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/*
* Copyright (c) 2017-2022 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* 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 "arm_compute/runtime/NEON/functions/NEGEMM.h"
#include "arm_compute/core/ITensorPack.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/MemoryGroup.h"
#include "arm_compute/runtime/Tensor.h"
#include "src/core/CPP/Validate.h"
#include "src/core/helpers/MemoryHelpers.h"
#include "src/cpu/operators/CpuGemm.h"
using namespace arm_compute::experimental;
namespace arm_compute
{
struct NEGEMM::Impl
{
MemoryGroup memory_group{};
IWeightsManager *weights_manager{ nullptr };
std::unique_ptr<cpu::CpuGemm> op{ nullptr };
const ITensor *original_b{ nullptr };
bool is_prepared{ false };
ITensorPack run_pack{};
ITensorPack prep_pack{};
WorkspaceData<Tensor> workspace{};
experimental::MemoryRequirements aux_mem_req{};
};
NEGEMM::NEGEMM(std::shared_ptr<IMemoryManager> memory_manager, IWeightsManager *weights_manager)
: _impl(std::make_unique<Impl>())
{
_impl->memory_group = MemoryGroup(std::move(memory_manager));
_impl->weights_manager = weights_manager;
}
NEGEMM::~NEGEMM() = default;
void NEGEMM::configure(const ITensor *a, const ITensor *b, const ITensor *c, ITensor *d, float alpha, float beta, const GEMMInfo &gemm_info)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(a, b, d);
ARM_COMPUTE_ERROR_THROW_ON(cpu::CpuGemm::validate(a->info(), b->info(), (c != nullptr) ? c->info() : nullptr, d->info(), alpha, beta, gemm_info));
// Check if we need to reshape the matrix B only on the first run
_impl->is_prepared = false;
_impl->original_b = b;
_impl->op = std::make_unique<cpu::CpuGemm>();
_impl->op->configure(a->info(), b->info(), (c != nullptr) ? c->info() : nullptr, d->info(), alpha, beta, gemm_info);
_impl->aux_mem_req = _impl->op->workspace();
_impl->run_pack = { { ACL_SRC_0, a }, { ACL_SRC_1, b }, { ACL_SRC_2, c }, { ACL_DST, d } };
_impl->prep_pack = { { ACL_SRC_1, b }, { ACL_SRC_2, c } };
_impl->workspace = manage_workspace<Tensor>(_impl->aux_mem_req, _impl->memory_group, _impl->run_pack, _impl->prep_pack);
}
Status NEGEMM::validate(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *output, float alpha, float beta, const GEMMInfo &gemm_info)
{
return cpu::CpuGemm::validate(a, b, c, output, alpha, beta, gemm_info);
}
Status NEGEMM::has_opt_impl(arm_compute::WeightFormat &expected_weight_format, const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *output,
float alpha, float beta, const GEMMInfo &gemm_info)
{
ARM_COMPUTE_UNUSED(alpha, beta);
return cpu::CpuGemm::has_opt_impl(expected_weight_format, a, b, c, output, gemm_info);
}
void NEGEMM::run()
{
prepare();
MemoryGroupResourceScope scope_mg(_impl->memory_group);
_impl->op->run(_impl->run_pack);
}
void NEGEMM::prepare()
{
if(!_impl->is_prepared)
{
_impl->op->prepare(_impl->prep_pack);
auto has_reshape = std::find_if(_impl->aux_mem_req.begin(),
_impl->aux_mem_req.end(),
[](const MemoryInfo & m) -> bool { return m.lifetime == MemoryLifetime::Persistent; });
if(has_reshape != std::end(_impl->aux_mem_req))
{
_impl->original_b->mark_as_unused();
}
else
{
_impl->run_pack.add_const_tensor(ACL_SRC_1, _impl->original_b);
}
// Release temporary tensors that are only used in prepare stage
release_temporaries<Tensor>(_impl->aux_mem_req, _impl->workspace);
_impl->is_prepared = true;
}
}
} // namespace arm_compute
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