* Copyright (c) 2025 Huawei Technologies Co., Ltd.
* This program is free software, you can redistribute it and/or modify it under the terms and conditions of
* CANN Open Software License Agreement Version 2.0 (the "License").
* Please refer to the License for details. You may not use this file except in compliance with the License.
* THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED,
* INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
* See LICENSE in the root of the software repository for the full text of the License.
*/
* \file kernel_operator_vec_binary_intf.h
* \brief
*/
#ifndef ASCENDC_MODULE_OPERATOR_VEC_BINARY_INTERFACE_H
#define ASCENDC_MODULE_OPERATOR_VEC_BINARY_INTERFACE_H
#include "kernel_macros.h"
#include "kernel_tensor.h"
#include "kernel_struct_binary.h"
#if defined(__NPU_ARCH__) && (__NPU_ARCH__ == 3101 || __NPU_ARCH__ == 5102)
#include "micro_api/kernel_micro_utils.h"
#endif
#if defined(ASCENDC_CPU_DEBUG) && ASCENDC_CPU_DEBUG == 1
#include <cstdint>
#include "stub_def.h"
#endif
#pragma begin_pipe(V)
namespace AscendC {
* Add *
* ************************************************************************************************* */
* @ingroup Add Level 0
* @brief dst = src0 + src1
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] mask[]/mask mask array/count
* @param [in] repeatTime repeat times
* @param [in] repeatParams.dstBlkStride dst block stride
* @param [in] repeatParams.src0BlkStride src0 block stride
* @param [in] repeatParams.src1BlkStride src1 block stride
* @param [in] repeatParams.dstRepStride dst repeat stride
* @param [in] repeatParams.src0RepStride src0 repeat stride
* @param [in] repeatParams.src1RepStride src1 repeat stride
*/
template <typename T, bool isSetMask = true>
__aicore__ inline void Add(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask[], const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <typename T, bool isSetMask = true>
__aicore__ inline void Add(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask, const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
* @ingroup Add Level 2
* @brief dst = src0 + src1
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] count number Number of data involved in calculation
*/
template <typename T>
__aicore__ inline void Add(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, const int32_t& count);
* Sub *
* ************************************************************************************************* */
* @ingroup Sub Level 0
* @brief dst = src0 - src1
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] mask[]/mask mask array/count
* @param [in] repeatTime repeat times
* @param [in] repeatParams.dstBlkStride dst block stride
* @param [in] repeatParams.src0BlkStride src0 block stride
* @param [in] repeatParams.src1BlkStride src1 block stride
* @param [in] repeatParams.dstRepStride dst repeat stride
* @param [in] repeatParams.src0RepStride src0 repeat stride
* @param [in] repeatParams.src1RepStride src1 repeat stride
*/
template <typename T, bool isSetMask = true>
__aicore__ inline void Sub(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask[], const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <typename T, bool isSetMask = true>
__aicore__ inline void Sub(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask, const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
* @ingroup Sub Level 2
* @brief dst = src0 - src1
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] count number Number of data involved in calculation
*/
template <typename T>
__aicore__ inline void Sub(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, const int32_t& count);
* Mul *
* ************************************************************************************************* */
* @ingroup Mul Level 0
* @brief dst = src0 * src1
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] mask[]/mask mask array/count
* @param [in] repeatTime repeat times
* @param [in] repeatParams.dstBlkStride dst block stride
* @param [in] repeatParams.src0BlkStride src0 block stride
* @param [in] repeatParams.src1BlkStride src1 block stride
* @param [in] repeatParams.dstRepStride dst repeat stride
* @param [in] repeatParams.src0RepStride src0 repeat stride
* @param [in] repeatParams.src1RepStride src1 repeat stride
*/
template <typename T, bool isSetMask = true>
__aicore__ inline void Mul(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask[], const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <typename T, bool isSetMask = true>
__aicore__ inline void Mul(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask, const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
* @ingroup Mul Level 2
* @brief dst = src0 * src1
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] count number Number of data involved in calculation
*/
template <typename T>
__aicore__ inline void Mul(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, const int32_t& count);
* Div *
* ************************************************************************************************* */
