| # 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. |
| |
| """ |
| Test relax transform - Eliminate redundant reshape operations |
| """ |
| import tvm.testing |
| from tvm import relax |
| from tvm.relax.transform import DeadCodeElimination |
| from tvm.relax.transform import RemoveRedundantReshape |
| from tvm.script import ir as I, relax as R |
| |
| |
| def _run_pass_compare_output(Before, Expected): |
| fused_mod = RemoveRedundantReshape()(Before) |
| fused_mod = DeadCodeElimination()(fused_mod) |
| tvm.ir.assert_structural_equal(Expected, fused_mod) |
| |
| |
| def test_remove_redundant_reshape_pass_one_arg(): |
| @I.ir_module |
| class Before: |
| @R.function |
| def main( |
| x: R.Tensor((1, 1001, 1, 1), dtype="float16") |
| ) -> R.Tensor((1, 1001), dtype="float16"): |
| with R.dataflow(): |
| lv: R.Tensor((1, 1001), dtype="float16") = R.reshape(x, R.shape([1, 1001])) |
| lv1: R.Tensor((1, 1001), dtype="float16") = R.reshape(lv, R.shape([1, 1001])) |
| gv: R.Tensor((1, 1001), dtype="float16") = R.reshape(lv1, R.shape([1, 1001])) |
| R.output(gv) |
| return gv |
| |
| @I.ir_module |
| class Expected: |
| @R.function |
| def main( |
| x: R.Tensor((1, 1001, 1, 1), dtype="float16") |
| ) -> R.Tensor((1, 1001), dtype="float16"): |
| with R.dataflow(): |
| gv: R.Tensor((1, 1001), dtype="float16") = R.reshape(x, R.shape([1, 1001])) |
| R.output(gv) |
| return gv |
| |
| _run_pass_compare_output(Before, Expected) |
| |
| |
| def test_remove_redundant_reshape_pass_two_arg(): |
| @I.ir_module |
| class Before: |
| @R.function |
| def main( |
| x: R.Tensor((1, 1001, 1, 1), dtype="float16") |
| ) -> R.Tensor((1, 1001), dtype="float16"): |
| with R.dataflow(): |
| lv: R.Tensor((1, 1001, 1), dtype="float16") = R.reshape(x, R.shape([1, 1001, 1])) |
| lv1: R.Tensor((1, 1001), dtype="float16") = R.reshape(lv, R.shape([1, 1001])) |
| R.output(lv1) |
| return lv1 |
| |
| @I.ir_module |
| class Expected: |
| @R.function |
| def main( |
| x: R.Tensor((1, 1001, 1, 1), dtype="float16") |
| ) -> R.Tensor((1, 1001), dtype="float16"): |
| with R.dataflow(): |
| lv1: R.Tensor((1, 1001), dtype="float16") = R.reshape(x, R.shape([1, 1001])) |
| R.output(lv1) |
| return lv1 |
| |
| _run_pass_compare_output(Before, Expected) |
| |
| |
| def test_remove_redundant_reshape_pass_three_arg(): |
| @I.ir_module |
| class Before: |
| @R.function |
| def main( |
| x: R.Tensor((1, 1001, 1, 1), dtype="float16") |
| ) -> R.Tensor((1, 1001, 1, 1), dtype="float16"): |
| with R.dataflow(): |
| lv: R.Tensor((1, 1001, 1, 1), dtype="float16") = R.reshape( |
| x, R.shape([1, 1001, 1, 1]) |
| ) |
| R.output(lv) |
| return lv |
| |
| @I.ir_module |
| class Expected: |
| @R.function |
| def main( |
| x: R.Tensor((1, 1001, 1, 1), dtype="float16") |
| ) -> R.Tensor((1, 1001, 1, 1), dtype="float16"): |
| return x |
| |
| _run_pass_compare_output(Before, Expected) |
| |
| |
| if __name__ == "__main__": |
| tvm.testing.main() |