/*
 * Copyright (c) 2019-2024, NVIDIA CORPORATION.  All rights reserved.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

#include "tensorrt_llm/kernels/beamSearchKernels.h"
#include "tensorrt_llm/layers/beamSearchLayer.h"
#include "tensorrt_llm/layers/defaultDecodingParams.h"
#include "tensorrt_llm/layers/layerUtils.h"
#include <limits>

using namespace tensorrt_llm::common;
using namespace tensorrt_llm::kernels;

namespace tensorrt_llm::layers
{

template <typename T>
BeamSearchLayer<T>::BeamSearchLayer(
    DecoderDomain const& decoderDomain, cudaStream_t stream, std::shared_ptr<IAllocator> allocator)
    : BaseLayer(decoderDomain, stream, std::move(allocator))
    , mVocabSize(decoderDomain.getVocabSize())
    , mVocabSizePadded(decoderDomain.getVocabSizePadded())
{
    TLLM_LOG_TRACE(__PRETTY_FUNCTION__);

    mDiversityRateHost.resize(mDecoderDomain.getBatchSize());
    mLengthPenaltyHost.resize(mDecoderDomain.getBatchSize());
    mEarlyStoppingHost.resize(mDecoderDomain.getBatchSize());
    allocateBuffer(mDecoderDomain.getBatchSize(), mDecoderDomain.getBeamWidth());

    TLLM_CHECK_WITH_INFO(mDecoderDomain.getBeamWidth() <= nMaxBeamWidth,
        std::string("Beam width is larger than the maximum supported (" + std::to_string(mDecoderDomain.getBeamWidth())
            + " > " + std::to_string(nMaxBeamWidth) + ")."));
}

template <typename T>
BeamSearchLayer<T>::~BeamSearchLayer()
{
    TLLM_LOG_TRACE(__PRETTY_FUNCTION__);
}

template <typename T>
void BeamSearchLayer<T>::setup(runtime::SizeType32 const batchSize, runtime::SizeType32 const beamWidth,
    runtime::SizeType32 const* batchSlots, std::shared_ptr<BaseSetupParams> const& baseSetupParams)
{
    TLLM_LOG_TRACE("%s start", __PRETTY_FUNCTION__);
    TLLM_CHECK_WITH_INFO(beamWidth <= mDecoderDomain.getBeamWidth(),
        std::string("Beam width is larger than the constructed for (" + std::to_string(beamWidth) + " > "
            + std::to_string(mDecoderDomain.getBeamWidth()) + ")."));

    auto setupParams = std::dynamic_pointer_cast<BeamSearchSetupParams>(baseSetupParams);

    auto constexpr fltMax = std::numeric_limits<float>::max();
    auto constexpr fltMin = std::numeric_limits<float>::lowest();
    auto constexpr fltEpsilon = std::numeric_limits<float>::epsilon();

    std::vector<SizeType32> batchSlotsVec(batchSize);
    std::iota(batchSlotsVec.begin(), batchSlotsVec.end(), 0);
    auto batchSlotsHost = batchSlots ? batchSlots : batchSlotsVec.data();

    FillBuffers const fillBuffers{batchSize, mDecoderDomain.getBatchSize(), mStream};
    fillBuffers(setupParams->beamSearchDiversityRate, DefaultDecodingParams::getBeamSearchDiversity(),
        mDiversityRateHost, mDiversityRateDevice, batchSlotsHost, std::make_pair(-fltEpsilon, fltMax),
        "diversity rate");
    fillBuffers(setupParams->lengthPenalty, DefaultDecodingParams::getLengthPenalty(), mLengthPenaltyHost,
        mLengthPenaltyDevice, batchSlotsHost, std::make_pair(fltMin, fltMax), "length penalty");
    fillBuffers(setupParams->earlyStopping, DefaultDecodingParams::getEarlyStopping(), mEarlyStoppingHost,
        mEarlyStoppingDevice, batchSlotsHost, std::make_pair(0, std::numeric_limits<int>::max()), "early stopping");

    TLLM_LOG_TRACE("%s stop", __PRETTY_FUNCTION__);
}

__global__ void updateCacheIndirectionKernel(
    int* tgtCI, int const* srcCI, BeamHypotheses bh, int const nMaxAttentionWindow, int const nSinkTokenLength)
{
    // Update indirections from steps `bh.inputLength[indexBatchBeam]` to step `sequenceLengths[indexBatchBeam]`
    int const step = threadIdx.x + blockIdx.x * blockDim.x;
    int const nBM{bh.nBeamWidth};
    int const nMSL{bh.nMaxSeqLen};
    int const indexBatch = blockIdx.y;
    int const batchSlot = bh.batchSlots ? bh.batchSlots[indexBatch] : indexBatch;
    int const indexBeam = blockIdx.z;
    int const indexBatchBeam = batchSlot * nBM + indexBeam;
    int const lastStep{bh.sequenceLengths[indexBatchBeam] - 1}; // the sequenceLengths is updated, need to minus 1

    // Return early when the indexBatchBeam or step is out of the bound
    // No update for the indices of context part since KV Cache is shared
    if (step >= nMSL || step < bh.inputLengths[indexBatchBeam] || step < (nMSL - nMaxAttentionWindow)
        || bh.finished[indexBatchBeam].isFinished())
    {
        return;
    }

    // Keep all past tokens by parentIdsPtr
    int const indexBeamSrc = bh.parentIdsPtr[batchSlot][indexBeam * nMSL + lastStep];
    int const stepCirc = (step >= nSinkTokenLength)
        ? nSinkTokenLength + (step - nSinkTokenLength) % (nMaxAttentionWindow - nSinkTokenLength)
        : step;
    // Consider cyclic kv cache for the indir tables
    uint32_t const tgtOffset = batchSlot * nBM * nMaxAttentionWindow + indexBeam * nMaxAttentionWindow + stepCirc;
    uint32_t const srcOffset = batchSlot * nBM * nMaxAttentionWindow + indexBeamSrc * nMaxAttentionWindow + stepCirc;
    tgtCI[tgtOffset] = (step == lastStep) ? indexBeam : srcCI[srcOffset];
}

template <typename T>
void BeamSearchLayer<T>::forwardAsync(
    std::shared_ptr<BaseDecodingOutputs> const& baseOutputs, std::shared_ptr<BaseDecodingInputs> const& baseInputs)
{
    TLLM_LOG_TRACE("%s start", __PRETTY_FUNCTION__);

    auto ip = std::dynamic_pointer_cast<DecodingInputs>(baseInputs);
    auto op = std::dynamic_pointer_cast<BeamSearchOutputs>(baseOutputs);
    auto const localDecoderDomain = getLocalDecoderDomain(ip, mDecoderDomain);

    TLLM_CHECK_WITH_INFO(localDecoderDomain.getBeamWidth() > 1,
        "Decoding mode is beam search, but beamWidth <= 1 (%d <= 1)", localDecoderDomain.getBeamWidth());
    TLLM_CHECK_WITH_INFO(ip->srcCacheIndirection.has_value(), "srcCacheIndirection is mandatory in beam search.");
    TLLM_CHECK_WITH_INFO(op->parentIds.has_value(), "parentIds tensor is mandatory in beam search.");
    TLLM_CHECK_WITH_INFO(op->finished.has_value(), "finished tensor is mandatory in beam search.");
    TLLM_CHECK_WITH_INFO(op->cumLogProbs.has_value(), "cumLogProbs tensor is mandatory in beam search.");
    TLLM_CHECK_WITH_INFO(op->beamHypotheses, std::string("Output BeamHypotheses is not set."));
    TLLM_CHECK_WITH_INFO(op->sequenceLength->template getPtr<int>() != nullptr || mLengthPenaltyDevice == nullptr,
        std::string("Current sequence lengths must be set for length penalty computation."));
    TLLM_CHECK_WITH_INFO(ip->ite == 0, "Pipeline Parallelism is not supported yet !");

    BeamHypotheses bh;
    // bh's members not used in function: outputIds, logProbs, outputIdsUnfinish, parentIdsUnfinish
    bh.outputIdsCBA = op->beamHypotheses->outputIdsCBA;
    bh.logProbsCBA = op->beamHypotheses->logProbsCBA;
    bh.sequenceLengthsCBA = op->beamHypotheses->sequenceLengthsCBA;
    bh.cumLogProbsCBA = op->beamHypotheses->cumLogProbsCBA;
    bh.normedScoresCBA = op->beamHypotheses->normedScoresCBA;
    bh.numBeamsCBA = op->beamHypotheses->numBeamsCBA;
    bh.minNormedScoresCBA = op->beamHypotheses->minNormedScoresCBA;
    bh.batchDones = op->beamHypotheses->batchDones;
    bh.nMaxBatchSize = static_cast<std::int32_t>(op->outputIdsPtr.shape[0]);
    bh.nBatchSize = ip->localBatchSize;
    bh.batchSlots = ip->batchSlots ? ip->batchSlots->template getPtr<SizeType32 const>() : nullptr;
    bh.nBeamWidth = static_cast<std::int32_t>(op->outputIdsPtr.shape[1]);
    bh.nMaxSeqLen = static_cast<std::int32_t>(op->outputIdsPtr.shape[2]);
    bh.nVocabSize = mVocabSizePadded;
    bh.diversityRates = mDiversityRateDevice;
    bh.lengthPenalties = mLengthPenaltyDevice;
    bh.earlyStoppings = mEarlyStoppingDevice;
    bh.inputLengths = ip->inputLengths->template getPtr<int const>();
    bh.endIds = ip->endIds.template getPtr<int const>();
    bh.logProbsTiled = (op->outputLogProbsTiled) ? op->outputLogProbsTiled->template getPtr<float>() : nullptr;
    bh.sequenceLengths = op->sequenceLength->template getPtr<int>();
    bh.cumLogProbs = op->cumLogProbs->template getPtr<float>();
    bh.finished = reinterpret_cast<FinishedState*>(op->finished->template getPtr<FinishedState::UnderlyingType>());
    bh.outputIdsPtr = op->outputIdsPtr.template getPtr<int*>();
    bh.parentIdsPtr = op->parentIdsPtr.template getPtr<int*>();

