# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. import tvm from tvm.s_tir.meta_schedule.testing import te_workload from tvm.script import ir as I from tvm.script import tirx as T # pylint: disable=invalid-name,no-member,line-too-long,too-many-nested-blocks,no-self-argument,missing-class-docstring,missing-function-docstring # fmt: off @I.ir_module(s_tir=True) class Module: @T.prim_func(s_tir=True) def main( A: T.Buffer((729, 729), "float32"), B: T.Buffer((729, 729), "float32"), C: T.Buffer((729, 729), "float32"), ): T.func_attr( { "global_symbol": "test", "target": tvm.target.Target("llvm", host="llvm"), "tirx.noalias": True, } ) # with T.sblock("root"): for i, j, k in T.grid(729, 729, 729): with T.sblock("C"): v_i, v_j, v_k = T.axis.remap("SSR", [i, j, k]) T.reads(A[v_i, v_k], B[v_k, v_j]) T.writes(C[v_i, v_j]) with T.init(): C[v_i, v_j] = T.float32(0) C[v_i, v_j] = C[v_i, v_j] + A[v_i, v_k] * B[v_k, v_j] # fmt: on # pylint: enable=invalid-name,no-member,line-too-long,too-many-nested-blocks,no-self-argument,missing-class-docstring,missing-function-docstring def test_host_func(): """Test that host functions are not split.""" # te schedule copied from test_tir_transform_split_host_device.py func = tvm.te.create_prim_func( te_workload.matmul(729, 729, 729, in_dtype="float32", out_dtype="float32") ) mod = tvm.ir.IRModule({"main": func}) target = tvm.target.Target("cuda") mod = tvm.tirx.transform.Apply( lambda f: f.with_attr( { "global_symbol": "test", "tirx.is_host_func": True, } ) )(mod) mod = tvm.tirx.transform.BindTarget(target)(mod) tvm.ir.assert_structural_equal(mod, Module) assert "tirx.is_host_func" not in mod["main"].attrs, ( """Target and is_host_func attributes should be mutually exclusive""" ) if __name__ == "__main__": test_host_func()