# 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 def test_virtual_thread(): m = tvm.var('m') A = tvm.placeholder((m, ), name='A') A1 = tvm.compute((m,), lambda i: A[i], name='A1') A2 = tvm.compute((m,), lambda i: A1[i] + 3, name='A2') s = tvm.create_schedule(A2.op) vx = tvm.thread_axis("vthread", name="vx") xo, xi = s[A2].split(A2.op.axis[0], nparts=2) s[A2].bind(xo, vx) xo, xi = s[A2].split(xi, 8) s[A1].compute_at(s[A2], xo) bounds = tvm.schedule.InferBound(s) assert isinstance(bounds, tvm.container.Map) stmt = tvm.schedule.ScheduleOps(s, bounds) Ab = tvm.decl_buffer(A.shape, A.dtype, name='A') A2b = tvm.decl_buffer(A2.shape, A2.dtype, name='A2') stmt = tvm.ir_pass.StorageFlatten(stmt, {A: Ab, A2: A2b}, 64) stmt = tvm.ir_pass.Simplify(stmt) stmt = tvm.ir_pass.InjectVirtualThread(stmt) print(stmt) if __name__ == "__main__": test_virtual_thread()