    T const* logits = ip->logits->template getPtr<T>();
    T const* bias = static_cast<T const*>(nullptr);
    TLLM_CHECK_WITH_INFO(mWorkspaceSize >= 2 * bh.nBatchSize * bh.nBeamWidth * bh.nBeamWidth * 2,
        fmtstr("Workspace size (%lu) is not enough for topk softmax required (%lu).", (uint64_t) mWorkspaceSize,
            (uint64_t) (2 * bh.nMaxBatchSize * bh.nBeamWidth * bh.nBeamWidth * 2)));

    invokeTopkSoftMax(logits, bias, mWorkspace, bh, mStream);
    sync_check_cuda_error();

    if (bh.nBeamWidth > 1)
    {
        auto tgtCI = op->tgtCacheIndirection.template getPtr<int>();
        auto srcCI = ip->srcCacheIndirection->template getPtr<int const>();
        dim3 const grid(roundUp(bh.nMaxSeqLen, 32), bh.nBatchSize, bh.nBeamWidth);
        updateCacheIndirectionKernel<<<grid, 32, 0, mStream>>>(
            tgtCI, srcCI, bh, ip->maxAttentionWindow, ip->sinkTokenLength);
        sync_check_cuda_error();
    }

    TLLM_LOG_TRACE("%s stop", __PRETTY_FUNCTION__);
}

template <typename T>
void BeamSearchLayer<T>::allocateBuffer(runtime::SizeType32 const batchSize, runtime::SizeType32 const beamWidth)
{
    TLLM_LOG_TRACE("%s start", __PRETTY_FUNCTION__);
    int const nPadBeamWidth = padToNextPowerOfTwo(beamWidth);
    // Unit of mWorkspaceSize is number of elements (not Byte), align to 4 for further optimization
    size_t nTopK = batchSize * nPadBeamWidth * nPadBeamWidth * 2;
    size_t nTempBuffer = batchSize * nPadBeamWidth * nMaxVocabPartForStage1FastKernel * (2 * (nPadBeamWidth * 2) + 2);
    mWorkspaceSize = roundUp(nTopK, 4) * 2 + roundUp(nTempBuffer, 4);
    mWorkspace = mAllocator->reMalloc(mWorkspace, sizeof(float) * mWorkspaceSize, true);
    mDiversityRateDevice
        = mAllocator->reMalloc(mDiversityRateDevice, sizeof(float) * mDecoderDomain.getBatchSize(), false);
    mLengthPenaltyDevice
        = mAllocator->reMalloc(mLengthPenaltyDevice, sizeof(float) * mDecoderDomain.getBatchSize(), false);
    mEarlyStoppingDevice
        = mAllocator->reMalloc(mEarlyStoppingDevice, sizeof(int) * mDecoderDomain.getBatchSize(), false);
    mIsAllocateBuffer = true;
    TLLM_LOG_TRACE("%s stop", __PRETTY_FUNCTION__);
}

template <typename T>
void BeamSearchLayer<T>::freeBuffer()
{
    TLLM_LOG_TRACE("%s start", __PRETTY_FUNCTION__);
    if (mIsAllocateBuffer)
    {
        mAllocator->free((void**) (&mWorkspace));
        mAllocator->free((void**) (&mDiversityRateDevice));
        mAllocator->free((void**) (&mLengthPenaltyDevice));
        mAllocator->free((void**) (&mEarlyStoppingDevice));
        mIsAllocateBuffer = false;
    }
    TLLM_LOG_TRACE("%s stop", __PRETTY_FUNCTION__);
}

template class BeamSearchLayer<float>;
template class BeamSearchLayer<half>;

} // namespace tensorrt_llm::layers