mirror of
https://github.com/blakeblackshear/frigate.git
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104 lines
4.1 KiB
C++
104 lines
4.1 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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#ifndef MIGRAPHX_GUARD_RTGLIB_CONVOLUTION_HPP
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#define MIGRAPHX_GUARD_RTGLIB_CONVOLUTION_HPP
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#include <migraphx/config.hpp>
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#include <migraphx/dfor.hpp>
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#include <migraphx/par_for.hpp>
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#include <migraphx/shape_for_each.hpp>
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#include <migraphx/tensor_view.hpp>
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#include <vector>
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namespace migraphx {
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inline namespace MIGRAPHX_INLINE_NS {
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template <class Output, class T, class Padding, class Stride, class Dilation>
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void convolution(
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Output output, T input, T weights, Padding padding, Stride stride, Dilation dilation, int group)
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{
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auto output_shape = output.get_shape();
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auto in_lens = input.get_shape().lens();
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auto wei_lens = weights.get_shape().lens();
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auto wei_n = wei_lens[0];
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auto wei_c = wei_lens[1];
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std::vector<std::size_t> win_size(wei_lens.begin() + 1, wei_lens.end());
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par_for(output_shape.elements(), [&](auto i) {
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auto idx_o = output_shape.multi(i);
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auto w = idx_o[1];
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auto n_dim = idx_o.size();
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std::vector<std::ptrdiff_t> win_start;
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for(std::size_t dim = 2; dim < n_dim; ++dim)
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{
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auto d_2 = dim - 2;
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win_start.push_back(std::ptrdiff_t(idx_o[dim] * stride[d_2]) -
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std::ptrdiff_t(padding[d_2]));
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}
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const auto group_id = w / (wei_n / group);
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shape win_shape{output_shape.type(), win_size};
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double acc = 0.0;
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shape_for_each(win_shape, [&](const auto& idx_win) {
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auto k = idx_win[0];
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const auto in_ch = group_id * wei_c + k;
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std::vector<std::ptrdiff_t> idx(idx_o.begin(), idx_o.end());
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idx[1] = in_ch;
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std::vector<std::ptrdiff_t> idx_dil(idx_win.size() - 1);
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std::transform(idx_win.cbegin() + 1,
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idx_win.cend(),
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dilation.cbegin(),
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idx_dil.begin(),
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[](std::ptrdiff_t ii, std::ptrdiff_t d) { return d * ii; });
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std::transform(idx_dil.begin(),
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idx_dil.end(),
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win_start.begin(),
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idx.begin() + 2,
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[](std::ptrdiff_t ii, std::ptrdiff_t jj) { return ii + jj; });
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std::vector<std::ptrdiff_t> idx_wei(idx_o.size());
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idx_wei[0] = w;
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std::copy(idx_win.begin(), idx_win.end(), idx_wei.begin() + 1);
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if(std::all_of(idx.begin() + 2, idx.end(), [&](auto ii) { return ii >= 0; }) and
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std::equal(idx.begin(),
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idx.end(),
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in_lens.begin(),
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in_lens.end(),
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std::less<std::ptrdiff_t>{}))
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{
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acc += input(idx.begin(), idx.end()) * weights(idx_wei.begin(), idx_wei.end());
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}
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});
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output[i] = acc;
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});
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}
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} // namespace MIGRAPHX_INLINE_NS
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} // namespace migraphx
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#endif
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