mean_squared_error_test.py 文件源码

def check_forward(self, x_data, t_data, v_data, use_visibility):
        x = chainer.Variable(x_data)
        t = chainer.Variable(t_data)
        v = chainer.Variable(v_data)
        loss = mean_squared_error(x, t, v, use_visibility)
        loss_value = cuda.to_cpu(loss.data)
        eq_(loss_value.dtype, np.float32)
        eq_(loss_value.shape, ())
        # compute expected value.
        loss_expect = 0.
        for i in np.ndindex(self.x.shape):
            diff = self.x[i] - self.t[i]
            if use_visibility:
                diff *= self.v[i[:-1]]
            loss_expect += diff**2
        if use_visibility:
            N = self.v.sum()/2
        else:
            N = self.x.size/2
        loss_expect /= N
        self.assertAlmostEqual(loss_expect, loss_value, places=5)