# 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 pytest import tvm from tvm import te @pytest.mark.xfail def test_loop_dependent_allocate(): N = te.size_var("N") A = te.placeholder((2*N,), "float32", "A") C = te.compute((N, ), lambda i: A[2*i] + A[i+1], name='C') s = te.create_schedule(C.op) AA = s.cache_read(A, "local", [C]) s[AA].compute_at(s[C], s[C].op.axis[0]) # this line should fail due to IRUseDefAnalysis sees an allocate statement # referencing undefined variable tvm.lower(s, [A,C]) if __name__ == "__main__": test_loop_dependent_allocate()