* @ingroup Div Level 0
* @brief dst = src0 / src1
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] mask[]/mask mask array/count
* @param [in] repeatTime repeat times
* @param [in] repeatParams.dstBlkStride dst block stride
* @param [in] repeatParams.src0BlkStride src0 block stride
* @param [in] repeatParams.src1BlkStride src1 block stride
* @param [in] repeatParams.dstRepStride dst repeat stride
* @param [in] repeatParams.src0RepStride src0 repeat stride
* @param [in] repeatParams.src1RepStride src1 repeat stride
*/
#if (__NPU_ARCH__ == 3101) || (__NPU_ARCH__ == 5102)
template <typename T, bool isSetMask = true, const DivConfig& config = DEFAULT_DIV_CONFIG>
__aicore__ inline void Div(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask[], const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <typename T, bool isSetMask = true, const DivConfig& config = DEFAULT_DIV_CONFIG>
__aicore__ inline void Div(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask, const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
#else
template <typename T, bool isSetMask = true>
__aicore__ inline void Div(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask[], const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <typename T, bool isSetMask = true>
__aicore__ inline void Div(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask, const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
#endif
* @ingroup Div Level 2
* @brief dst = src0 / src1
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] count number Number of data involved in calculation
*/
#if (__NPU_ARCH__ == 3101) || (__NPU_ARCH__ == 5102)
template <typename T, const DivConfig& config = DEFAULT_DIV_CONFIG>
__aicore__ inline void Div(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, const int32_t& count);
#else
template <typename T>
__aicore__ inline void Div(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, const int32_t& count);
#endif
* MulAddDst *
* ************************************************************************************************* */
* @ingroup MulAddDst Level 0
* @brief dst = src0 * src1 + dst
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] mask[]/mask mask array/count
* @param [in] repeatTime repeat times
* @param [in] repeatParams.dstBlkStride dst block stride
* @param [in] repeatParams.src0BlkStride src0 block stride
* @param [in] repeatParams.src1BlkStride src1 block stride
* @param [in] repeatParams.dstRepStride dst repeat stride
* @param [in] repeatParams.src0RepStride src0 repeat stride
* @param [in] repeatParams.src1RepStride src1 repeat stride
*/
template <typename T, typename U, bool isSetMask = true>
__aicore__ inline void MulAddDst(const LocalTensor<T>& dst, const LocalTensor<U>& src0,
const LocalTensor<U>& src1, const uint64_t mask[], const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <typename T, typename U, bool isSetMask = true>
__aicore__ inline void MulAddDst(const LocalTensor<T>& dst, const LocalTensor<U>& src0,
const LocalTensor<U>& src1, uint64_t mask, const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
* @ingroup MulAddDst Level 2
* @brief dst = src0 * src1 + dst
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] count number Number of data involved in calculation
*/
template <typename T, typename U>
__aicore__ inline void MulAddDst(const LocalTensor<T>& dst, const LocalTensor<U>& src0,
const LocalTensor<U>& src1, const int32_t& count);
* Max *
* ************************************************************************************************* */
* @ingroup Max Level 0
* @brief dst = src0 > src1 ? src0 : src1
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] mask[]/mask mask array/count
* @param [in] repeatTime repeat times
* @param [in] repeatParams.dstBlkStride dst block stride
* @param [in] repeatParams.src0BlkStride src0 block stride
* @param [in] repeatParams.src1BlkStride src1 block stride
* @param [in] repeatParams.dstRepStride dst repeat stride
* @param [in] repeatParams.src0RepStride src0 repeat stride
* @param [in] repeatParams.src1RepStride src1 repeat stride
*/
template <typename T, bool isSetMask = true>
__aicore__ inline void Max(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask[], const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <typename T, bool isSetMask = true>
__aicore__ inline void Max(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask, const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
* @ingroup Max Level 2
* @brief dst = src0 > src1 ? src0 : src1
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] count number Number of data involved in calculation
*/
template <typename T>
__aicore__ inline void Max(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, const int32_t& count);
* Min *
* ************************************************************************************************* */
* @ingroup Min Level 0
* @brief dst = src0 > src1 ? src1 : src0
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] mask[]/mask mask array/count
