(x: R.Tensor((2, 4), dtype="float32"))
| 56 | |
| 57 | @R.function |
| 58 | def main(x: R.Tensor((2, 4), dtype="float32")) -> R.Tensor((10,), dtype="float32"): |
| 59 | # we expected RemovePurityChecking to have been invoked first |
| 60 | R.func_attr({"relax.force_pure": True}) |
| 61 | cls = Module |
| 62 | alloc: R.Tensor((2, 4), dtype="float32") = R.builtin.alloc_tensor(R.shape([2, 4]), dtype="float32", runtime_device_index=0) |
| 63 | _: R.Tuple() = cls.exp(x, alloc) |
| 64 | lv: R.Tensor((2, 4), dtype="float32") = alloc |
| 65 | lv1: R.Tensor((8,), dtype="float32") = R.reshape(lv, (8,)) |
| 66 | alloc1: R.Tensor((8,), dtype="float32") = R.builtin.alloc_tensor(R.shape([8]), dtype="float32", runtime_device_index=0) |
| 67 | _1: R.Tuple() = cls.relu(lv1, alloc1) |
| 68 | lv2: R.Tensor((8,), dtype="float32") = alloc1 |
| 69 | alloc2: R.Tensor((8,), dtype="float32") = R.builtin.alloc_tensor(R.shape([8]), dtype="float32", runtime_device_index=0) |
| 70 | _2: R.Tuple() = cls.add(lv2, R.const(1, "float32"), alloc2) |
| 71 | lv3: R.Tensor((8,), dtype="float32") = alloc2 |
| 72 | alloc3: R.Tensor((10,), dtype="float32") = R.builtin.alloc_tensor(R.shape([10]), dtype="float32", runtime_device_index=0) |
| 73 | _3: R.Tuple() = cls.pad(lv3, alloc3) |
| 74 | lv4: R.Tensor((10,), dtype="float32") = alloc3 |
| 75 | alloc4: R.Tensor((10,), dtype="float32") = R.builtin.alloc_tensor(R.shape([10]), dtype="float32", runtime_device_index=0) |
| 76 | _4: R.Tuple() = cls.log(lv4, alloc4) |
| 77 | gv: R.Tensor((10,), dtype="float32") = alloc4 |
| 78 | return gv |
| 79 | |
| 80 | @tvm.script.ir_module |
| 81 | class Expected: |
no test coverage detected