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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_NEGEMMASSEMBLYDISPATCH_H__
#define __ARM_COMPUTE_NEGEMMASSEMBLYDISPATCH_H__
#include "arm_compute/core/NEON/kernels/assembly/NEGEMMAssemblyWrapperKernel.h"
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/runtime/IMemoryManager.h"
#include "arm_compute/runtime/MemoryGroup.h"
#include "arm_compute/runtime/Tensor.h"
#include "arm_compute/core/NEON/kernels/assembly/arm_gemm.hpp"
namespace arm_compute
{
/** Assembly kernel glue */
template <typename TypeInput, typename TypeOutput>
class NEGEMMAssemblyDispatch : public IFunction
{
public:
/** Default constructor */
NEGEMMAssemblyDispatch(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
/** Prevent instances of this class from being copy constructed */
NEGEMMAssemblyDispatch(const NEGEMMAssemblyDispatch<TypeInput, TypeOutput> &) = delete;
/** Prevent instances of this class from being copied */
NEGEMMAssemblyDispatch<TypeInput, TypeOutput> &operator=(const NEGEMMAssemblyDispatch<TypeInput, TypeOutput> &) = delete;
NEGEMMAssemblyDispatch(NEGEMMAssemblyDispatch<TypeInput, TypeOutput> &&) = default;
NEGEMMAssemblyDispatch<TypeInput, TypeOutput> &operator=(NEGEMMAssemblyDispatch<TypeInput, TypeOutput> &&) = default;
~NEGEMMAssemblyDispatch() = default;
private:
/** ACL Function */
std::unique_ptr<IFunction> _function;
/** If supported create the ACL function corresponding to the GemmMethod provided to process the other passed parameters
*
* @param[in] method GemmMethod to use to perform the matrix multiplication.
* @param[in] a Input tensor (Matrix A).
* @param[in] b Input tensor (Matrix B).
* @param[out] d 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 D matrix before adding product.
* @param[in] pretransposed_hint Can the B tensor can be pretransposed (ie shared across invocations)?
*
* @return True if the method is supported and the function was successfully created, false otherwise.
*/
bool create_function(arm_gemm::GemmMethod method, const ITensor *a, const ITensor *b, ITensor *d, float alpha, float beta, bool pretranspose_hint);
//Fallback: use arm_gemm's AssemblyGemm:
class Fallback
{
#ifndef DOXYGEN_SKIP_THIS
public:
/** Configures the arrays pointers and strides in the assembly kernel and executes the assembly kernel.
* The call to set_arrays is needed to deal with the input sizes containing batches (dims > 2)
*/
void run();
void configure(const ITensor *a, const ITensor *b, ITensor *d, arm_gemm::GemmArgs<TypeOutput> &args, MemoryGroup &memory_group);
void prepare();
bool is_configured() const;
#endif /* DOXYGEN_SKIP_THIS */
private:
/** Allocate a workspace tensor.
*
* @param[in] workspace_size Size to allocate.
* @param[in] memory_group Tensor memory group.
* @param[in] alignment Workspace memory alignment.
*/
void allocate_workspace(size_t workspace_size, MemoryGroup *memory_group, size_t alignment);
/** Assembly Gemm kernel */
std::unique_ptr<arm_gemm::GemmCommon<TypeInput, TypeOutput>> _gemm_kernel_asm{ nullptr };
/** Optimised NEON kernel */
std::unique_ptr<INEKernel> _optimised_kernel{ nullptr };
/** Input A */
const ITensor *_a
{
nullptr
};
/** Input B */
const ITensor *_b
{
nullptr
};
/** Output */
ITensor *_d{ nullptr };
/** GEMM workspace */
Tensor _workspace{};
/** Pre-transpose tensor */
Tensor _pretranspose{};
/** Prepared flag */
bool _is_prepared{ false };
} _arm_gemm; /**< Fallback in case ACL doesn't have a function */
MemoryGroup _memory_group; /**< Function memory group */
public:
/** If supported create an ACL function else fallback to the arm_gemm function.
*
* @param[in] a Input tensor (Matrix A)
* @param[in] b Input tensor (Matrix B)
* @param[out] d 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 D matrix before adding product.
* @param[in] pretranspose_hint Can the B tensor can be pretransposed (ie shared across invocations)?
*/
void configure(const ITensor *a, const ITensor *b, ITensor *d, float alpha, float beta, bool pretranspose_hint);
/** Was the function successfully configured ?
*
* @return True if the function is configured and ready to run
*/
bool is_configured() const;
// Inherited methods overridden:
/** Runs a preparation step, usually for pre-transposing matrix b */
void prepare() override;
void run() override;
};
/** Float 32 assembly dispatch kernel */
using NEGEMMAssemblyDispatchF32 = NEGEMMAssemblyDispatch<float, float>;
/** Uint 8 to Uint 32 assembly dispatch kernel */
using NEGEMMAssemblyDispatchU8U32 = NEGEMMAssemblyDispatch<uint8_t, uint32_t>;
/** Int 8 to Int 32 assembly dispatch kernel */
using NEGEMMAssemblyDispatchS8S32 = NEGEMMAssemblyDispatch<int8_t, int32_t>;
} // namespace arm_compute
#endif /* __ARM_COMPUTE_NEGEMMASSEMBLYDISPATCH_H__ */
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