TensorRT-LLMs/cpp/tensorrt_llm/layers/lookaheadAlgorithm.h
Kaiyu Xie bf0a5afc92
Update TensorRT-LLM (#1598)
* Update TensorRT-LLM
2024-05-14 16:43:41 +08:00

91 lines
4.1 KiB
C++

#pragma once
#include "lookaheadPoolManager.h"
#include "tensorrt_llm/layers/baseLayer.h"
#include "tensorrt_llm/layers/decodingParams.h"
#include "tensorrt_llm/runtime/common.h"
#include <curand_kernel.h>
namespace tensorrt_llm::layers
{
//! @brief An CPU implementation of Lookahead with ITensor.
class LookaheadAlgorithm
{
public:
using TensorPtr = runtime::ITensor::SharedPtr;
//! @brief Currently the resource management is to be aligned with batch manager.
//! @param w, n, g is the Jacobi window, n-gram level and guess set size respectively.
LookaheadAlgorithm(runtime::SizeType32 w, runtime::SizeType32 n, runtime::SizeType32 g,
runtime::TokenIdType endToken, std::shared_ptr<runtime::BufferManager> bufferManager)
: mW(w)
, mN(n)
, mG(g)
, mEndToken(endToken)
, mFilling(0)
, mBufferManager(bufferManager)
, mPoolManager(g, bufferManager)
, mGoldenTokens(mBufferManager->cpu(runtime::ITensor::makeShape({n * 2 - 2}), nvinfer1::DataType::kINT32))
, mPastTokens(mBufferManager->cpu(runtime::ITensor::makeShape({w, n - 1}), nvinfer1::DataType::kINT32))
, mPrefills(mBufferManager->cpu(runtime::ITensor::makeShape({n - 2}), nvinfer1::DataType::kINT32))
{
}
//! @brief setup per request, fill internal states from @param prompt.
void setup(TensorPtr prompt);
//! @brief combine lookahead and guess to prepare the tensors.
//! @param offset is position id of the last golden token.
//! @param lastToken the last golden token for searching in the pool.
//! @return a tuple of <lookahead tokens, position ids, sampling mask>, including the golden token, the lookahead
//! and the verification branch information.
std::tuple<TensorPtr, TensorPtr, TensorPtr> prepare(runtime::SizeType32 offset, runtime::TokenIdType lastToken);
//! @brief update the internal states and generate accepted tokens from @param outputTokens.
//! @param outputTokens is the all the tokens from the language model. The position at samplingMask=1 is valid.
//! @return the longest accepted token tensor, note, at least one.
TensorPtr update(TensorPtr outputTokens);
private:
//! @brief generate lookahead branch information.
//! @param offset the position id of the last golden token.
//! @return a tuple of <lookahead tokens, position ids, sampling mask>.
std::tuple<TensorPtr, TensorPtr, TensorPtr> lookahead(runtime::SizeType32 offset);
//! @brief generate verification branch information. Also save the guessed tokens for future verification.
//! @param offset the position id of the last golden token.
//! @param lastToken the last golden token for searching in the pool.
//! @return a tuple of <lookahead tokens, position ids>.
std::tuple<TensorPtr, TensorPtr> guess(runtime::SizeType32 offset, runtime::TokenIdType lastToken);
//! @brief verify the guessed tokens results and generate the longest accepted tokens.
//! @param newLastToken is the new-generated last golden token.
//! @param goldenTokens is the guessed token results from the language model.
//! @return the longest accepted token tensor, note, at least one.
TensorPtr verify(runtime::TokenIdType newLastToken, TensorPtr goldenTokens);
private:
std::shared_ptr<runtime::BufferManager> mBufferManager;
LookaheadPoolManager mPoolManager;
//! the random prefill tokens, shape [(mN-2)]
TensorPtr mPrefills;
//! shape [mW, (mN-1)], the look ahead branch window
TensorPtr mPastTokens;
//! all the moving tail golden tokens, shape[mN*2-2]
TensorPtr mGoldenTokens;
//! the same guess tokens from `guess` and used in `verify`
TensorPtr mGuessTokens;
//! look ahead algorithm parameters, Window size, Level and Guess set size.
runtime::SizeType32 mW, mN, mG;
//! in prefilling mode when mFilling < mN-1.
runtime::SizeType32 mFilling;
//! the end token for verification early quit.
runtime::TokenIdType mEndToken;
//! @brief record the current golden token for debugging.
runtime::TokenIdType mCurrentToken;
};
} // namespace tensorrt_llm::layers