* 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 tan.h
* \brief Defines a series of interface used to do elementwise math tan calculation.
* Formula: tan(x) = xP(x) / ((�/2 - x)(�/2 + x)Q(x))
* The Tan function does not have an elementary function expression, first normalize x to (-�/2, �/2)
* and then calculating by function approximation.
* Final solution锛?
* k=round(x/�), x0=x-k�, x0 belongs to (-�/2, �/2)
* �=�_0+�_1+�_2+�_3+�_4 achieve final precision compensation.
* Final solution锛?
* k = round(x * invpi)
* x -= k * pi_0
* x -= k * pi_1
* down1 = x + pio2_high // pi/2 + x
* down2 = x - pio2_high // x - pi/2
* x -= k * pi_2
* down1 -= k * pi_2
* down2 -= k * pi_2
* x -= k * pi_3
* down1 -= k * pi_3
* down2 -= k * pi_3
* x -= k * pi_4
* down1 -= k * pi_4
* down2 -= k * pi_4
* P(x) = (x^2 * R0 + R1) * x^2 + R2
* Q(x) = x^2 * R3
* R0 = 0.0698520831551998762793
* R1 = -6.8711573651634203789
* R2 = 61.20362572811089435388
* R3 = -24.8048928861126769186219
*/
#if !defined(__ASCENDC_INCLUDE_INTERNAL_HEADERS__)
#define __ASCENDC_INCLUDE_INTERNAL_HEADERS__
#define __UNDEF_ASCENDC_INCLUDE_INTERNAL_HEADERS_TAN_H__
#endif
#ifndef LIB_MATH_TAN_H
#define LIB_MATH_TAN_H
#if defined(__NPU_ARCH__) && (__NPU_ARCH__ == 2201 || __NPU_ARCH__ == 2002 || __NPU_ARCH__ == 3510 || \
__NPU_ARCH__ == 5102 || __NPU_ARCH__ == 3003 || __NPU_ARCH__ == 3113)
#include "kernel_tensor.h"
#if defined(__NPU_ARCH__) && (__NPU_ARCH__ == 2002 || __NPU_ARCH__ == 2201)
#include "../../../impl/adv_api/detail/math/tan/tan_common_impl.h"
#elif defined(__NPU_ARCH__) && (__NPU_ARCH__ == 3510 || __NPU_ARCH__ == 5102 || __NPU_ARCH__ == 3003 || \
__NPU_ARCH__ == 3113)
#include "../../../impl/adv_api/detail/math/tan/tan_c310_impl.h"
#endif
namespace AscendC {
#pragma begin_pipe(V)
* \ingroup Tan
* \brief compute Tan elementwisely
* \tparam T: half/float
* \tparam isReuseSource: whether allows API to modify source data, usually for performance reason,
* this parameter is reserved, please use the default value.
* \param [out] dstTensor: output LocalTensor
* \param [in] srcTensor: input LocalTensor
* \param [in] sharedTmpBuffer: extra temporary shared space used for intermediate values among calculation process,
* whose required space size should refer to corresponding tiling API, which is defined at tan_tiling.h.
* Generally, the more space you allocate, the better performance you will achieve, and the performance
* reaches peak when buffer size is maximum(calculated by tiling function). Moreover, it is not guaranteed
* that the shared space will be cleared after usage, the data could be anything.
* \note src/dst Tensor must be 32B aligned, and it doesn't allow src/dst/sharedTmpBuffer tensor address overlap.
* Input data valid range should be (-65504, 65504)
*/
template <typename T, bool isReuseSource = false>
__aicore__ inline void Tan(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor,
const LocalTensor<uint8_t>& sharedTmpBuffer)
{
Tan<T, isReuseSource>(dstTensor, srcTensor, sharedTmpBuffer, srcTensor.GetSize());
}
* \ingroup Tan
* \brief compute Tan elementwisely
* \tparam T: half/float
* \tparam isReuseSource: whether allows API to modify source data, usually for performance reason,
* this parameter is reserved, please use the default value.
* \param [out] dstTensor: output LocalTensor
* \param [in] srcTensor: input LocalTensor
* \param [in] sharedTmpBuffer: extra temporary shared space used for intermediate values among calculation process,
* whose required space size should refer to corresponding tiling API, which is defined at tan_tiling.h.
* Generally, the more space you allocate, the better performance you will achieve, and the performance
* reaches peak when buffer size is maximum(calculated by tiling function). Moreover, it is not guaranteed
* that the shared space will be cleared after usage, the data could be anything.
* \param [in] calCount: the number of elements to be processed.
* \note src/dst Tensor must be 32B aligned, and it doesn't allow src/dst/sharedTmpBuffer tensor address overlap.
* Input data valid range should be (-65504, 65504)
*/
template <typename T, bool isReuseSource = false>
__aicore__ inline void Tan(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor,
const LocalTensor<uint8_t>& sharedTmpBuffer, const uint32_t calCount)
{
TanImpl<T, isReuseSource>(dstTensor, srcTensor, sharedTmpBuffer, calCount);
}
* \ingroup Tan
* \brief compute Tan elementwisely
* \tparam T: half/float
* \tparam isReuseSource: whether allows API to modify source data, usually for performance reason,
* this parameter is reserved, please use the default value.
* \param [out] dstTensor: output LocalTensor
* \param [in] srcTensor: input LocalTensor
* \param [in] calCount: the number of elements to be processed.
* \note src/dst Tensor must be 32B aligned, and it doesn't allow src/dst/sharedTmpBuffer tensor address overlap.
* Input data valid range should be (-65504, 65504)
*/
template <typename T, bool isReuseSource = false>
__aicore__ inline void Tan(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor, const uint32_t calCount)
{
TanImpl<T, isReuseSource>(dstTensor, srcTensor, calCount);
}
* \ingroup Tan
* \brief compute Tan elementwisely
* \tparam T: half/float
* \tparam isReuseSource: whether allows API to modify source data, usually for performance reason,
* this parameter is reserved, please use the default value.
* \param [out] dstTensor: output LocalTensor
* \param [in] srcTensor: input LocalTensor
* \note src/dst Tensor must be 32B aligned, and it doesn't allow src/dst/sharedTmpBuffer tensor address overlap.
* Input data valid range should be (-65504, 65504)
*/
template <typename T, bool isReuseSource = false>
__aicore__ inline void Tan(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor)
{
Tan<T, isReuseSource>(dstTensor, srcTensor, srcTensor.GetSize());
}
#pragma end_pipe
}
#endif
#endif
#if defined(__UNDEF_ASCENDC_INCLUDE_INTERNAL_HEADERS_TAN_H__)
#undef __ASCENDC_INCLUDE_INTERNAL_HEADERS__
#undef __UNDEF_ASCENDC_INCLUDE_INTERNAL_HEADERS_TAN_H__
#endif
