mirror of
https://github.com/blakeblackshear/frigate.git
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115 lines
4.1 KiB
C++
115 lines
4.1 KiB
C++
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/*
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* The MIT License (MIT)
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*
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* Copyright (c) 2015-2022 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/eliminate_pad.hpp>
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#include <migraphx/program.hpp>
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#include <migraphx/instruction.hpp>
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#include <migraphx/op/convolution.hpp>
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#include <migraphx/op/im2col.hpp>
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#include <migraphx/op/pooling.hpp>
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#include <migraphx/op/pad.hpp>
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#include <migraphx/make_op.hpp>
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#include <migraphx/iterator_for.hpp>
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#include <migraphx/stringutils.hpp>
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namespace migraphx {
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inline namespace MIGRAPHX_INLINE_NS {
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static void update_op(const instruction_ref& input, const instruction_ref& ins, module& m)
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{
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auto pad_op = any_cast<op::pad>(input->get_operator());
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auto kdims = input->get_shape().lens().size() - 2;
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auto kdims_it = pad_op.pads.begin() + 2;
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std::vector<size_t> pads_l(kdims_it, kdims_it + kdims);
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std::vector<size_t> pads_r(kdims_it + kdims + 2, pad_op.pads.end());
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auto op = ins->get_operator();
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std::vector<size_t> padding(kdims * 2, 0);
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std::transform(
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pads_l.begin(), pads_l.end(), padding.begin(), padding.begin(), std::plus<size_t>());
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std::transform(pads_r.begin(),
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pads_r.end(),
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padding.begin() + kdims,
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padding.begin() + kdims,
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std::plus<size_t>());
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op.from_value({{"padding", padding}});
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std::vector<instruction_ref> new_inputs{ins->inputs()};
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new_inputs.front() = input->inputs().front();
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m.replace_instruction(ins, op, new_inputs);
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}
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static void update_pooling(const instruction_ref& input, const instruction_ref& ins, module& m)
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{
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auto op = any_cast<op::pooling>(ins->get_operator());
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if(op.mode == op::pooling_mode::average)
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{
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return;
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}
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auto pad_op = any_cast<op::pad>(input->get_operator());
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auto kdims = input->get_shape().lens().size() - 2;
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auto kdims_it = pad_op.pads.begin() + 2;
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std::vector<size_t> pads_l(kdims_it, kdims_it + kdims);
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std::vector<size_t> pads_r(kdims_it + kdims + 2, pad_op.pads.end());
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std::transform(
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pads_l.begin(), pads_l.end(), op.padding.begin(), op.padding.begin(), std::plus<size_t>());
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std::transform(pads_r.begin(),
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pads_r.end(),
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op.padding.begin() + kdims,
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op.padding.begin() + kdims,
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std::plus<size_t>());
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std::vector<instruction_ref> new_inputs{ins->inputs()};
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new_inputs.front() = input->inputs().front();
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m.replace_instruction(ins, op, new_inputs);
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}
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void eliminate_pad::apply(module& m) const
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{
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for(auto ins : iterator_for(m))
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{
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const std::string& op_name = ins->name();
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if(op_name != "convolution" and op_name != "im2col" and op_name != "pooling")
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continue;
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auto input = ins->inputs().front();
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if(input->name() != "pad")
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continue;
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if(op_name == "convolution" or op_name == "im2col")
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update_op(input, ins, m);
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else if(op_name == "pooling")
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update_pooling(input, ins, m);
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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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