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/*
* Copyright (c) 2016-2022 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 "src/cpu/kernels/CpuGemmMatrixAdditionKernel.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Validate.h"
#include "src/core/common/Registrars.h"
#include "src/core/CPP/Validate.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
#include "src/core/NEON/NEFixedPoint.h"
#include "src/cpu/kernels/gemm_matrix_add/list.h"
namespace arm_compute
{
namespace cpu
{
namespace kernels
{
namespace
{
static const std::vector<CpuGemmMatrixAdditionKernel::GemmMatrixAddKernel> available_kernels = {
{"neon_fp32_gemm_matrix_add", [](const DataTypeISASelectorData &data) { return (data.dt == DataType::F32); },
REGISTER_FP32_NEON(neon_fp32_gemm_matrix_add)},
{"neon_fp16_gemm_matrix_add",
[](const DataTypeISASelectorData &data) { return (data.dt == DataType::F16) && data.isa.fp16; },
REGISTER_FP16_NEON(neon_fp16_gemm_matrix_add)},
};
} // namespace
void CpuGemmMatrixAdditionKernel::configure(const ITensorInfo *src, ITensorInfo *dst, float beta)
{
ARM_COMPUTE_UNUSED(dst);
ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
// Perform validation step
ARM_COMPUTE_ERROR_THROW_ON(CpuGemmMatrixAdditionKernel::validate(src, dst, beta));
_beta = beta;
const auto uk = CpuGemmMatrixAdditionKernel::get_implementation(
DataTypeISASelectorData{src->data_type(), CPUInfo::get().get_isa()});
ARM_COMPUTE_ERROR_ON_NULLPTR(uk);
_func = uk->ukernel;
// Configure kernel window
Window win = calculate_max_window(*src, Steps());
ICPPKernel::configure(win);
}
Status CpuGemmMatrixAdditionKernel::validate(const ITensorInfo *src, const ITensorInfo *dst, float beta)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst);
ARM_COMPUTE_UNUSED(beta);
ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(src);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::F16, DataType::F32);
if (dst->total_size() > 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(src, dst);
}
return Status{};
}
void CpuGemmMatrixAdditionKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
ARM_COMPUTE_ERROR_ON(tensors.empty());
const ITensor *src = tensors.get_const_tensor(TensorType::ACL_SRC);
ITensor *dst = tensors.get_tensor(TensorType::ACL_DST);
if (_beta != 0.0f)
{
(*_func)(src, dst, window, _beta);
}
}
const char *CpuGemmMatrixAdditionKernel::name() const
{
return "CpuGemmMatrixAdditionKernel";
}
const std::vector<CpuGemmMatrixAdditionKernel::GemmMatrixAddKernel> &
CpuGemmMatrixAdditionKernel::get_available_kernels()
{
return available_kernels;
}
} // namespace kernels
} // namespace cpu
} // namespace arm_compute
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