/* * The MIT License (MIT) * * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved. * * Permission is hereby granted, free of charge, to any person obtaining a copy * of this software and associated documentation files (the "Software"), to deal * in the Software without restriction, including without limitation the rights * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell * copies of the Software, and to permit persons to whom the Software is * furnished to do so, subject to the following conditions: * * The above copyright notice and this permission notice shall be included in * all copies or substantial portions of the Software. * * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN * THE SOFTWARE. */ #include #include #include #include #include #include #include #include #include void run_pass(migraphx::module& m) { migraphx::run_passes( m, {migraphx::normalize_ops{}, migraphx::insert_pad{}, migraphx::dead_code_elimination{}}); } migraphx::instruction_ref create_im2col(migraphx::instruction_ref& l_img, size_t channels, migraphx::module& m) { size_t f[2] = {1, 1}; std::vector weights(channels * f[0] * f[1]); migraphx::shape s_weights{migraphx::shape::int32_type, {1, channels, f[0], f[1]}}; auto l_weights = m.add_literal(migraphx::literal{s_weights, weights}); return m.add_instruction( migraphx::make_op("im2col", {{"padding", {0, 0, 1, 1}}}), l_img, l_weights); } migraphx::instruction_ref create_conv(migraphx::instruction_ref& l_img, size_t channels, migraphx::module& m, migraphx::op::padding_mode_t padding_mode = migraphx::op::padding_mode_t::default_) { migraphx::shape s_weights{migraphx::shape::int32_type, {4, channels, 3, 3}}; std::vector weights(4 * channels * 3 * 3); auto l_weights = m.add_literal(migraphx::literal{s_weights, weights}); migraphx::op::convolution op; op.padding_mode = padding_mode; op.padding = {0, 0, 1, 1}; return m.add_instruction(op, l_img, l_weights); } TEST_CASE(rewrite_pad) { migraphx::module m; size_t img_dim[2] = {2, 2}; size_t channels = 1; std::vector input(channels * img_dim[0] * img_dim[1]); std::iota(input.begin(), input.end(), 0); migraphx::shape s_img{migraphx::shape::int32_type, {1, channels, img_dim[0], img_dim[1]}}; auto l_img = m.add_literal(migraphx::literal{s_img, input}); auto l0 = create_im2col(l_img, channels, m); auto l1 = create_conv(l_img, channels, m); auto l2 = m.add_instruction( migraphx::make_op("pooling", {{"mode", migraphx::op::pooling_mode::max}, {"padding", {0, 0, 1, 1}}}), l_img); m.add_instruction(migraphx::make_op("identity"), l0, l1, l2); run_pass(m); EXPECT(std::any_of( m.begin(), m.end(), [](const migraphx::instruction& ins) { return ins.name() == "pad"; })); } TEST_CASE(rewrite_pad_symmetric) { migraphx::module m; size_t img_dim[2] = {2, 2}; size_t channels = 1; std::vector input(channels * img_dim[0] * img_dim[1]); std::iota(input.begin(), input.end(), 0); migraphx::shape s_img{migraphx::shape::int32_type, {1, channels, img_dim[0], img_dim[1]}}; auto l_img = m.add_literal(migraphx::literal{s_img, input}); m.add_instruction( migraphx::make_op("pooling", {{"mode", migraphx::op::pooling_mode::max}, {"padding", {1, 1, 1, 1}}}), l_img); run_pass(m); EXPECT(std::none_of( m.begin(), m.end(), [](const migraphx::instruction& ins) { return ins.name() == "pad"; })); } int main(int argc, const char* argv[]) { test::run(argc, argv); }