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

74 lines
2.6 KiB
C++

/*
* The MIT License (MIT)
*
* Copyright (c) 2015-2022 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/cpu/pointwise.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace cpu {
struct dnnl_eltwise : dnnl_op<dnnl_eltwise, dnnl::eltwise_forward>
{
std::string algo;
float alpha = 0;
float beta = 0;
template <class Self, class F>
static auto reflect(Self& self, F f)
{
return pack_join(self.reflect_base(self, f),
pack(f(self.algo, "algo"), f(self.alpha, "alpha"), f(self.beta, "beta")));
}
std::string group() const { return this->name() + "::" + algo; }
std::string name() const { return "dnnl::eltwise"; }
shape compute_shape(std::vector<shape> inputs) const
{
// Compensate for allocation
inputs.pop_back();
check_shapes{this->trim_post_op_inputs(inputs), *this}.has(1).packed();
auto s = inputs.at(0);
auto r = s;
if(not s.packed())
r = shape{s.type(), s.lens()};
// Call to get_primitive to make sure an algo is available
this->get_primitive(this->to_memory_desc(r, inputs));
return r;
}
dnnl::eltwise_forward::desc get_desc(const std::unordered_map<int, dnnl::memory::desc>& m) const
{
return {dnnl::prop_kind::forward_inference,
to_dnnl_algo(algo),
m.at(MIGRAPHX_DNNL_PREFIX(ARG_SRC_0)),
alpha,
beta};
}
};
} // namespace cpu
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx