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Flatten subprojects into a single base monorepo
2026-09-02 16:34:47 -07:00

210 lines
9.5 KiB
C++

/*******************************************************************************
*
* MIT License
*
* Copyright (c) 2022 Advanced Micro Devices, Inc.
*
* 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.
*
*******************************************************************************/
#ifndef GUARD_GPU_CONV_HPP
#define GUARD_GPU_CONV_HPP
#include <miopen/env.hpp>
#include <miopen/convolution.hpp>
#include <miopen/conv/wrw_invoke_params.hpp>
#include "get_handle.hpp"
#include "tensor_holder.hpp"
namespace env = miopen::env;
namespace miopen {
namespace debug {
MIOPEN_EXPORT extern bool
AlwaysEnableConvDirectNaive; // NOLINT (cppcoreguidelines-avoid-non-const-global-variables)
MIOPEN_EXPORT extern bool
LoggingQuiet; // NOLINT (cppcoreguidelines-avoid-non-const-global-variables)
} // namespace debug
} // namespace miopen
MIOPEN_DECLARE_ENV_VAR_BOOL(MIOPEN_DEBUG_TEST_DISABLE_GPU_REF)
struct AutoPrepareForGpuReference
{
AutoPrepareForGpuReference()
{
quiet_prev = miopen::debug::LoggingQuiet;
naive_prev = miopen::debug::AlwaysEnableConvDirectNaive;
miopen::debug::AlwaysEnableConvDirectNaive = true;
miopen::debug::LoggingQuiet = true;
}
AutoPrepareForGpuReference(const AutoPrepareForGpuReference&) = delete;
AutoPrepareForGpuReference(AutoPrepareForGpuReference&&) = delete;
AutoPrepareForGpuReference& operator=(const AutoPrepareForGpuReference&) = delete;
AutoPrepareForGpuReference& operator=(AutoPrepareForGpuReference&&) = delete;
~AutoPrepareForGpuReference()
{
miopen::debug::LoggingQuiet = quiet_prev;
miopen::debug::AlwaysEnableConvDirectNaive = naive_prev;
}
private:
bool naive_prev;
bool quiet_prev;
};
template <typename Tin, typename Twei, typename Tout>
bool gpu_ref_convolution_fwd(const tensor<Tin>& input,
const tensor<Twei>& weights,
tensor<Tout>& rout,
miopen::ConvolutionDescriptor filter,
const miopen::Scalar& alpha = miopen::Scalar(1.0),
const miopen::Scalar& beta = miopen::Scalar(0.0))
{
bool gpu_ref_used = false;
if(!env::enabled(MIOPEN_DEBUG_TEST_DISABLE_GPU_REF))
{
const AutoPrepareForGpuReference guard;
auto&& handle = get_handle();
auto in_dev = handle.Write(input.data);
auto wei_dev = handle.Write(weights.data);
auto out_dev = handle.Write(rout.data);
const auto naive_conv_id = miopen::solver::Id{"ConvDirectNaiveConvFwd"};
const auto naive_solver = naive_conv_id.GetSolver();
const auto tensors = miopen::ConvFwdTensors{
input.desc, in_dev.get(), weights.desc, wei_dev.get(), rout.desc, out_dev.get()};
const auto problem = miopen::conv::ProblemDescription{input.desc,
weights.desc,
rout.desc,
filter,
miopen::conv::Direction::Forward,
0,
alpha,
beta};
auto ctx = miopen::ExecutionContext{};
ctx.SetStream(&handle);
if(naive_solver.IsApplicable(ctx, problem))
{
gpu_ref_used = true;
const auto invoke_ctx = miopen::conv::DataInvokeParams{
tensors, nullptr, 0, filter.attribute.gfx90aFp16alt.GetFwd(), alpha, beta};
const auto invoker = miopen::LoadOrPrepareInvoker(ctx, problem, naive_conv_id.Value());
