/* * 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 "verify_program.hpp" #include #include #include #include #include migraphx::instruction_ref add_instancenorm(migraphx::module& m, migraphx::instruction_ref x, const std::vector& dims, float eps = 1e-5f) { auto mgx_type = x->get_shape().type(); auto x_lens = x->get_shape().lens(); std::vector axes(x_lens.size() - 2); std::iota(axes.begin(), axes.end(), 2); auto scale = m.add_parameter("scale", migraphx::shape{mgx_type, dims}); auto bias = m.add_parameter("bias", migraphx::shape{mgx_type, dims}); auto epsilon = m.add_literal(migraphx::literal{migraphx::shape{mgx_type}, {eps}}); auto mean = m.add_instruction(migraphx::make_op("reduce_mean", {{"axes", axes}}), x); auto mean_mbcast = m.add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", x_lens}}), mean); auto sub = m.add_instruction(migraphx::make_op("sub"), x, mean_mbcast); auto l0 = m.add_instruction(migraphx::make_op("sqdiff"), {x, mean_mbcast}); auto var = m.add_instruction(migraphx::make_op("reduce_mean", {{"axes", axes}}), {l0}); auto epsilon_mbcast = m.add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", x_lens}}), epsilon); auto var_mbcast = m.add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", x_lens}}), var); auto add_epsilon = m.add_instruction(migraphx::make_op("add"), var_mbcast, epsilon_mbcast); auto rsqrt = m.add_instruction(migraphx::make_op("rsqrt"), add_epsilon); auto l1 = m.add_instruction(migraphx::make_op("mul"), {sub, rsqrt}); auto scale_mbcast = m.add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", x_lens}}), scale); auto mul = m.add_instruction(migraphx::make_op("mul"), scale_mbcast, l1); auto bias_mbcast = m.add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", x_lens}}), bias); return m.add_instruction(migraphx::make_op("add"), mul, bias_mbcast); } template struct test_instancenorm : verify_program> { migraphx::program create_program() const { migraphx::program p; auto* mm = p.get_main_module(); std::vector dims = {1, 2, 5, 5}; auto x = mm->add_parameter("x", migraphx::shape{TYPE, dims}); add_instancenorm(*mm, x, {1, 2, 1, 1}); return p; } }; template struct test_instancenorm; template struct test_instancenorm; template struct test_instancenorm_large_3d : verify_program> { migraphx::program create_program() const { migraphx::program p; auto* mm = p.get_main_module(); std::vector dims = {1, 32, 64, 64, 64}; auto x = mm->add_parameter("x", migraphx::shape{TYPE, dims}); add_instancenorm(*mm, x, {1, 32, 1, 1, 1}); return p; } }; template struct test_instancenorm_large_3d; template struct test_instancenorm_large_3d;