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/*
* Copyright (c) 2018 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.
*/
#ifndef __ARM_COMPUTE_NEGEMMINTERLEAVEDWRAPPER_H__
#define __ARM_COMPUTE_NEGEMMINTERLEAVEDWRAPPER_H__
#include "arm_compute/core/NEON/kernels/assembly/Helpers.h"
#include "arm_compute/core/NEON/kernels/assembly/INEGEMMWrapperKernel.h"
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/runtime/IMemoryManager.h"
#include "arm_compute/runtime/IScheduler.h"
#include "arm_compute/runtime/MemoryGroup.h"
#include "arm_compute/runtime/Tensor.h"
#include <memory>
namespace arm_compute
{
class ITensor;
class NEGEMMInterleavedPrepareBWrapperKernel;
class PrepareBWorkload;
class TransformAWorkload;
class MatrixMultiplyWorkload;
class NEGEMMInterleavedTransformAWrapper;
class NEGEMMInterleavedMatrixMultiplyWrapper;
/** Equivalent to arm_gemm::GemmInterleaved but using Compute Library types.
*/
class NEGEMMInterleavedWrapper : public IFunction
{
public:
NEGEMMInterleavedWrapper(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
NEGEMMInterleavedWrapper(const NEGEMMInterleavedWrapper &) = delete;
NEGEMMInterleavedWrapper &operator=(const NEGEMMInterleavedWrapper &) = delete;
/** Initialise the kernel's input and output.
*
* @note The input and output tensor must have the same dimensions
*
* @param[in] a Input tensor (Matrix A)
* @param[in] b Input tensor (Matrix B)
* @param[out] c Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0.
* @param[in] alpha Scalar multiplier to apply to AB matrix product.
* @param[in] beta Scalar multiplier to apply to input C matrix before adding product.
* @param[in] pretranspose_b If true, pretranspose B once during the prepare() stage instead of on the fly every time.
* @param[in] use_dot (Optional) If the input's type is U8/S8/QASYMM8 then use the dot product flavour or the matrix multiply routine. (Must be supported by the hardware).
*/
void configure(const ITensor *a, const ITensor *b, ITensor *c, float alpha, float beta, bool pretranspose_b, bool use_dot = false);
// Inherited methods overridden:
void run() override;
void prepare() override;
private:
MemoryGroup _memory_group;
bool _is_prepared{ false };
bool _pretranspose_b{ false };
Window _block_walker{};
Window _batch_window{};
const ITensor *_a{ nullptr };
const ITensor *_b{ nullptr };
ITensor *_c{ nullptr };
Tensor _transformed_b{};
Tensor _transformed_a{};
Tensor _tmp_c{};
INEGEMMWrapperKernel::Params _params{};
BlockSizes _block_sizes{};
std::unique_ptr<NEGEMMInterleavedPrepareBWrapperKernel> _prepare_b{ nullptr };
std::unique_ptr<NEGEMMInterleavedTransformAWrapper> _transform_a{ nullptr };
std::unique_ptr<NEGEMMInterleavedMatrixMultiplyWrapper> _matrix_multiply{ nullptr };
std::vector<TransformAWorkload> _a_workloads{};
std::vector<PrepareBWorkload> _b_workloads{};
std::vector<MatrixMultiplyWorkload> _mm_workloads{};
std::vector<IScheduler::Workload> _workloads{};
};
} // namespace arm_compute
#endif /* __ARM_COMPUTE_NEGEMMINTERLEAVEDWRAPPER_H__ */
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