/* * 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 namespace migraphx { inline namespace MIGRAPHX_INLINE_NS { namespace cpu { struct dnnl_eltwise : dnnl_op { std::string algo; float alpha = 0; float beta = 0; template static auto reflect(Self& self, F f) { return pack_join(self.reflect_base(self, f), pack(f(self.algo, "algo"), f(self.alpha, "alpha"), f(self.beta, "beta"))); } std::string group() const { return this->name() + "::" + algo; } std::string name() const { return "dnnl::eltwise"; } shape compute_shape(std::vector inputs) const { // Compensate for allocation inputs.pop_back(); check_shapes{this->trim_post_op_inputs(inputs), *this}.has(1).packed(); auto s = inputs.at(0); auto r = s; if(not s.packed()) r = shape{s.type(), s.lens()}; // Call to get_primitive to make sure an algo is available this->get_primitive(this->to_memory_desc(r, inputs)); return r; } dnnl::eltwise_forward::desc get_desc(const std::unordered_map& m) const { return {dnnl::prop_kind::forward_inference, to_dnnl_algo(algo), m.at(MIGRAPHX_DNNL_PREFIX(ARG_SRC_0)), alpha, beta}; } }; } // namespace cpu } // namespace MIGRAPHX_INLINE_NS } // namespace migraphx