frigate/docker/rocm/migraphx/targets/cpu/pooling.cpp
WhiteWolf84 931b31452a upload2
2025-02-03 22:44:02 +01:00

84 lines
3.4 KiB
C++

/*
* The MIT License (MIT)
*
* Copyright (c) 2015-2024 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/config.hpp>
#include <migraphx/register_op.hpp>
#include <migraphx/reflect.hpp>
#include <migraphx/par_for.hpp>
#include <migraphx/context.hpp>
#include <migraphx/cpu/context.hpp>
#include <migraphx/cpu/dnnl.hpp>
#include <migraphx/op/pooling.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace cpu {
struct dnnl_pooling : dnnl_extend_op<dnnl_pooling, dnnl::pooling_v2_forward, op::pooling>
{
std::vector<int> arg_map(int) const { return {MIGRAPHX_DNNL_PREFIX(ARG_SRC)}; }
dnnl::algorithm get_algo() const
{
switch(op.mode)
{
case op::pooling_mode::max: return dnnl::algorithm::pooling_max;
case op::pooling_mode::average:
return op.count_include_pad ? dnnl::algorithm::pooling_avg_include_padding
: dnnl::algorithm::pooling_avg_exclude_padding;
case op::pooling_mode::lpnorm: MIGRAPHX_THROW("Lpnorn pooling mode not supported");
}
MIGRAPHX_THROW("Unknown pooling mode");
}
dnnl::pooling_v2_forward::desc
get_desc(const std::unordered_map<int, dnnl::memory::desc>& m) const
{
auto algo = get_algo();
auto kdims = op.kdims();
std::vector<size_t> padding_l(op.padding.begin(), op.padding.begin() + kdims);
std::vector<size_t> padding_r(op.padding.begin() + kdims, op.padding.end());
// Note: It is not documented, but the default dilation seems to be 0 instead of 1.
// We need to offset dilations with -1.
std::vector<size_t> dilations;
std::transform(op.dilations.cbegin(),
op.dilations.cend(),
std::back_inserter(dilations),
[](size_t d) { return d - 1; });
return {dnnl::prop_kind::forward_inference,
algo,
m.at(MIGRAPHX_DNNL_PREFIX(ARG_SRC)),
m.at(MIGRAPHX_DNNL_PREFIX(ARG_DST)),
to_dnnl_dims(op.stride),
to_dnnl_dims(op.lengths),
to_dnnl_dims(dilations),
to_dnnl_dims(padding_l),
to_dnnl_dims(padding_r)};
}
};
} // namespace cpu
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx