/**
 * Copyright (c) 2024 Huawei Technologies Co., Ltd.
 * This file is a part of the CANN Open Software.
 * Licensed under CANN Open Software License Agreement Version 1.0 (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.
 */

#ifndef LIB_RMSNORM_RMSNORM_H
#define LIB_RMSNORM_RMSNORM_H
#include "kernel_tensor.h"
#include "kernel_operator_intf.h"
#include "kernel_pop_stack_buffer.h"
#include "kernel_tiling/kernel_tiling.h"
#include "../../impl/normalization/rmsnorm/rmsnorm_common_impl.h"

#if __CCE_AICORE__ == 220 || __CCE_AICORE__ == 200
namespace AscendC {
#pragma begin_pipe(V)
/*!
 * \brief Root Mean Square Layer Normalization, for more info see https://arxiv.org/abs/1910.07467
 *
 * \note support data type: half and float
 *
 * \param [in] isBasicBlock: indicate whether enable basic block
 * \param [out] dstLocal: output LocalTensor
 * \param [in] srcLocal: input LocalTensor
 * \param [in] gammaLocal: input gamma LocalTensor
 * \param [in] sharedTmpBuffer: input temporary localTensor
 * \param [in] epsilon: epslion value
 * \param [in] tiling: tiling for RmsNorm interface
 */
template <typename T, bool isBasicBlock = false>
__aicore__ inline void RmsNorm(const LocalTensor<T>& dstLocal, const LocalTensor<T>& srcLocal,
    const LocalTensor<T>& gammaLocal, const LocalTensor<uint8_t>& sharedTmpBuffer, const T epsilon,
    const RmsNormTiling& tiling)
{
    if ASCEND_IS_AIC {
        return;
    }
    ASCENDC_ASSERT((IsSameType<T, half>::value || IsSameType<T, float>::value),
        { KERNEL_LOG(KERNEL_ERROR, "RmsNorm only support data type: float/half"); });
    RmsNormAPI::RmsNormImpl<T, isBasicBlock>(dstLocal, srcLocal, gammaLocal, sharedTmpBuffer, epsilon, tiling);
}

/*!
 * \brief Root Mean Square Layer Normalization, for more info see https://arxiv.org/abs/1910.07467
 *
 * \note support data type: half and float. This interface will allocate a tmp buffer.
 *       user should make sure that memory on UB is big enough for input tiling.
 *
 * \param [in] isBasicBlock: indicate whether enable basic block
 * \param [out] dstLocal: output LocalTensor
 * \param [in] srcLocal: input LocalTensor
 * \param [in] gammaLocal: input gamma LocalTensor
 * \param [in] epsilon: epslion value
 * \param [in] tiling: tiling for RmsNorm interface
 */
template <typename T, bool isBasicBlock = false>
__aicore__ inline void RmsNorm(const LocalTensor<T>& dstLocal, const LocalTensor<T>& srcLocal,
    const LocalTensor<T>& gammaLocal, const T epsilon, const RmsNormTiling& tiling)
{
    if ASCEND_IS_AIC {
        return;
    }
    LocalTensor<uint8_t> stackBufer;
    bool ret = PopStackBuffer<uint8_t, TPosition::LCM>(stackBufer);
    ASCENDC_ASSERT((ret), { KERNEL_LOG(KERNEL_ERROR, "RmsNorm failed to apply for tmp buffer!"); });
    RmsNorm<T, isBasicBlock>(dstLocal, srcLocal, gammaLocal, stackBufer, epsilon, tiling);
}
#pragma end_pipe
} // namespace AscendC
#endif
#endif // LIB_RMSNORM_RMSNORM_H