Method main

tests/python/relax/test_analysis_estimate_memory_usage.py:72–115

(x: R.Tensor((2, 4), dtype="float32"))

        @R.function(pure=False)
        def main(x: R.Tensor((2, 4), dtype="float32")) -> R.Tensor((10,), dtype="float32"):
            cls = Module
            storage: R.Object = R.memory.alloc_storage(
                R.shape([32]), virtual_device_index=0, storage_scope="global", dtype="float32"
            )
            alloc: R.Tensor((2, 4), dtype="float32") = R.memory.alloc_tensor(
                storage, offset=0, shape=R.shape([2, 4]), dtype="float32"
            )
            _: R.Tuple() = cls.exp(x, alloc)
            lv: R.Tensor((2, 4), dtype="float32") = alloc
            lv1: R.Tensor((8,), dtype="float32") = R.call_packed(
                "vm.builtin.reshape", lv, R.shape([8]), sinfo_args=[R.Tensor((8,), dtype="float32")]
            )
            storage1: R.Object = R.memory.alloc_storage(
                R.shape([40]), virtual_device_index=0, storage_scope="global", dtype="float32"
            )
            alloc1: R.Tensor((8,), dtype="float32") = R.memory.alloc_tensor(
                storage1, offset=0, shape=R.shape([8]), dtype="float32"
            )
            _1: R.Tuple() = cls.relu(lv1, alloc1)
            _2: R.Tuple() = R.memory.kill_tensor(alloc)
            _3: R.Tuple() = R.memory.kill_tensor(lv1)
            lv2: R.Tensor((8,), dtype="float32") = alloc1
            alloc2: R.Tensor((8,), dtype="float32") = R.memory.alloc_tensor(
                storage, offset=0, shape=R.shape([8]), dtype="float32"
            )
            _4: R.Tuple() = cls.add(lv2, R.const(1, "float32"), alloc2)
            _5: R.Tuple() = R.memory.kill_tensor(alloc1)
            lv3: R.Tensor((8,), dtype="float32") = alloc2
            alloc3: R.Tensor((10,), dtype="float32") = R.memory.alloc_tensor(
                storage1, offset=0, shape=R.shape([10]), dtype="float32"
            )
            _6: R.Tuple() = cls.pad(lv3, alloc3)
            _7: R.Tuple() = R.memory.kill_tensor(alloc2)
            lv4: R.Tensor((10,), dtype="float32") = alloc3
            alloc4: R.Tensor((10,), dtype="float32") = R.builtin.alloc_tensor(
                R.shape([10]), dtype="float32", runtime_device_index=0
            )
            _8: R.Tuple() = cls.log(lv4, alloc4)
            _9: R.Tuple() = R.memory.kill_tensor(alloc3)
            gv5: R.Tensor((10,), dtype="float32") = alloc4
            _11: R.Tuple() = R.memory.kill_storage(storage)
            _10: R.Tuple() = R.memory.kill_storage(storage1)
            return gv5

    assert (
        estimate_memory_usage(Module)