invoker(handle, invoke_ctx);
rout.data = handle.Read<Tout>(out_dev, rout.data.size());
}
}
return gpu_ref_used;
}
template <typename Tin, typename Twei, typename Tout>
bool gpu_ref_convolution_bwd(tensor<Tin>& input,
const tensor<Twei>& weights,
const tensor<Tout> output,
miopen::ConvolutionDescriptor filter,
const miopen::Scalar& alpha = miopen::Scalar(1.0),
const miopen::Scalar& beta = miopen::Scalar(0.0))
{
bool gpu_ref_used = false;
if(!env::enabled(MIOPEN_DEBUG_TEST_DISABLE_GPU_REF))
{
const AutoPrepareForGpuReference guard;
auto&& handle = get_handle();
auto in_dev = handle.Write(input.data);
auto wei_dev = handle.Write(weights.data);
auto out_dev = handle.Write(output.data);
const auto naive_conv_id = miopen::solver::Id{"ConvDirectNaiveConvBwd"};
const auto naive_solver = naive_conv_id.GetSolver();
const auto tensors = miopen::ConvBwdTensors{
output.desc, out_dev.get(), weights.desc, wei_dev.get(), input.desc, in_dev.get()};
const auto problem = miopen::conv::ProblemDescription{output.desc,
weights.desc,
input.desc,
filter,
miopen::conv::Direction::BackwardData,
0,
alpha,
beta};
auto ctx = miopen::ExecutionContext{};
ctx.SetStream(&handle);
if(naive_solver.IsApplicable(ctx, problem))
{
gpu_ref_used = true;
const auto invoke_ctx = miopen::conv::DataInvokeParams{
tensors, nullptr, 0, filter.attribute.gfx90aFp16alt.GetBwd(), alpha, beta};
const auto invoker = miopen::LoadOrPrepareInvoker(ctx, problem, naive_conv_id.Value());
invoker(handle, invoke_ctx);
input.data = handle.Read<Tin>(in_dev, input.data.size());
}
}
return gpu_ref_used;
}
template <typename Tin, typename Twei, typename Tout>
bool gpu_ref_convolution_wrw(const tensor<Tin>& input,
tensor<Twei>& weights,
const tensor<Tout> output,
miopen::ConvolutionDescriptor filter,
const miopen::Scalar& alpha = miopen::Scalar(1.0),
const miopen::Scalar& beta = miopen::Scalar(0.0))
{
bool gpu_ref_used = false;
if(!env::enabled(MIOPEN_DEBUG_TEST_DISABLE_GPU_REF))
{
const AutoPrepareForGpuReference guard;
auto&& handle = get_handle();
auto in_dev = handle.Write(input.data);
auto wei_dev = handle.Write(weights.data);
auto out_dev = handle.Write(output.data);
const auto naive_conv_id = miopen::solver::Id{"ConvDirectNaiveConvWrw"};
const auto naive_solver = naive_conv_id.GetSolver();
const auto tensors = miopen::ConvWrwTensors{
output.desc, out_dev.get(), input.desc, in_dev.get(), weights.desc, wei_dev.get()};
const auto problem =
miopen::conv::ProblemDescription{output.desc,
weights.desc,
input.desc,
filter,
miopen::conv::Direction::BackwardWeights,
0,
alpha,
beta};
auto ctx = miopen::ExecutionContext{};
ctx.SetStream(&handle);
if(naive_solver.IsApplicable(ctx, problem))
{
gpu_ref_used = true;
const auto invoke_ctx = miopen::conv::WrWInvokeParams{
tensors, nullptr, 0, filter.attribute.gfx90aFp16alt.GetWrW(), alpha, beta};
const auto invoker = miopen::LoadOrPrepareInvoker(ctx, problem, naive_conv_id.Value());
invoker(handle, invoke_ctx);
weights.data = handle.Read<Twei>(wei_dev, weights.data.size());
}
}
return gpu_ref_used;
}
#endif // GUARD_GPU_CONV_HPP