/**
* 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 asinh.h
 * \brief
 */

#ifndef LIB_MATH_ASINH_H
#define LIB_MATH_ASINH_H
#if defined(__NPU_ARCH__) && (__NPU_ARCH__ == 2201 || __NPU_ARCH__ == 2002 || __NPU_ARCH__ == 3101 || __NPU_ARCH__ == 5102)
#include "kernel_tensor.h"

#if defined(__NPU_ARCH__) && (__NPU_ARCH__ == 2002 || __NPU_ARCH__ == 2201)
#include "../../../impl/adv_api/detail/math/asinh/asinh_common_impl.h"
#else
#include "../../../impl/adv_api/detail/math/asinh/asinh_c310_impl.h"
#endif
#if defined(__NPU_ARCH__) && (__NPU_ARCH__ == 2201 || __NPU_ARCH__ == 2002 || __NPU_ARCH__ == 3101 || __NPU_ARCH__ == 5102)

namespace AscendC {
#pragma begin_pipe(V)
/* !
 * \brief Returns a new tensor with the inverse hyperbolic sine of the elements of input.
 * https://pytorch.org/docs/stable/generated/torch.asinh.html#torch.asinh
 * \note support data type: half and float
 *
 * \param [out] dstTensor, output LocalTensor
 * \param [in] srcTensor, input LocalTensor
 * \param [in] sharedTmpBuffer, input local temporary Tensor
 * \param [in] calCount, amount of data to be calculated
 */
template <typename T, bool isReuseSource = false>
__aicore__ inline void Asinh(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor,
    const LocalTensor<uint8_t>& sharedTmpBuffer, const uint32_t calCount)
{
    AsinhImpl<T, isReuseSource>(dstTensor, srcTensor, sharedTmpBuffer, calCount);
}

/* !
 * \note support data type: half and float
 *
 * \param [out] dstTensor, output LocalTensor
 * \param [in] srcTensor, input LocalTensor
 * \param [in] sharedTmpBuffer, input local temporary Tensor
 */
template <typename T, bool isReuseSource = false>
__aicore__ inline void Asinh(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor,
    const LocalTensor<uint8_t>& sharedTmpBuffer)
{
    Asinh<T, isReuseSource>(dstTensor, srcTensor, sharedTmpBuffer, srcTensor.GetSize());
}

/* !
 * \note support data type: half and float
 *
 * \param [out] dstTensor, output LocalTensor
 * \param [in] srcTensor, input LocalTensor
 * \param [in] calCount, amount of data to be calculated
 */
template <typename T, bool isReuseSource = false>
__aicore__ inline void Asinh(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor, const uint32_t calCount)
{
    // Only for AI Vector Core.
    if ASCEND_IS_AIC {
        return;
    }

    AsinhImpl<T, isReuseSource>(dstTensor, srcTensor, calCount);
}

/* !
 * \note support data type: half and float
 *
 * \param [out] dstTensor, output LocalTensor
 * \param [in] srcTensor, input LocalTensor
 */
template <typename T, bool isReuseSource = false>
__aicore__ inline void Asinh(const LocalTensor<T>& dstTensor, const LocalTensor<T>& srcTensor)
{
    // Only for AI Vector Core.
    if ASCEND_IS_AIC {
        return;
    }

    AsinhImpl<T, isReuseSource>(dstTensor, srcTensor);
}
#pragma end_pipe
}
#endif
#endif
#endif // LIB_MATH_ASINH_H