| # 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() |
