* 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 simplesoftmax.h
* \brief SimpleSoftMax api of AscendC
*/
#ifndef LIB_SOFTMAX_SIMPLESOFTMAX_H
#define LIB_SOFTMAX_SIMPLESOFTMAX_H
#include "kernel_tensor.h"
#include "kernel_tiling/kernel_tiling.h"
#include "include/adv_api/activation/softmax_utils.h"
#if defined(__NPU_ARCH__) && (__NPU_ARCH__ == 2201 || __NPU_ARCH__ == 2002 || __NPU_ARCH__ == 3101 || __NPU_ARCH__ == 3002 || __NPU_ARCH__ == 5102 || \
__NPU_ARCH__ == 3003 || __NPU_ARCH__ == 3113)
#include "../../../impl/adv_api/detail/activation/softmax/softmax_common.h"
#include "../../../impl/adv_api/detail/activation/softmax/simple_softmax_base_impl.h"
#pragma begin_pipe(V)
namespace AscendC {
* \ingroup SimpleSoftMax
* \brief compute process: y = exp(x-inmax)/insum
* \note support data type: half and float
* \param [out] dstTensor: output y
* \param [in] inSumTensor: input insum
* \param [in] inMaxTensor: input inmax
* \param [in] srcTensor: input x
* \param [in] softmaxShapeInfo: input srcTensor shape
* \param [in] tiling: input softmaxtiling
* \param [in] isReuseSource: reserved param
* \param [in] isBasicBlock: if srcTensor shape[m,k] satisfy the condition(m%8 == 0 && k%64 == 0),you can set true to
* improve performance, but it is a reserved param when isDataFormatNZ = true
* \param [in] isDataFormatNZ: if the data format of input srcTensor is NZ
*/
template <typename T, bool isReuseSource = false, bool isBasicBlock = false, bool isDataFormatNZ = false,
const SoftmaxConfig& config = SOFTMAX_DEFAULT_CFG>
__aicore__ inline void SimpleSoftMax(const LocalTensor<T>& dstTensor, const LocalTensor<T>& inSumTensor,
const LocalTensor<T>& inMaxTensor, const LocalTensor<T>& srcTensor, const SoftMaxTiling& tiling,
const SoftMaxShapeInfo& softmaxShapeInfo = {})
{
if ASCEND_IS_AIC {
return;
}
SimpleSoftMaxImpl<T, T, isReuseSource, isBasicBlock, isDataFormatNZ, config>(dstTensor, inSumTensor, inMaxTensor, srcTensor,
tiling, softmaxShapeInfo);
}
* \ingroup SimpleSoftMax
* \brief compute process: y = exp(x-inmax)/insum
* \param [out] dstTensor: output y with dtype of half
* \param [in] inSumTensor: input insum with dtype of float
* \param [in] inMaxTensor: input inmax with dtype of float
* \param [in] srcTensor: input x with dtype of half
* \param [in] softmaxShapeInfo: input srcTensor shape
* \param [in] tiling: input softmaxtiling
* \param [in] isReuseSource: reserved param
* \param [in] isBasicBlock: if srcTensor shape[m,k] satisfy the condition(m%8 == 0 && k%64 == 0), you can set true to
* improve performance, but it is a reserved param when isDataFormatNZ = true
* \param [in] isDataFormatNZ: if the data format of input srcTensor is NZ
*/
template <typename T, bool isReuseSource = false, bool isBasicBlock = false, bool isDataFormatNZ = false,
const SoftmaxConfig& config = SOFTMAX_DEFAULT_CFG>
__aicore__ inline void SimpleSoftMax(const LocalTensor<half>& dstTensor, const LocalTensor<float>& inSumTensor,
const LocalTensor<float>& inMaxTensor, const LocalTensor<half>& srcTensor, const SoftMaxTiling& tiling,
const SoftMaxShapeInfo& softmaxShapeInfo = {})
{
if ASCEND_IS_AIC {
return;
}
