mirror of
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103 lines
4.2 KiB
C++
103 lines
4.2 KiB
C++
/*
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* The MIT License (MIT)
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*
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* Copyright (c) 2015-2024 Advanced Micro Devices, Inc. All rights reserved.
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to deal
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* in the Software without restriction, including without limitation the rights
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* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in
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* all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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* THE SOFTWARE.
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*/
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#include <migraphx/onnx/op_parser.hpp>
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#include <migraphx/ranges.hpp>
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#include <migraphx/instruction.hpp>
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#include <migraphx/make_op.hpp>
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#include <migraphx/tune_axis.hpp>
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namespace migraphx {
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inline namespace MIGRAPHX_INLINE_NS {
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namespace onnx {
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struct parse_gather_elements : op_parser<parse_gather_elements>
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{
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std::vector<op_desc> operators() const { return {{"GatherElements"}}; }
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instruction_ref parse(const op_desc& opd,
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const onnx_parser& parser,
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onnx_parser::node_info info,
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std::vector<instruction_ref> args) const
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{
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int axis = 0;
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if(contains(info.attributes, "axis"))
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{
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axis = parser.parse_value(info.attributes.at("axis")).at<int>();
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}
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// standardize input data and index
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auto arg_data = info.make_contiguous(args[0]);
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auto arg_ind = info.make_contiguous(args[1]);
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auto data_s = arg_data->get_shape();
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auto ind_s = arg_ind->get_shape();
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if(data_s.lens().size() != ind_s.lens().size())
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{
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MIGRAPHX_THROW("PARSE_GATHER_ELEMENTS: input data and index must have the same rank!");
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}
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int n_rank = data_s.lens().size();
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int tuned_axis = tune_axis(n_rank, axis, opd.onnx_name);
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auto axis_stride = data_s.strides()[tuned_axis];
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int64_t data_elem_num = data_s.elements();
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// reshape the input data as one dimension and used as input data
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// to the gather operator
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arg_data = info.add_instruction(make_op("reshape", {{"dims", {data_elem_num}}}), arg_data);
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std::size_t elem_num = ind_s.elements();
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std::vector<int> ind_index(elem_num);
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std::iota(ind_index.begin(), ind_index.end(), 0);
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// convert index in input indices to that in input data
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std::vector<int> data_indices(elem_num);
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std::transform(ind_index.begin(), ind_index.end(), data_indices.begin(), [&](auto i) {
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return data_s.index(ind_s.multi(i));
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});
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std::vector<int> vec_axis_ind(elem_num);
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std::transform(ind_index.begin(), ind_index.end(), vec_axis_ind.begin(), [&](auto i) {
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return ind_s.multi(i)[tuned_axis];
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});
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auto l_shape_idx =
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info.add_literal(literal(ind_s, data_indices.begin(), data_indices.end()));
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auto l_dim_idx = info.add_literal(literal(ind_s, vec_axis_ind.begin(), vec_axis_ind.end()));
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auto l_stride = info.add_literal(literal{{ind_s.type(), {1}}, {axis_stride}});
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l_stride =
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info.add_instruction(make_op("multibroadcast", {{"out_lens", ind_s.lens()}}), l_stride);
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auto dim_diff = info.add_instruction(make_op("sub"), arg_ind, l_dim_idx);
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auto delta = info.add_instruction(make_op("mul"), dim_diff, l_stride);
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auto ind = info.add_instruction(make_op("add"), l_shape_idx, delta);
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auto op = make_op("gather", {{"axis", 0}});
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return info.add_instruction(op, arg_data, ind);
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}
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};
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} // namespace onnx
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} // namespace MIGRAPHX_INLINE_NS
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} // namespace migraphx
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