def test_concat(self):
t1 = tensor.Tensor((2, 3))
t2 = tensor.Tensor((1, 3))
t1.set_value(1)
t2.set_value(2)
lyr = layer.Concat('concat', 0, [t1.shape, t2.shape])
t = lyr.forward(model_pb2.kTrain, [t1, t2])
tnp = tensor.to_numpy(t[0])
self.assertEquals(np.sum(tnp), 12)
def test_concat(self):
t1 = tensor.Tensor((2, 3))
t2 = tensor.Tensor((1, 3))
t1.set_value(1)
t2.set_value(2)
lyr = layer.Concat('concat', 0, [(3, ), (3, )])
t = lyr.forward(model_pb2.kTrain, [t1, t2])
tnp = tensor.to_numpy(t)
self.assertEquals(np.sum(tnp), 12)
t3 = tensor.Tensor((3, 3))
t3.set_value(1.5)
grads, _ = lyr.backward(model_pb2.kTrain, [t3])
gnp = tensor.to_numpy(grads[0])
self.assertEquals(np.sum(gnp), 6 * 1.5)