test_action_value.py 文件源码

def test_max_bounded(self):
        n_batch = 20
        ndim_action = 3
        mu = np.random.randn(n_batch, ndim_action).astype(np.float32)
        mat = np.broadcast_to(
            np.eye(ndim_action, dtype=np.float32)[None],
            (n_batch, ndim_action, ndim_action))
        v = np.random.randn(n_batch).astype(np.float32)
        min_action, max_action = -1.3, 1.3
        q_out = action_value.QuadraticActionValue(
            chainer.Variable(mu),
            chainer.Variable(mat),
            chainer.Variable(v),
            min_action, max_action)

        v_out = q_out.max
        self.assertIsInstance(v_out, chainer.Variable)
        v_out = v_out.data

        # If mu[i] is an valid action, v_out[i] should be v[i]
        mu_is_allowed = np.all(
            (min_action < mu) * (mu < max_action),
            axis=1)
        np.testing.assert_almost_equal(v_out[mu_is_allowed], v[mu_is_allowed])

        # Otherwise, v_out[i] should be less than v[i]
        mu_is_not_allowed = ~np.all(
            (min_action - 1e-2 < mu) * (mu < max_action + 1e-2),
            axis=1)
        np.testing.assert_array_less(
            v_out[mu_is_not_allowed],
            v[mu_is_not_allowed])