class ParameterTest(unittest.TestCase):
@classmethod
def setUpClass(cls):
pass
@classmethod
def tearDownClass(cls):
pass
def setUp(self):
self.dev = D.Naive()
Device.set_default(self.dev)
self.p = Parameter([8], I.Constant(0))
self.p.value.reset_by_vector([1, 2, 3, 4, 5, 6, 7, 8])
def tearDown(self):
pass
def test_parameter_stats(self):
self.p.add_stats("stat1", Shape([2, 3]))
self.p.add_stats("stat2", Shape([2, 4]))
st1 = self.p.stats["stat1"]
st1.reset(0)
self.assertTrue((st1.to_ndarrays()[0] == np.zeros([2, 3])).all())
self.p.stats["stat1"] = tF.input(np.ones([2, 3]))
self.assertTrue((st1.to_ndarrays()[0] == np.ones([2, 3])).all())
self.assertIn("stat1", self.p.stats)
self.assertIn("stat2", self.p.stats)
self.assertNotIn("stat3", self.p.stats)
with self.assertRaises(NotImplementedError):
del self.p.stats["stat1"]
with self.assertRaises(AttributeError):
self.p.stats = ParameterStatistics(self.p)
def test_parameter_value(self):
self.assertTrue(
(self.p.value.to_ndarrays() == np.array([1, 2, 3, 4, 5, 6, 7,
8])).all())
val = self.p.value
self.p.value += tF.input(np.ones([8]))
self.assertTrue(
(val.to_ndarrays()[0] == np.array([2, 3, 4, 5, 6, 7, 8, 9])).all())
with self.assertRaises(NotImplementedError):
del self.p.value
def test_parameter_gradient(self):
self.p.reset_gradient()
self.assertTrue((self.p.gradient.to_ndarrays() == np.zeros([8])).all())
grad = self.p.gradient
self.p.gradient += tF.input(np.ones([8]))
self.assertTrue((grad.to_ndarrays()[0] == np.ones([8])).all())
with self.assertRaises(NotImplementedError):
del self.p.gradient
def test_ModelTest_CheckSaveLoadWithStats(self):
shape = Shape([2, 2])
values1 = [1, 2, 3, 4]
values2 = [5, 6, 7, 8]
stats1 = [10, 20, 30, 40]
stats2 = [50, 60, 70, 80]
tmp = tempfile.NamedTemporaryFile()
m1 = Model()
m2 = Model()
p1 = Parameter(shape, I.Constant(0))
p1.value += tF.raw_input(shape, values1)
p2 = Parameter(shape, I.Constant(0))
p2.value += tF.raw_input(shape, values2)
p1.add_stats("a", shape)
p2.add_stats("b", shape)
p1.stats["a"].reset_by_vector(stats1);
p2.stats["b"].reset_by_vector(stats2);
m1.add("p", p1)
m2.add("p", p2)
m1.add("sm", m2)
m1.save(tmp.name)
m1 = Model()
m2 = Model()
p1 = Parameter()
p2 = Parameter()
m1.add("p", p1)
m2.add("p", p2)
m1.add("sm", m2)
m1.load(tmp.name)
self.assertTrue(p1.valid())
self.assertTrue(p2.valid())
self.assertEqual(shape, p1.shape())
self.assertEqual(shape, p2.shape())
self.assertEqual(values1, p1.value.to_list())
self.assertEqual(values2, p2.value.to_list())
self.assertTrue("a" in p1.stats)
self.assertTrue("b" in p2.stats)
self.assertEqual(stats1, p1.stats["a"].to_list())
self.assertEqual(stats2, p2.stats["b"].to_list())