class TestLinear(TestCase):
def setUp(self):
self.linear = Linear(indim=10, dim=15)
self.data = np.random.random((100, 10))
self.out = self.linear.predict(self.data)
def test_linear_shapes(self):
self.assertEqual(self.out.shape, (100, 15))
def test_linear_output(self):
self.assertTrue(np.allclose(self.out, np.dot(self.data, self.linear.W.d.get_value()) + self.linear.b.d.get_value()))
class TestLinear(TestCase):
def setUp(self):
self.linear = Linear(indim=10, dim=15)
self.data = np.random.random((100, 10))
self.out = self.linear.predict(self.data)
def test_linear_shapes(self):
self.assertEqual(self.out.shape, (100, 15))
def test_linear_output(self):
self.assertTrue(
np.allclose(
self.out,
np.dot(self.data, self.linear.W.d.get_value()) +
self.linear.b.d.get_value()))
def test_set_lr(self):
lin = Linear(indim=10, dim=15)
lin.set_lr(0.123)
o = lin(Val(0))
#print ["{}: {}".format(x, x.lrmul) for x in o.allparams]
for x in o.allparams:
self.assertEqual(x.lrmul, 0.123)
def test_get_params(self):
lin = Linear(indim=10, dim=15)
params = {lin.W, lin.b}
self.assertEqual(params, lin.get_params())
def test_multilevel_set_lr(self):
l1 = Linear(10, 11)
l2 = Linear(11, 12)
l3 = Linear(12, 13)
s = stack(l1, l2, l3)
s[1].set_lr(0.5)
s[2].set_lr(0.1)
o = s(Val(0))
l1o = s[0](Val(0))
l2o = s[1](Val(0))
l3o = s[2](Val(0))
print["{}: {}".format(x, x.lrmul) for x in o.allparams]
for x in o.allparams:
if x in l1o.allparams:
self.assertEqual(x.lrmul, 1.0)
elif x in l2o.allparams:
self.assertEqual(x.lrmul, 0.5)
elif x in l3o.allparams:
self.assertEqual(x.lrmul, 0.1)
s.set_lr(0.21)
o = s(Val(0))
print["{}: {}".format(x, x.lrmul) for x in o.allparams]
for x in o.allparams:
self.assertEqual(x.lrmul, 0.21)
class TestLinear(TestCase):
def setUp(self):
self.linear = Linear(indim=10, dim=15)
self.data = np.random.random((100, 10))
self.out = self.linear.predict(self.data)
def test_linear_shapes(self):
self.assertEqual(self.out.shape, (100, 15))
def test_linear_output(self):
self.assertTrue(
np.allclose(
self.out,
np.dot(self.data, self.linear.W.d.get_value()) +
self.linear.b.d.get_value()))
