value"] = 1.
if kwargs.get("name") == "y":
kwargs["value"] = 0.42
return ed.traceable(f)(*args, **kwargs)
def model():
x = ed.Normal(loc=0., scale=1., name="x")
y = ed.Normal(loc=x, scale=1., name="y")
return x + y
with ed.trace(set_xy):
with ed.trace(double):
z = model()
value = 2. * 1. + 2. * 0.42
z_value = self.evaluate(z)
self.assertAlmostEqual(z_value, value, places=5)
def testTapeInnerForwarding(self):
def double(f, *args, **kwargs):
return 2. * ed.traceable(f)(*args, **kwargs)
def model():
x = ed.Normal(loc=0., scale=1., name="x")
y = ed.Normal(loc=x, scale=1., name="y")
return x + y
with ed.trace(double):
with ed.tape() as model_tape:
output = model()
expected_value, actual_value = self.evaluate([
model_tape["x"] + model_tape["y"], output])
self.assertEqual(list(six.iterkeys(model_tape)), ["x", "y"])
self.assertEqual(expected_value, actual_value)
def testTraceException(self):
def f():
raise NotImplementedError()
def tracer(f, *fargs, **fkwargs):
return f(*fargs, **fkwargs)
with ed.get_next_tracer() as top_tracer:
old_tracer = top_tracer
with self.assertRaises(NotImplementedError):
with ed.trace(tracer):
f()
with ed.get_next_tracer() as top_tracer:
new_tracer = top_tracer
self.assertEqual(old_tracer, new_tracer)
def transformed_model():
with ed.trace(trivial_tracer):
model()