SimpleSoftMaxImpl<half, float, isReuseSource, isBasicBlock, isDataFormatNZ, config>(dstTensor, inSumTensor, inMaxTensor, srcTensor,
tiling, softmaxShapeInfo);
}
* \ingroup SimpleSoftMax
* \brief compute process: y = exp(x-inmax)/insum
* \note support data type: half and float
* \param [out] dstTensor: output y
* \param [in] inSumTensor: input insum
* \param [in] inMaxTensor: input inmax
* \param [in] srcTensor: input x
* \param [in] sharedTmpBuffer: input local temporary Tensor,you can get the range by tilingfunc of
* GetSoftMaxMinTmpSize/GetSoftMaxMaxTmpSize
* \param [in] softmaxShapeInfo: input srcTensor shape
* \param [in] tiling: input softmaxtiling
* \param [in] isReuseSource: reserved param
* \param [in] isBasicBlock: if srcTensor shape[m,k] satisfy the condition(m%8 == 0 && k%64 == 0), you can set true to
* improve performance, but it is a reserved param when isDataFormatNZ = true
* \param [in] isDataFormatNZ: if the data format of input srcTensor is NZ
*/
template <typename T, bool isReuseSource = false, bool isBasicBlock = false, bool isDataFormatNZ = false,
const SoftmaxConfig& config = SOFTMAX_DEFAULT_CFG>
__aicore__ inline void SimpleSoftMax(const LocalTensor<T>& dstTensor, const LocalTensor<T>& inSumTensor,
const LocalTensor<T>& inMaxTensor, const LocalTensor<T>& srcTensor, const LocalTensor<uint8_t>& sharedTmpBuffer,
const SoftMaxTiling& tiling, const SoftMaxShapeInfo& softmaxShapeInfo = {})
{
if ASCEND_IS_AIC {
return;
}
SimpleSoftMaxImpl<T, T, isReuseSource, isBasicBlock, isDataFormatNZ, config>(dstTensor, inSumTensor, inMaxTensor, srcTensor,
sharedTmpBuffer, tiling, softmaxShapeInfo);
}
* \ingroup SimpleSoftMax
* \brief compute process: y = exp(x-inmax)/insum
* \param [out] dstTensor: output y with dtype of half
* \param [in] inSumTensor: input insum with dtype of float
* \param [in] inMaxTensor: input inmax with dtype of float
* \param [in] srcTensor: input x with dtype of half
* \param [in] sharedTmpBuffer: input local temporary Tensor,you can get the range by tilingfunc of
* GetSoftMaxMinTmpSize/GetSoftMaxMaxTmpSize
* \param [in] softmaxShapeInfo: input srcTensor shape
* \param [in] tiling: input softmaxtiling
* \param [in] isReuseSource: reserved param
* \param [in] isBasicBlock: if srcTensor shape[m,k] satisfy the condition(m%8 == 0 && k%64 == 0), you can set true to
* improve performance, but it is a reserved param when isDataFormatNZ = true
* \param [in] isDataFormatNZ: if the data format of input srcTensor is NZ
*/
template <typename T, bool isReuseSource = false, bool isBasicBlock = false, bool isDataFormatNZ = false,
const SoftmaxConfig& config = SOFTMAX_DEFAULT_CFG>
__aicore__ inline void SimpleSoftMax(const LocalTensor<half>& dstTensor, const LocalTensor<float>& inSumTensor,
const LocalTensor<float>& inMaxTensor, const LocalTensor<half>& srcTensor,
const LocalTensor<uint8_t>& sharedTmpBuffer, const SoftMaxTiling& tiling,
const SoftMaxShapeInfo& softmaxShapeInfo = {})
{
if ASCEND_IS_AIC {
return;
}
SimpleSoftMaxImpl<half, float, isReuseSource, isBasicBlock, isDataFormatNZ, config>(dstTensor, inSumTensor, inMaxTensor, srcTensor,
sharedTmpBuffer, tiling, softmaxShapeInfo);
}
}
#pragma end_pipe
#endif
#endif