* @param [in] repeatTime repeat times
* @param [in] repeatParams.dstBlkStride dst block stride
* @param [in] repeatParams.src0BlkStride src0 block stride
* @param [in] repeatParams.src1BlkStride src1 block stride
* @param [in] repeatParams.dstRepStride dst repeat stride
* @param [in] repeatParams.src0RepStride src0 repeat stride
* @param [in] repeatParams.src1RepStride src1 repeat stride
*/
template <typename T, bool isSetMask = true>
__aicore__ inline void Min(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask[], const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <typename T, bool isSetMask = true>
__aicore__ inline void Min(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask, const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
* @ingroup Min Level 2
* @brief dst = src0 > src1 ? src1 : src0
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] count number Number of data involved in calculation
*/
template <typename T>
__aicore__ inline void Min(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, const int32_t& count);
* And *
* ************************************************************************************************* */
* @ingroup And Level 0
* @brief dst = src0 & src1
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] mask[]/mask mask array/count
* @param [in] repeatTime repeat times
* @param [in] repeatParams.dstBlkStride dst block stride
* @param [in] repeatParams.src0BlkStride src0 block stride
* @param [in] repeatParams.src1BlkStride src1 block stride
* @param [in] repeatParams.dstRepStride dst repeat stride
* @param [in] repeatParams.src0RepStride src0 repeat stride
* @param [in] repeatParams.src1RepStride src1 repeat stride
*/
template <typename T, bool isSetMask = true>
__aicore__ inline void And(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask[], const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <typename T, bool isSetMask = true>
__aicore__ inline void And(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask, const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
* @ingroup And Level 2
* @brief dst = src0 & src1
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] count number Number of data involved in calculation
*/
template <typename T>
__aicore__ inline void And(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, const int32_t& count);
* Or *
* ************************************************************************************************* */
* @ingroup Or Level 0
* @brief dst = src0 | src1
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] mask[]/mask mask array/count
* @param [in] repeatTime repeat times
* @param [in] repeatParams.dstBlkStride dst block stride
* @param [in] repeatParams.src0BlkStride src0 block stride
* @param [in] repeatParams.src1BlkStride src1 block stride
* @param [in] repeatParams.dstRepStride dst repeat stride
* @param [in] repeatParams.src0RepStride src0 repeat stride
* @param [in] repeatParams.src1RepStride src1 repeat stride
*/
template <typename T, bool isSetMask = true>
__aicore__ inline void Or(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask[], const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <typename T, bool isSetMask = true>
__aicore__ inline void Or(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask, const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
* @ingroup Or Level 2
* @brief dst = src0 | src1
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] count number Number of data involved in calculation
*/
template <typename T>
__aicore__ inline void Or(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, const int32_t& count);
#if (__NPU_ARCH__ == 3101) || (__NPU_ARCH__ == 5102)
* ShiftLeft *
* ************************************************************************************************* */
* @ingroup ShiftLeft Level 2
* @brief dst = src0 << src1
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] count number Number of data involved in calculation
*/
template <typename T, typename U>
__aicore__ inline void ShiftLeft(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<U>& src1, const int32_t& count);
* ShiftRight *
* ************************************************************************************************* */
* @ingroup ShiftRight Level 2
* @brief dst = src0 >> src1
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] count number Number of data involved in calculation
*/
template <typename T, typename U>
__aicore__ inline void ShiftRight(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<U>& src1, const int32_t& count);
#endif
* AddRelu *
* ************************************************************************************************* */
* @ingroup AddRelu Level 0
* @brief dst = Relu(src0 + src1)
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] mask[]/mask mask array/count
* @param [in] repeatTime repeat times
* @param [in] repeatParams.dstBlkStride dst block stride
* @param [in] repeatParams.src0BlkStride src0 block stride
* @param [in] repeatParams.src1BlkStride src1 block stride
