# 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_lower_rfactor(): n = te.size_var("n") m = te.size_var("m") A = te.placeholder((n, m), name="A") k = te.reduce_axis((0, m), "k") B = te.compute((n,), lambda i: te.sum(A[i, k], axis=k), name="B") s = te.create_schedule(B.op) ko, ki = s[B].split(B.op.reduce_axis[0], factor=16) BF = s.rfactor(B, ki) xo, xi = s[B].split(s[B].op.axis[0], factor=32) s[B.op].bind(xo, te.thread_axis("blockIdx.x")) s[B.op].bind(xi, te.thread_axis("threadIdx.y")) s[B].bind(s[B].op.reduce_axis[0], te.thread_axis("threadIdx.x")) s[BF].compute_at(s[B], s[B].op.reduce_axis[0]) fapi = tvm.lower(s, [A, B]) def test_dependent_output_shape(): n, m, x = te.size_var("n"), te.size_var("m"), te.size_var("x") A = te.placeholder((n, m)) B = te.compute((m, n // x), lambda i, j: A[i, j], name="B") s = te.create_schedule(B.op) mod = tvm.build(s, [A, B, x]) def test_split_uneven_unique_likely(): a = te.placeholder( (16, 16), ) b = te.placeholder( (16, 16), ) c = te.compute((16, 16), lambda x, y: a[x, y] + b[x, y]) x, y = c.op.axis sch = te.create_schedule(c.op) xo, xi = sch[c].split(x, 5) stmt = tvm.lower(sch, [a, b, c])["main"].body assert isinstance(stmt.body.body, tvm.tir.stmt.IfThenElse) if __name__ == "__main__": test_lower_rfactor() test_dependent_output_shape() test_split_uneven_unique_likely()