def test_dump_and_load_before_fitting(tmpdir):
model1 = pf.LinearRegression(7)
fname = str(tmpdir.join("test_model.pkl"))
model1.save(fname)
model2 = pf.load(fname)
assert isinstance(model2, pf.LinearRegression)
assert model1 is not model2
post1 = model1.posterior_mean()
post2 = model2.posterior_mean()
for k in post1:
assert isclose(post1[k], post2[k])
def test_dump_and_load_after_fitting(tmpdir):
model1 = pf.LinearRegression(7)
x, y = get_test_data(1024, 7)
model1.fit(x, y, epochs=2)
fname = str(tmpdir.join("test_model.pkl"))
model1.save(fname)
model2 = pf.load(fname)
assert isinstance(model2, pf.LinearRegression)
assert model1 is not model2
post1 = model1.posterior_mean()
post2 = model2.posterior_mean()
for k in post1:
assert isclose(post1[k], post2[k])
def load_model(self, filename):
self.model = pf.load(filename)
return self.model