frigate/docker/rocm/migraphx/onnx/parse_if.cpp
WhiteWolf84 7eefb89bf6 upload
2025-02-03 22:01:20 +01:00

114 lines
4.2 KiB
C++

/*
* The MIT License (MIT)
*
* Copyright (c) 2015-2023 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 <migraphx/instruction_ref.hpp>
#include <migraphx/onnx/op_parser.hpp>
#include <migraphx/onnx/onnx_parser.hpp>
#include <migraphx/onnx/checks.hpp>
#include <migraphx/ranges.hpp>
#include <migraphx/instruction.hpp>
#include <migraphx/make_op.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace onnx {
struct parse_if : op_parser<parse_if>
{
std::vector<op_desc> operators() const { return {{"If"}}; }
std::vector<instruction_ref> parse(const op_desc& /*opd*/,
onnx_parser& parser,
const onnx_parser::node_info& info,
std::vector<instruction_ref> args) const
{
const auto& then_graph = info.attributes.at("then_branch").g();
const auto& else_graph = info.attributes.at("else_branch").g();
if(args.front()->get_shape().elements() != 1)
{
MIGRAPHX_THROW("PARSE_IF: " + info.name +
" condition input can have only one element!");
}
// Fold instruction if condition is constant thus can be evaled
// prior to inference
if(args.front()->can_eval())
{
auto cond_arg = args.front()->eval();
auto* mod = info.mod;
// then branch
if(cond_arg.at<bool>())
{
return parser.parse_graph(mod, then_graph, true);
}
// else branch
else
{
return parser.parse_graph(mod, else_graph, true);
}
}
std::string then_name = info.name + "_if";
module_ref then_mdl = parser.prog.create_module(then_name);
std::string else_name = info.name + "_else";
module_ref else_mdl = parser.prog.create_module(else_name);
// parse the then sub_graph
(void)parser.parse_graph(then_mdl, then_graph);
// parse_the else sub_graph
(void)parser.parse_graph(else_mdl, else_graph);
auto then_out_shapes = then_mdl->get_output_shapes();
auto else_out_shapes = else_mdl->get_output_shapes();
if(not std::equal(then_out_shapes.begin(),
then_out_shapes.end(),
else_out_shapes.begin(),
else_out_shapes.end()))
{
MIGRAPHX_THROW("PARSE_IF: " + info.name +
" then and else sub_grahps must have same output shapes!");
}
auto if_ret = info.add_instruction(make_op("if"), args, {then_mdl, else_mdl});
auto out_s = if_ret->get_shape();
assert(out_s.type() == shape::tuple_type);
const auto& vec_shapes = out_s.sub_shapes();
std::vector<instruction_ref> out_inss;
for(std::size_t i = 0; i < vec_shapes.size(); ++i)
{
auto ret = info.add_instruction(make_op("get_tuple_elem", {{"index", i}}), if_ret);
out_inss.push_back(ret);
}
return out_inss;
}
};
} // namespace onnx
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx