# 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 import te def test_double_buffer(): dtype = "int64" n = 100 m = 4 tx = te.thread_axis("threadIdx.x") ib = tvm.tir.ir_builder.create() A = ib.pointer("float32", name="A") C = ib.pointer("float32", name="C") ib.scope_attr(tx, "thread_extent", 1) with ib.for_range(0, n) as i: B = ib.allocate("float32", m, name="B", scope="shared") with ib.new_scope(): ib.scope_attr(B.asobject(), "double_buffer_scope", 1) with ib.for_range(0, m) as j: B[j] = A[i * 4 + j] with ib.for_range(0, m) as j: C[j] = B[j] + 1 stmt = ib.get() mod = tvm.IRModule({"db": tvm.tir.PrimFunc([A.asobject(), C.asobject()], stmt)}) opt = tvm.transform.Sequential( [tvm.tir.transform.InjectDoubleBuffer(), tvm.tir.transform.Simplify()] ) with tvm.transform.PassContext(config={"tir.InjectDoubleBuffer": {"split_loop": 2}}): mod = opt(mod) stmt = mod["db"].body assert isinstance(stmt.body, tvm.tir.Allocate) assert stmt.body.extents[0].value == 2 f = tvm.tir.transform.ThreadSync("shared")(mod)["db"] count = [0] def count_sync(op): if isinstance(op, tvm.tir.Call) and op.op.same_as(tvm.ir.Op.get("tir.tvm_storage_sync")): count[0] += 1 tvm.tir.stmt_functor.post_order_visit(f.body, count_sync) assert count[0] == 4 if __name__ == "__main__": test_double_buffer()