test(autograd): test jvp emulated by 2nd grad

GitOrigin-RevId: 47114fcd99f53b335c1615896370dd6e45dd3693

imperative/python/src/grad_override.cpp

@@ -163,7 +163,9 @@ apply_result_t indexingMultiAxisVec_grad_rule(ApplyContext& ctx, CustomBackward:
 apply_result_t reduce_grad_rule(ApplyContext& ctx, CustomBackward::Maker& maker) {
     auto& op = ctx.op->cast_final_safe<Reduce>();
     if (op.mode == Reduce::Mode::SUM) {
-        mgb_assert(ctx.nargs == 1);
+        if (ctx.nargs != 1) {
+            throw GradRuleFallback();
+        }
         std::array<std::shared_ptr<Tensor>, 1> input_shapes;
         if (input_requires_grad(ctx, 0)) {
             input_shapes[0] = get_shape(ctx.args[0]);

imperative/python/test/unit/autodiff/test_grad_manger.py

@@ -349,3 +349,29 @@ def test_grad_manager_visibility_by_order():
             gm.backward(x.grad)
 
     np.testing.assert_almost_equal(x.grad.numpy(), -np.sin(x_np), decimal=5)
+
+
+@pytest.mark.require_higher_order_directive()
+@pytest.mark.parametrize("target", [F.cos, F.sin, lambda x: x * 2 + 1])
+def test_emulate_forward_mode_with_reverse_mode(target):
+    def jvp(inp, expr):
+        with GradManager() as gm:
+            with GradManager().attach([inp]) as gm2:
+                oup = expr(inp)
+                oup_grad = F.zeros_like(oup)
+                gm.attach(oup_grad)
+                gm2.backward(oup, oup_grad)
+            gm.backward(inp.grad)
+        return oup, oup_grad.grad
+
+    def fake_jvp(inp, expr):
+        delta = 0.001
+        return expr(inp), (expr(inp + delta) - expr(inp - delta)) / (2 * delta)
+
+    x_np = np.random.rand(10).astype("float32")
+    x = mge.tensor(x_np)
+    y, dy = jvp(x, target)
+    y1, dy1 = fake_jvp(x, target)
+
+    np.testing.assert_almost_equal(y.numpy(), y1.numpy(), decimal=5)
+    np.testing.assert_almost_equal(dy.numpy(), dy1.numpy(), decimal=3)