mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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105 lines
4.0 KiB
Plaintext
105 lines
4.0 KiB
Plaintext
/*
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* Copyright (c) 2019-2024, NVIDIA CORPORATION. All rights reserved.
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* Copyright (c) 2021, NAVER Corp. Authored by CLOVA.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include <cuda_runtime_api.h>
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#include <cuda_bf16.h>
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#include <cuda_fp16.h>
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#ifdef ENABLE_FP8
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#include <cuda_fp8.h>
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#endif
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#include "draftTokenTreeKernels.h"
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#include "tensorrt_llm/common/assert.h"
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#include "tensorrt_llm/common/config.h"
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#include "tensorrt_llm/common/cudaBf16Fallbacks.cuh"
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#include "tensorrt_llm/common/cudaTypeUtils.cuh"
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#include "tensorrt_llm/common/cudaUtils.h"
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using namespace tensorrt_llm::common;
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TRTLLM_NAMESPACE_BEGIN
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namespace kernels
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{
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__global__ void extractRealDraftTokensKernel(int const curDraftIdx, int const batchSize, int const maxDraftLen,
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int const maxTotalDraftTokens, int const maxTopK, int const numTokensExpandThisLayer,
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int* tokensGatherIdxForDrafterModel, int* topKList, int* draftTokensIndicesCumsum, int64_t* newDraftTokens,
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int64_t* draftTokensBuffer)
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{
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// curDraftIdx: int
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// batchSize: int
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// maxTotalDraftTokens: int
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// maxTopK: int
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// tokensGatherIdxForDrafterModel: int32_t*, indices of the draft tokens that need to be expand this layer
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// shape: [numTokensExpandThisLayer]
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// topKList: int32_t*, top k value for each expandable token
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// shape: [numTokensExpandThisLayer]
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// draftTokensIndicesCumsum: int32_t*, the cumulative sum of the write back indices for each draft layer
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// shape: [maxDraftLen + 1]
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// newDraftTokens: int64_t*, the new draft tokens. We only need to extract this layer's tokens and write back to
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// the draftTokensBuffer shape: [batchSize, maxTotalDraftTokens + 1 if curDraftIdx > 0 else 1, maxTopK]
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// draftTokensBuffer: int64_t*, the buffer to store the real draft tokens
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// shape: [maxBatchSize, maxTotalDraftTokens + 1]
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// Each thread handles one request
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auto const tix = static_cast<int>(blockIdx.x * blockDim.x + threadIdx.x);
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auto const isValid{tix < batchSize};
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if (isValid)
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{
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int newDraftTokensOffset = curDraftIdx == 0 ? 1 : maxTotalDraftTokens + 1;
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auto newDraftTokensStartPtr = newDraftTokens + tix * newDraftTokensOffset * maxTopK;
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auto draftTokensBufferPtr
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= draftTokensBuffer + tix * (maxTotalDraftTokens + 1) + draftTokensIndicesCumsum[curDraftIdx];
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int cnt = 0;
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for (int i = 0; i < numTokensExpandThisLayer; i++)
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{
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int tokenGatherIdx = tokensGatherIdxForDrafterModel[i];
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auto newDraftTokenPtr = newDraftTokensStartPtr + tokenGatherIdx * maxTopK;
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int topKValue = topKList[i];
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for (int j = 0; j < topKValue; j++)
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{
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int64_t newGenDraftToken = newDraftTokenPtr[j];
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draftTokensBufferPtr[cnt] = newGenDraftToken;
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cnt++;
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}
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}
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}
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}
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void invokeExtractRealDraftTokens(ExtractRealDraftTokensParam& params, cudaStream_t const stream)
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{
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int constexpr BLOCK_SIZE = 64;
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int NUM_BLOCKS = divUp(params.batchSize, BLOCK_SIZE);
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extractRealDraftTokensKernel<<<NUM_BLOCKS, BLOCK_SIZE, 0, stream>>>(params.curDraftIdx, params.batchSize,
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params.maxDraftLen, params.maxTotalDraftTokens, params.maxTopK, params.numTokensExpandThisLayer,
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params.tokensGatherIdxForDrafterModel, params.topKList, params.draftTokensIndicesCumsum, params.newDraftTokens,
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params.draftTokensBuffer);
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sync_check_cuda_error(stream);
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}
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} // namespace kernels
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TRTLLM_NAMESPACE_END
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