| 865 | |
| 866 | @R.function |
| 867 | def func1( |
| 868 | x: R.Tensor((2, 3), dtype="float32"), y: R.Tensor((2, 3), dtype="int32") |
| 869 | ) -> R.Tensor((2, 3), dtype="float32"): |
| 870 | R.func_attr({"relax.force_pure": True}) |
| 871 | cls = Expected |
| 872 | storage: R.Object = R.memory.alloc_storage( |
| 873 | R.shape([24]), virtual_device_index=0, storage_scope="global", dtype="float32" |
| 874 | ) |
| 875 | alloc: R.Tensor((2, 3), dtype="float32") = R.memory.alloc_tensor( |
| 876 | storage, 0, R.shape([2, 3]), dtype="float32" |
| 877 | ) |
| 878 | _: R.Tuple() = cls.add(x, x, alloc) |
| 879 | gv1: R.Tensor((2, 3), dtype="float32") = alloc |
| 880 | storage1: R.Object = R.memory.alloc_storage( |
| 881 | R.shape([24]), virtual_device_index=0, storage_scope="global", dtype="int32" |
| 882 | ) |
| 883 | alloc1: R.Tensor((2, 3), dtype="int32") = R.memory.alloc_tensor( |
| 884 | storage1, 0, R.shape([2, 3]), dtype="int32" |
| 885 | ) |
| 886 | _2: R.Tuple() = cls.add1(y, y, alloc1) |
| 887 | gv12: R.Tensor((2, 3), dtype="int32") = alloc1 |
| 888 | return x |
| 889 | |
| 890 | @R.function |
| 891 | def func2( |