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

105 lines
3.7 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/gpu/compiler.hpp>
#include <migraphx/gpu/context.hpp>
#include <migraphx/gpu/compile_hip_code_object.hpp>
#include <migraphx/gpu/compile_hip.hpp>
#include <migraphx/gpu/compile_gen.hpp>
#include <migraphx/reduce_dims.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace gpu {
MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_USE_FAST_SOFTMAX)
using namespace migraphx::gpu::gen; // NOLINT
static const char* const softmax_kernel = R"__migraphx__(
#include <migraphx/kernels/index.hpp>
#include <migraphx/kernels/softmax.hpp>
#include <migraphx/kernels/vectorize.hpp>
#include <args.hpp>
namespace migraphx {
extern "C" {
MIGRAPHX_GLOBAL void softmax_kernel(void* input_p, void* output_p)
{
transform_args(make_tensors(), ${transformers})(input_p, output_p)([](auto input, auto output) {
softmax<${axis}>(input, output);
});
}
}
} // namespace migraphx
)__migraphx__";
struct softmax_compiler : compiler<softmax_compiler>
{
std::vector<std::string> names() const { return {"softmax"}; }
operation compile_op(context& ctx, const std::vector<shape>& inputs, const value& v) const
{
// TODO: Use reduce_dims
auto axis = v.at("axis").to<int64_t>();
auto faxis = find_fast_axis({inputs.front()});
vectorize vec{};
// Vectorize if the axis is a reduction axis
if(faxis == axis)
{
vec = vectorize::elements(ctx, faxis, inputs);
}
auto relements = inputs[0].lens()[axis] / vec.size;
auto nelements = (inputs.back().elements() / inputs[0].lens()[axis]);
auto block_size = compute_block_size(ctx, relements, 256);
hip_compile_options options;
options.set_launch_params(
v, compute_global_for(ctx, nelements * block_size, 256), block_size);
options.output = inputs.back();
options.inputs = inputs;
options.kernel_name = "softmax_kernel";
if(enabled(MIGRAPHX_USE_FAST_SOFTMAX{}))
options.emplace_param("-DMIGRAPHX_USE_FAST_SOFTMAX");
auto src = interpolate_string(
softmax_kernel,
{{"transformers", make_transformer_args(vec)}, {"axis", to_string(axis)}});
return compile_hip_code_object(ctx, src, options);
}
compiler_replace compile(context& ctx, instruction_ref ins, const operation& op) const
{
return compile_op(ctx, to_shapes(ins->inputs()), op.to_value());
}
};
} // namespace gpu
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx