TensorRT-LLMs/cpp/tensorrt_llm/layers/medusaDecodingLayer.h
2024-09-03 12:14:23 +02:00

90 lines
3.4 KiB
C++

/*
* Copyright (c) 2019-2024, NVIDIA CORPORATION. All rights reserved.
* Copyright (c) 2021, NAVER Corp. Authored by CLOVA.
*
* 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.
*/
#pragma once
#include <curand_kernel.h>
#include "tensorrt_llm/layers/baseLayer.h"
#include "tensorrt_llm/layers/decodingParams.h"
#include "tensorrt_llm/runtime/common.h"
namespace tensorrt_llm::layers
{
//! \brief
template <typename T>
class MedusaDecodingLayer : public BaseLayer
{
public:
using Base = BaseLayer;
using PathsVec = std::vector<std::vector<std::vector<runtime::SizeType32>>>;
MedusaDecodingLayer(DecoderDomain const& decoderDomain, std::shared_ptr<runtime::BufferManager> bufferManager);
void setup(runtime::SizeType32 batchSize, runtime::SizeType32 beamWidth, TensorConstPtr batchSlots,
std::shared_ptr<BaseSetupParams> const& setupParams,
std::shared_ptr<runtime::DecodingLayerWorkspace> const& workspace) override;
void forwardAsync(std::shared_ptr<BaseDecodingOutputs> const& outputs,
std::shared_ptr<BaseDecodingInputs> const& inputs,
std::shared_ptr<runtime::DecodingLayerWorkspace> const& workspace) override;
//! @returns workspace needed for this layer in bytes
[[nodiscard]] size_t getWorkspaceSize() const noexcept override;
private:
void allocateBuffer();
void samplePrimeHeadTokens(SpeculativeDecodingOutputs const& outputs, MedusaDecodingInputs const& inputs,
std::shared_ptr<runtime::DecodingLayerWorkspace> const& workspace);
void acceptDraftTokens(SpeculativeDecodingOutputs const& outputs, MedusaDecodingInputs const& inputs,
std::shared_ptr<runtime::DecodingLayerWorkspace> const& workspace);
void sampleNewDraftTokens(SpeculativeDecodingOutputs const& outputs, MedusaDecodingInputs const& inputs,
std::shared_ptr<runtime::DecodingLayerWorkspace> const& workspace);
void scatterNewDraftTokens(SpeculativeDecodingOutputs const& outputs, MedusaDecodingInputs const& inputs);
void packAcceptedPaths(SpeculativeDecodingOutputs const& outputs, MedusaDecodingInputs const& inputs,
std::shared_ptr<runtime::DecodingLayerWorkspace> const& workspace);
private:
using Base::mDecoderDomain;
size_t mWorkspaceSize{0};
size_t mSetupWorkspaceSize{0};
runtime::SizeType32 mRuntimeMaxTopK{0};
runtime::SizeType32 mRuntimeMaxTopKPerRequestPerMedusaHead{0};
TensorPtr mCurandStatesDevice;
TensorPtr mRuntimeTopKDevice;
TensorPtr mTargetTokensDevice;
TensorPtr mRandomSeedsDevice;
TensorPtr mMedusaSelectedLogitsPtrsDevice;
TensorPtr mCurandStatesMedusaLogitsDevice;
TensorPtr mRuntimeTopKPerRequestPerMedusaHeadDevice;
TensorPtr mNewDraftTokensDevice;
TensorPtr mBestPathIdsDevice;
TensorPtr mTiledBatchSlotsSetup;
TensorPtr mTiledBatchSlotsForward;
TensorPtr mDraftIdsPtrHost;
TensorPtr mMedusaInputLogitsPtrs;
std::vector<runtime::SizeType32> mCummulativeTopK;
};
} // namespace tensorrt_llm::layers