/* * Copyright (c) 2016-2020 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_NEPIXELWISEMULTIPLICATIONKERNEL_H #define ARM_COMPUTE_NEPIXELWISEMULTIPLICATIONKERNEL_H #include "arm_compute/core/Types.h" #include "src/core/NEON/INEKernel.h" namespace arm_compute { class ITensor; /** Interface for the kernel to perform addition between two tensors */ class NEPixelWiseMultiplicationKernel : public INEKernel { public: const char *name() const override { return "NEPixelWiseMultiplicationKernel"; } /** Default constructor */ NEPixelWiseMultiplicationKernel(); /** Prevent instances of this class from being copied (As this class contains pointers) */ NEPixelWiseMultiplicationKernel(const NEPixelWiseMultiplicationKernel &) = delete; /** Prevent instances of this class from being copied (As this class contains pointers) */ NEPixelWiseMultiplicationKernel &operator=(const NEPixelWiseMultiplicationKernel &) = delete; /** Allow instances of this class to be moved */ NEPixelWiseMultiplicationKernel(NEPixelWiseMultiplicationKernel &&) = default; /** Allow instances of this class to be moved */ NEPixelWiseMultiplicationKernel &operator=(NEPixelWiseMultiplicationKernel &&) = default; /** Default destructor */ ~NEPixelWiseMultiplicationKernel() = default; /** Initialise the kernel's input, output and border mode. * * Valid configurations (Input1,Input2) -> Output : * * Support: Broadcast? Scale=1/255? * - (U8,U8) -> U8, S16 N Y * - (U8,S16) -> S16 N Y * - (S16,U8) -> S16 N Y * - (S16,S16) -> S16 N Y * - (S32,S32) -> S32 Y N * - (F16,F16) -> F16 N Y * - (F32,F32) -> F32 Y Y * - (QASYMM8,QASYMM8) -> QASYMM8 Y Y * - (QASYMM8_SIGNED,QASYMM8_SIGNED) -> QASYMM8_SIGNED Y Y * - (QSYMM16,QSYMM16) -> QSYMM16, S32 N Y * * @note For @p scale equal to 1/255 only round to nearest even (implemented as round half up) is supported. * For all other scale values only round to zero (implemented as round towards minus infinity) is supported. * * @param[in] input1 First input tensor. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/S32/QSYMM16/F16/F32 * @param[in] input2 Second input tensor. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/S32/QSYMM16/F16/F32 * @param[out] output Output tensor. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/S32/QSYMM16/F16/F32 * @param[in] scale Scale to apply after multiplication. * Scale must be positive and its value must be either 1/255 or 1/2^n where n is between 0 and 15. * If both @p input1, @p input2 and @p output are of datatype S32, scale cannot be 1/255 * @param[in] overflow_policy Overflow policy. ConvertPolicy cannot be WRAP if any of the inputs is of quantized datatype * @param[in] rounding_policy Rounding policy. */ void configure(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, float scale, ConvertPolicy overflow_policy, RoundingPolicy rounding_policy); /** Static function to check if given info will lead to a valid configuration of @ref NEPixelWiseMultiplicationKernel * * Valid configurations (Input1,Input2) -> Output : * Support: Broadcast? Scale=1/255? * - (U8,U8) -> U8, S16 N Y * - (U8,S16) -> S16 N Y * - (S16,U8) -> S16 N Y * - (S16,S16) -> S16 N Y * - (S32,S32) -> S32 Y N * - (F16,F16) -> F16 N Y * - (F32,F32) -> F32 Y Y * - (QASYMM8,QASYMM8) -> QASYMM8 Y Y * - (QASYMM8_SIGNED,QASYMM8_SIGNED) -> QASYMM8_SIGNED Y Y * - (QSYMM16,QSYMM16) -> QSYMM16, S32 N Y * * @note For @p scale equal to 1/255 only round to nearest even (implemented as round half up) is supported. * For all other scale values only round to zero (implemented as round towards minus infinity) is supported. * * @param[in] input1 First input tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/S32/QSYMM16/F16/F32 * @param[in] input2 Second input tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/S32/QSYMM16/F16/F32 * @param[in] output Output tensor info. Data types supported: U8/QASYMM8/QASYMM8_SIGNED/S16/S32/QSYMM16/F16/F32 * @param[in] scale Scale to apply after multiplication. * Scale must be positive and its value must be either 1/255 or 1/2^n where n is between 0 and 15. * If both @p input1, @p input2 and @p output are of datatype S32, scale cannot be 1/255 * @param[in] overflow_policy Overflow policy. ConvertPolicy cannot be WRAP if any of the inputs is of quantized datatype * @param[in] rounding_policy Rounding policy. * * @return a status */ static Status validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float scale, ConvertPolicy overflow_policy, RoundingPolicy rounding_policy); // Inherited methods overridden void run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) override; private: /** Common signature for all the specialised multiplication functions with integer scaling factor * * @param[in] in1 Input1 tensor object. * @param[in] in2 Input2 tensor object. * @param[out] out Output tensor object. * @param[in] window Region on which to execute the kernel * @param[in] scale Integer scale factor. */ using MulFunctionInt = void(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, int scale); /** Common signature for all the specialised multiplication functions with float scaling factor * * @param[in] in1 Input1 tensor object. * @param[in] in2 Input2 tensor object. * @param[out] out Output tensor object. * @param[in] window Region on which to execute the kernel * @param[in] scale Float scale factor. */ using MulFunctionFloat = void(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, float scale); /** Common signature for all the specialised QASYMM8 multiplication functions with float scaling factor * * @param[in] in1 Input1 tensor object. * @param[in] in2 Input2 tensor object. * @param[out] out Output tensor object. * @param[in] window Region on which to execute the kernel * @param[in] scale Float scale factor. * */ using MulFunctionQuantized = void(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, float scale); MulFunctionFloat *_func_float; MulFunctionInt *_func_int; MulFunctionQuantized *_func_quantized; private: float _scale; int _scale_exponent; }; /** Interface for the complex pixelwise multiplication kernel. */ class NEComplexPixelWiseMultiplicationKernel : public INEKernel { public: const char *name() const override { return "NEComplexPixelWiseMultiplicationKernel"; } /** Initialise the kernel's input, output and border mode. * * @param[in] input1 An input tensor. Data types supported: F32. Number of channels supported: 2 (complex tensor). * @param[in] input2 An input tensor. Data types supported: same as @p input1. Number of channels supported: same as @p input1. * @param[out] output The output tensor, Data types supported: same as @p input1. Number of channels supported: same as @p input1. */ void configure(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output); /** Static function to check if given info will lead to a valid configuration of @ref NEComplexPixelWiseMultiplicationKernel * * @param[in] input1 An input tensor info. Data types supported: F32. Number of channels supported: 2 (complex tensor). * @param[in] input2 An input tensor info. Data types supported: same as @p input1. Number of channels supported: same as @p input1. * @param[in] output The output tensor info. Data types supported: same as @p input1. Number of channels supported: same as @p input1. * * @return a status */ static Status validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output); // Inherited methods overridden: void run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) override; }; } // namespace arm_compute #endif /*ARM_COMPUTE_NEPIXELWISEMULTIPLICATIONKERNEL_H */