/* * 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 namespace migraphx { inline namespace MIGRAPHX_INLINE_NS { namespace onnx { struct parse_gather_elements : op_parser { std::vector operators() const { return {{"GatherElements"}}; } instruction_ref parse(const op_desc& opd, const onnx_parser& parser, onnx_parser::node_info info, std::vector args) const { int axis = 0; if(contains(info.attributes, "axis")) { axis = parser.parse_value(info.attributes.at("axis")).at(); } // standardize input data and index auto arg_data = info.make_contiguous(args[0]); auto arg_ind = info.make_contiguous(args[1]); auto data_s = arg_data->get_shape(); auto ind_s = arg_ind->get_shape(); if(data_s.lens().size() != ind_s.lens().size()) { MIGRAPHX_THROW("PARSE_GATHER_ELEMENTS: input data and index must have the same rank!"); } int n_rank = static_cast(data_s.lens().size()); int tuned_axis = tune_axis(n_rank, axis, opd.op_name); auto axis_stride = data_s.strides()[tuned_axis]; int64_t data_elem_num = data_s.elements(); // reshape the input data as one dimension and used as input data // to the gather operator arg_data = info.add_instruction(make_op("reshape", {{"dims", {data_elem_num}}}), arg_data); std::size_t elem_num = ind_s.elements(); std::vector ind_index(elem_num); std::iota(ind_index.begin(), ind_index.end(), 0); // convert index in input indices to that in input data std::vector data_indices(elem_num); std::transform(ind_index.begin(), ind_index.end(), data_indices.begin(), [&](auto i) { return data_s.index(ind_s.multi(i)); }); std::vector vec_axis_ind(elem_num); std::transform(ind_index.begin(), ind_index.end(), vec_axis_ind.begin(), [&](auto i) { return ind_s.multi(i)[tuned_axis]; }); auto l_shape_idx = info.add_literal(literal(ind_s, data_indices.begin(), data_indices.end())); auto l_dim_idx = info.add_literal(literal(ind_s, vec_axis_ind.begin(), vec_axis_ind.end())); auto l_stride = info.add_literal(literal{{ind_s.type(), {1}}, {axis_stride}}); l_stride = info.add_instruction(make_op("multibroadcast", {{"out_lens", ind_s.lens()}}), l_stride); auto dim_diff = info.add_instruction(make_op("sub"), arg_ind, l_dim_idx); auto delta = info.add_instruction(make_op("mul"), dim_diff, l_stride); auto ind = info.add_instruction(make_op("add"), l_shape_idx, delta); auto op = make_op("gather", {{"axis", 0}}); return info.add_instruction(op, arg_data, ind); } }; } // namespace onnx } // namespace MIGRAPHX_INLINE_NS } // namespace migraphx