mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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90 lines
3.4 KiB
C++
90 lines
3.4 KiB
C++
/*
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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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#pragma once
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#include <curand_kernel.h>
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#include "tensorrt_llm/layers/baseLayer.h"
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#include "tensorrt_llm/layers/decodingParams.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
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template <typename T>
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class MedusaDecodingLayer : public BaseLayer
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{
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public:
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using Base = BaseLayer;
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using PathsVec = std::vector<std::vector<std::vector<runtime::SizeType32>>>;
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MedusaDecodingLayer(DecoderDomain const& decoderDomain, std::shared_ptr<runtime::BufferManager> bufferManager);
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void setup(runtime::SizeType32 batchSize, runtime::SizeType32 beamWidth, TensorConstPtr batchSlots,
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std::shared_ptr<BaseSetupParams> const& setupParams,
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std::shared_ptr<runtime::DecodingLayerWorkspace> const& workspace) override;
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void forwardAsync(std::shared_ptr<BaseDecodingOutputs> const& outputs,
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std::shared_ptr<BaseDecodingInputs> const& inputs,
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std::shared_ptr<runtime::DecodingLayerWorkspace> const& workspace) override;
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//! @returns workspace needed for this layer in bytes
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[[nodiscard]] size_t getWorkspaceSize() const noexcept override;
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private:
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void allocateBuffer();
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void samplePrimeHeadTokens(SpeculativeDecodingOutputs const& outputs, MedusaDecodingInputs const& inputs,
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std::shared_ptr<runtime::DecodingLayerWorkspace> const& workspace);
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void acceptDraftTokens(SpeculativeDecodingOutputs const& outputs, MedusaDecodingInputs const& inputs,
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std::shared_ptr<runtime::DecodingLayerWorkspace> const& workspace);
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void sampleNewDraftTokens(SpeculativeDecodingOutputs const& outputs, MedusaDecodingInputs const& inputs,
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std::shared_ptr<runtime::DecodingLayerWorkspace> const& workspace);
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void scatterNewDraftTokens(SpeculativeDecodingOutputs const& outputs, MedusaDecodingInputs const& inputs);
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void packAcceptedPaths(SpeculativeDecodingOutputs const& outputs, MedusaDecodingInputs const& inputs,
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std::shared_ptr<runtime::DecodingLayerWorkspace> const& workspace);
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private:
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using Base::mDecoderDomain;
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size_t mWorkspaceSize{0};
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size_t mSetupWorkspaceSize{0};
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runtime::SizeType32 mRuntimeMaxTopK{0};
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runtime::SizeType32 mRuntimeMaxTopKPerRequestPerMedusaHead{0};
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TensorPtr mCurandStatesDevice;
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TensorPtr mRuntimeTopKDevice;
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TensorPtr mTargetTokensDevice;
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TensorPtr mRandomSeedsDevice;
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TensorPtr mMedusaSelectedLogitsPtrsDevice;
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TensorPtr mCurandStatesMedusaLogitsDevice;
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TensorPtr mRuntimeTopKPerRequestPerMedusaHeadDevice;
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TensorPtr mNewDraftTokensDevice;
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TensorPtr mBestPathIdsDevice;
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TensorPtr mTiledBatchSlotsSetup;
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TensorPtr mTiledBatchSlotsForward;
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TensorPtr mDraftIdsPtrHost;
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TensorPtr mMedusaInputLogitsPtrs;
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std::vector<runtime::SizeType32> mCummulativeTopK;
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};
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} // namespace tensorrt_llm::layers
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