test_contrastive.py 文件源码

def check_forward(self, x0_data, x1_data, t_data):
        x0_val = chainer.Variable(x0_data)
        x1_val = chainer.Variable(x1_data)
        t_val = chainer.Variable(t_data)
        loss = functions.contrastive(x0_val, x1_val, t_val, self.margin)
        self.assertEqual(loss.data.shape, ())
        self.assertEqual(loss.data.dtype, numpy.float32)
        loss_value = float(cuda.to_cpu(loss.data))

        # Compute expected value
        loss_expect = 0
        for i in six.moves.range(self.x0.shape[0]):
            x0d, x1d, td = self.x0[i], self.x1[i], self.t[i]
            d = numpy.sum((x0d - x1d) ** 2)
            if td == 1:  # similar pair
                loss_expect += d
            elif td == 0:  # dissimilar pair
                loss_expect += max(self.margin - math.sqrt(d), 0) ** 2
        loss_expect /= 2.0 * self.t.shape[0]
        self.assertAlmostEqual(loss_expect, loss_value, places=5)