mirror of
https://github.com/blakeblackshear/frigate.git
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98 lines
3.6 KiB
C++
98 lines
3.6 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/make_op.hpp>
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#include <migraphx/onnx/checks.hpp>
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#include <migraphx/instruction.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_hardmax : op_parser<parse_hardmax>
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{
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std::vector<op_desc> operators() const { return {{"Hardmax", "hardmax"}}; }
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instruction_ref parse(const op_desc& /*opd*/,
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const onnx_parser& parser,
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const onnx_parser::node_info& info,
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std::vector<instruction_ref> args) const
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{
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auto input = args[0];
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auto input_lens = input->get_shape().lens();
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// default axis value is -1 for opset 13
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int64_t axis = -1;
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// axis value is 1 for previous opset versions
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if(parser.opset_version < 13)
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{
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axis = 1;
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}
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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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if(parser.opset_version < 13)
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{
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// input is coerced into a 2D matrix of size NxD
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axis = axis < 0 ? axis + input_lens.size() : axis;
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size_t n = 1;
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for(int i = 0; i < axis; i++)
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{
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n *= input_lens[i];
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}
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size_t d = input->get_shape().elements() / n;
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input = info.add_instruction(make_op("reshape", {{"dims", {n, d}}}), input);
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axis = 1;
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}
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auto input_type = input->get_shape().type();
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auto indices = info.add_instruction(make_op("argmax", {{"axis", axis}}), input);
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auto data = info.add_instruction(
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make_op("multibroadcast", {{"out_lens", input->get_shape().lens()}}),
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info.add_literal(migraphx::literal{migraphx::shape{input_type}, {0}}));
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auto updates = info.add_instruction(
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make_op("multibroadcast", {{"out_lens", indices->get_shape().lens()}}),
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info.add_literal(migraphx::literal{migraphx::shape{input_type}, {1}}));
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auto output =
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info.add_instruction(make_op("scatter_none", {{"axis", axis}}), data, indices, updates);
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if(parser.opset_version < 13)
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{
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output = info.add_instruction(make_op("reshape", {{"dims", input_lens}}), output);
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}
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return output;
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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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