mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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136 lines
6.6 KiB
C++
136 lines
6.6 KiB
C++
/*
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* Copyright (c) 2024, NVIDIA CORPORATION. All rights reserved.
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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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#pragma once
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#include "lookaheadPoolManager.h"
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#include "tensorrt_llm/runtime/common.h"
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namespace tensorrt_llm::layers
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{
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//! @brief An CPU implementation of Lookahead with ITensor.
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class LookaheadAlgorithm
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{
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public:
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using TensorPtr = runtime::ITensor::SharedPtr;
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using TensorConstPtr = runtime::ITensor::SharedConstPtr;
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//! @brief Currently the resource management is to be aligned with batch manager.
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//! @param w, n, g is the Jacobi window, n-gram level and guess set size respectively.
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LookaheadAlgorithm(
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runtime::SizeType32 maxW, runtime::SizeType32 maxN, runtime::SizeType32 maxG, runtime::SizeType32 id = 0);
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//! @brief setup per request, fill internal states from @param prompt.
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void setup(TensorConstPtr const& prompt, runtime::SizeType32 w, runtime::SizeType32 n, runtime::SizeType32 g,
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uint64_t seed);
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//! @brief accept the new generated tokens.
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//! LookaheadDecodingLayer need call once for the first token in generation phase.
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void accept(TensorConstPtr const& generatedTokens);
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//! @brief combine lookahead and guess to prepare the tensors.
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//! input @param lastPositionIdPtr is position id of the last golden token, in a TensorPtr.
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//! input @param lastTokenPtr the last golden token for searching in the pool, in a TensorPtr.
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//! output @param draftTokens, positionIds includes the lookahead and the verification branch information.
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//! output @param draftLengthPtr holds the draft tokens length.
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//! output @param attentionMask holds the draft tokens dependency mask, and attentionMaskOffset is the index offset
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//! in attentionMask.
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void prepare(TensorPtr const& draftTokens, TensorPtr const& positionIds, TensorPtr const& draftLengthPtr,
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TensorPtr const& attentionMask, runtime::SizeType32 attentionMaskOffset,
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TensorConstPtr const& lastPositionIdPtr, TensorConstPtr const& lastTokenPtr);
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//! @brief update the internal states and generate accepted tokens from @param outputTokens.
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//! input @param sampledTokens is the all the tokens from the language model.
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//! input @param endToken is the end token for `verify` early quit.
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//! output @param acceptedTokens, acceptedOffsets in @param acceptedLength.
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void update(TensorPtr const& acceptedTokens, TensorPtr const& acceptedOffsets, TensorPtr const& acceptedLength,
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TensorConstPtr const& sampledTokens, TensorConstPtr const& endToken);
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//! generate attention @param mask from @param posIds.
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static void posIdsToMask(TensorPtr const& mask, TensorConstPtr const& posIds);
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//! inplace encode the @param tokens and @param posIds according to attention @param masks, and record the offsets
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//! in @param encodeMap.
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static runtime::SizeType32 treeEncode(
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TensorPtr const& tokens, TensorPtr const& posIds, TensorPtr const& masks, TensorPtr const& encodeMap);
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private:
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//! @brief generate lookahead branch information.
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//! input @param startPosId is the first position id of the draftTokens.
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//! output @param draftTokens, positionIds of the lookahead branch.
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//! @return the actual filled lookahead length.
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runtime::SizeType32 lookahead(
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TensorPtr const& draftTokens, TensorPtr const& positionIds, runtime::SizeType32 startPosId);
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//! @brief generate verification branch information. Also save the guessed tokens for future verification.
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//! input @param startPosId the first position id.
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//! input @param lastToken the last golden token for searching in the pool.
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//! output @param guessTokens, guessIds of the verification branch.
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//! @return the actual filled guess length.
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runtime::SizeType32 guess(TensorPtr const& guessTokens, TensorPtr const& guessIds, runtime::SizeType32 startPosId,
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runtime::TokenIdType lastToken);
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//! @brief verify the guessed tokens results and generate the longest accepted tokens.
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//! input @param newLastToken is the new-generated last golden token.
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//! input @param sampledTokens is the generated token results from the language model.
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//! input @param endToken is the end token for early quit detection.
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//! output @param accepted in @param acceptedLength, including the first golden one.
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//! output @param acceptedOffsets is the offsets of draft tokens, excluding the first golden one.
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void verify(TensorPtr const& accepted, TensorPtr const& acceptedOffsets, TensorPtr const& acceptedLength,
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runtime::TokenIdType newLastToken, TensorConstPtr const& sampledTokens, TensorConstPtr const& endToken);
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private:
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LookaheadPoolManager mPoolManager;
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//! the random prefill tokens,
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TensorPtr mPrefillsMax; // shape [mMaxN-2]
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TensorPtr mPrefills; // shape [mN-2]
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//! the look ahead branch window
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TensorPtr mPastTokensMax; // shape [mMaxW * (mMaxN-1)]
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TensorPtr mPastTokens; // shape [mW, (mN-1)]
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//! the shifted mPastTokens as key tokens;
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TensorPtr mKeyTokensMax; // shape [mMaxW]
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TensorPtr mKeyTokens; // shape [mW]
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//! all the moving tail golden tokens
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TensorPtr mGoldenTokensMax; // shape[mMaxN*2-1]
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TensorPtr mGoldenTokens; // shape[mN*2-1]
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//! the same guess tokens from `guess` and used in `verify`
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TensorPtr mGuessTokensMax; // shape [mMaxG*(mMaxN-1)]
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TensorPtr mGuessTokens; // shape [mG*(mN-1)]
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TensorPtr mDraftTokensMax;
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TensorPtr mDraftTokens;
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TensorPtr mAttentionMask;
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TensorPtr mEncodeMapMax;
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TensorPtr mEncodeMap;
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TensorPtr mSampledTokensMax;
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TensorPtr mSampledTokens;
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//! look ahead algorithm parameters, Window size, Level and Guess set size.
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//! max for reserving resources and current for current request.
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runtime::SizeType32 const mMaxW{0};
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runtime::SizeType32 const mMaxN{0};
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runtime::SizeType32 const mMaxG{0};
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runtime::SizeType32 mW{0};
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runtime::SizeType32 mN{0};
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runtime::SizeType32 mG{0};
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runtime::SizeType32 mRuntimeMaxDraftLen{0};
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runtime::SizeType32 mRuntimeMaxDraftPathLen{0};
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//! in prefilling mode when mFilling < mN-1.
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runtime::SizeType32 mFilling;
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};
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} // namespace tensorrt_llm::layers
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