* @param [in] repeatParams.dstRepStride dst repeat stride
* @param [in] repeatParams.src0RepStride src0 repeat stride
* @param [in] repeatParams.src1RepStride src1 repeat stride
*/
template <typename T, bool isSetMask = true>
__aicore__ inline void AddRelu(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask[], const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <typename T, bool isSetMask = true>
__aicore__ inline void AddRelu(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask, const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
* @ingroup AddRelu Level 2
* @brief dst = Relu(src0 + src1)
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] count number Number of data involved in calculation
*/
template <typename T>
__aicore__ inline void AddRelu(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, const int32_t& count);
* AddDeqRelu *
* ************************************************************************************************* */
* @ingroup AddDeqRelu Level 0
* @brief dst = DeqRelu(src0 + src1)
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] mask[]/mask mask array/count
* @param [in] repeatTime repeat times
* @param [in] repeatParams.dstBlkStride dst block stride
* @param [in] repeatParams.src0BlkStride src0 block stride
* @param [in] repeatParams.src1BlkStride src1 block stride
* @param [in] repeatParams.dstRepStride dst repeat stride
* @param [in] repeatParams.src0RepStride src0 repeat stride
* @param [in] repeatParams.src1RepStride src1 repeat stride
*/
template <bool isSetMask = true>
__aicore__ inline void AddDeqRelu(const LocalTensor<half>& dst, const LocalTensor<int32_t>& src0,
const LocalTensor<int32_t>& src1, uint64_t mask[], const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <typename T, typename U, bool isSetMask = true>
__aicore__ inline void AddDeqRelu(const LocalTensor<T>& dst, const LocalTensor<U>& src0,
const LocalTensor<U>& src1, uint64_t mask[], const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <bool isSetMask = true>
__aicore__ inline void AddDeqRelu(const LocalTensor<half>& dst, const LocalTensor<int32_t>& src0,
const LocalTensor<int32_t>& src1, uint64_t mask, const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <typename T, typename U, bool isSetMask = true>
__aicore__ inline void AddDeqRelu(const LocalTensor<T>& dst, const LocalTensor<U>& src0,
const LocalTensor<U>& src1, uint64_t mask, const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
* @ingroup AddDeqRelu Level 2
* @brief dst = DeqRelu(src0 + src1)
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] count number Number of data involved in calculation
*/
__aicore__ inline void AddDeqRelu(const LocalTensor<half>& dst, const LocalTensor<int32_t>& src0,
const LocalTensor<int32_t>& src1, const int32_t& count);
template <typename T, typename U>
__aicore__ inline void AddDeqRelu(const LocalTensor<T>& dst, const LocalTensor<U>& src0,
const LocalTensor<U>& src1, const int32_t& count);
* FusedMulAdd *
* ************************************************************************************************* */
* @ingroup FusedMulAdd Level 0
* @brief dst = src0 * dst + src1
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] mask[]/mask mask array/count
* @param [in] repeatTime repeat times
* @param [in] repeatParams.dstBlkStride dst block stride
* @param [in] repeatParams.src0BlkStride src0 block stride
* @param [in] repeatParams.src1BlkStride src1 block stride
* @param [in] repeatParams.dstRepStride dst repeat stride
* @param [in] repeatParams.src0RepStride src0 repeat stride
* @param [in] repeatParams.src1RepStride src1 repeat stride
*/
template <typename T, bool isSetMask = true>
__aicore__ inline void FusedMulAdd(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask[], const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <typename T, bool isSetMask = true>
__aicore__ inline void FusedMulAdd(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask, const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
* @ingroup FusedMulAdd Level 2
* @brief dst = src0 * dst + src1
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] count number Number of data involved in calculation
*/
template <typename T>
__aicore__ inline void FusedMulAdd(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, const int32_t& count);
* MulAddRelu *
* ************************************************************************************************* */
* @ingroup MulAddRelu Level 0
* @brief dst = relu(src0 * dst + src1)
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] mask[]/mask mask array/count
* @param [in] repeatTime repeat times
* @param [in] repeatParams.dstBlkStride dst block stride
* @param [in] repeatParams.src0BlkStride src0 block stride
* @param [in] repeatParams.src1BlkStride src1 block stride
* @param [in] repeatParams.dstRepStride dst repeat stride
* @param [in] repeatParams.src0RepStride src0 repeat stride
* @param [in] repeatParams.src1RepStride src1 repeat stride
*/
