About diverse beam search implementation

[shenlanyilang]

The diverse beam search in tensorrtllm seems so different with huggingface and the paper. Why using the parent beam's index as a additional score, is there any paper/work suggest that?
The huggingface's implementation will consider other beam's word, if having overlaps, will got a penalty score, which can avoid generating duplicates words.

# code in cpp/tensorrt_llm/kernels/beamSearchKernels.cu
template <typename T>
__global__ void addCumLogProbs(T* __restrict pStage1LogProbs, float const* __restrict cumLogProbs,
    FinishedState const* finished, int const* endIds, float const* diversityRates,
    runtime::SizeType32 const* batchSlots, size_t const nBS, size_t const nBMIn, size_t const nBMOut, size_t const nBM)
{
    int const bid = blockIdx.x; // Index of request in batch
    runtime::SizeType32 const slot = batchSlots[bid];
    float const diversityRate{diversityRates[slot]};
    T* pLocalLogProbs = pStage1LogProbs + bid * nBMIn * nBMOut * 2;

    for (int i = threadIdx.x; i < nBMIn * nBMOut * 2; i += blockDim.x)
    {
        int const iBMIn = i / (nBMOut * 2);
        if (finished[slot * nBMIn + iBMIn].isFinished())
        {
            pLocalLogProbs[i] += (i == endIds[slot]) ? 1.0f : 0.0f;
        }
        else
        {
            // nBM is used in VBWS since `cumLogProbs` is initialized with kMaxBeamWidth earlier than BeamSearchLayer
            pLocalLogProbs[i] += cumLogProbs[slot * nBM + iBMIn] + diversityRate * iBMIn;
        }
    }
    return;
}