feat(opr): let roll support empty IO

GitOrigin-RevId: b9a59b623a8b16ca0a6af1340cfc226b73128321

imperative/python/megengine/functional/tensor.py

@@ -1352,10 +1352,11 @@ def roll(
         if shift_ == 0:
             continue
         size = shp[axis_normalized_]
-        if shift_ > 0:
-            a, b = split(out, [size - shift_,], axis=axis_normalized_)
+        shift_normalized_ = 0 if size == 0 else shift_ % size
+        if shift_normalized_ > 0:
+            a, b = split(out, [size - shift_normalized_,], axis=axis_normalized_)
         else:
-            a, b = split(out, [-shift_,], axis=axis_normalized_)
+            a, b = split(out, [-shift_normalized_,], axis=axis_normalized_)
         out = concat((b, a), axis=axis_normalized_)
     if shp_bak is not None:
         out = out.reshape(shp_bak)

imperative/python/test/unit/functional/test_tensor.py

@@ -806,6 +806,8 @@ def test_tile(shape, reps, is_varnode):
     [
         ((2, 3), 0, None),
         ((2, 3), 1, 0),
+        ((2, 3), 100, 0),
+        ((2, 3), -100, 0),
         ((2, 3, 4, 5), (-1, 1), (0, 1)),
         ((2, 3, 4, 5), (-2, 1, 2), (1, 2, 3)),
     ],
@@ -829,3 +831,24 @@ def test_roll(shape, shifts, axis, is_varnode):
     opr_test(
         cases, func, ref_fn=lambda inp: np.roll(inp, shifts, axis), network=network
     )
+
+
+@pytest.mark.parametrize(
+    "shape, shifts, axis", [((10, 0), 5, 1), ((10, 0), -10, 1),],
+)
+@pytest.mark.parametrize("is_symbolic", [None, True, False])
+def test_roll_empty_tensor(shape, shifts, axis, is_symbolic):
+    inp = tensor(np.random.randn(*shape).astype("float32"))
+
+    def func(inp):
+        return F.roll(inp, shifts, axis)
+
+    if is_symbolic is not None:
+        func = trace(symbolic=is_symbolic)(func)
+
+    out_ref = np.roll(inp.numpy(), shifts, axis)
+    for _ in range(3):
+        out = F.roll(inp, shifts, axis)
+        np.testing.assert_equal(out.numpy(), out_ref)
+        if is_symbolic is None:
+            break

src/opr/impl/tensor_manip.cpp

@@ -1339,8 +1339,10 @@ void Concat::scn_do_execute() {
         if (real_axis < 0)
             real_axis += in.shape().ndim;
         end = begin + in.shape().shape[real_axis];
-        out.sub(Slice(begin, end).apply(out.layout(), real_axis)).
-            copy_from_fixlayout(in);
+        if (!in.layout().is_empty()) {
+            out.sub(Slice(begin, end).apply(out.layout(), real_axis)).
+                copy_from_fixlayout(in);
+        }
     }
 }