template <typename T, bool isSetMask = true>
__aicore__ inline void MulAddRelu(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask[], const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <typename T, bool isSetMask = true>
__aicore__ inline void MulAddRelu(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask, const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <typename T, bool isSetMask = true>
__aicore__ inline void FusedMulAddRelu(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask[], const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <typename T, bool isSetMask = true>
__aicore__ inline void FusedMulAddRelu(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask, const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
* @ingroup MulAddRelu Level 2
* @brief dst = relu(src0 * dst + src1)
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] count number Number of data involved in calculation
*/
template <typename T>
__aicore__ inline void MulAddRelu(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, const int32_t& count);
template <typename T>
__aicore__ inline void FusedMulAddRelu(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, const int32_t& count);
* SubRelu *
* ************************************************************************************************* */
* @ingroup SubRelu Level 0
* @brief dst = Relu(src0 - src1)
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] mask[]/mask mask array/count
* @param [in] repeatTime repeat times
* @param [in] repeatParams.dstBlkStride dst block stride
* @param [in] repeatParams.src0BlkStride src0 block stride
* @param [in] repeatParams.src1BlkStride src1 block stride
* @param [in] repeatParams.dstRepStride dst repeat stride
* @param [in] repeatParams.src0RepStride src0 repeat stride
* @param [in] repeatParams.src1RepStride src1 repeat stride
*/
template <typename T, bool isSetMask = true>
__aicore__ inline void SubRelu(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask[], const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <typename T, bool isSetMask = true>
__aicore__ inline void SubRelu(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, uint64_t mask, const uint8_t repeatTime,
const BinaryRepeatParams& repeatParams);
template <typename T>
__aicore__ inline void SubRelu(const LocalTensor<T>& dst, const LocalTensor<T>& src0,
const LocalTensor<T>& src1, const int32_t& count);
#if (__NPU_ARCH__ == 3101) || (__NPU_ARCH__ == 5102)
* Prelu *
* ************************************************************************************************* */
* @ingroup Prelu Level 2
* @brief dst = (src0 >= 0) ? src0 : src0 * src1
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] count number Number of data involved in calculation
*/
template <typename T>
__aicore__ inline void Prelu(const LocalTensor<T>& dst, const LocalTensor<T> &src0,
const LocalTensor<T> &src1, const uint32_t count);
* Mull *
* ************************************************************************************************* */
* @ingroup Mull Level 2
* @brief Multiply input data src0 and src1 by element based on the mask, write the result to
dst0, and write the overflow part to dst1.
* @param [out] dst0 output LocalTensor
* @param [out] dst1 output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] count number Number of data involved in calculation
*/
template <typename T>
__aicore__ inline void Mull(const LocalTensor<T>& dst0, const LocalTensor<T>& dst1,
const LocalTensor<T>& src0, const LocalTensor<T>& src1, const uint32_t count);
* AbsSub *
* ************************************************************************************************* */
* @ingroup AbsSub Level 2
* @brief dst = abs(src0 - src1)
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] count number Number of data involved in calculation
*/
template <typename T>
__aicore__ inline void AbsSub(const LocalTensor<T> &dst, const LocalTensor<T> &src0,
const LocalTensor<T> &src1, const uint32_t count);
template <typename T>
__aicore__ inline void FusedAbsSub(const LocalTensor<T> &dst, const LocalTensor<T> &src0,
const LocalTensor<T> &src1, const uint32_t count);
* ExpSub *
* ************************************************************************************************* */
* @ingroup ExpSub Level 2
* @brief when T is float : dst = e^(src0 - src1); when T is half : dst = e^(cast_f16_to_f32(src0) - cast_f16_to_f32(src1))
* @param [out] dst output LocalTensor
* @param [in] src0 input LocalTensor
* @param [in] src1 input LocalTensor
* @param [in] count number Number of data involved in calculation
*/
template <typename T, typename U>
__aicore__ inline void ExpSub(const LocalTensor<T> &dst, const LocalTensor<U> &src0,
const LocalTensor<U> &src1, const uint32_t count);
template <typename T, typename U>
__aicore__ inline void FusedExpSub(const LocalTensor<T> &dst, const LocalTensor<U> &src0,
const LocalTensor<U> &src1, const uint32_t count);
#endif
}
#pragma end_pipe
#include "../../impl/basic_api/kernel_operator_vec_binary_intf_impl.h"
#endif
