mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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90 lines
2.8 KiB
C++
90 lines
2.8 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 "tensorrt_llm/common/tensor.h"
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#include "tensorrt_llm/kernels/decodingCommon.h"
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#include "tensorrt_llm/layers/baseSamplingLayer.h"
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namespace tc = tensorrt_llm::common;
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namespace tensorrt_llm
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{
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namespace layers
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{
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//! \brief Layer to randomly sample tokens from TopP logits.
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//! Layer expects probs precomputed in "logits" tensor
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template <typename T>
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class TopPSamplingLayer : public BaseSamplingLayer<T>
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{
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public:
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using Base = BaseSamplingLayer<T>;
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using SetupParams = typename Base::SetupParams;
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using ForwardParams = typename Base::ForwardParams;
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TopPSamplingLayer(std::size_t maxBatchSize, std::size_t vocabSize, std::size_t vocabSizePadded, cudaStream_t stream,
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std::shared_ptr<tensorrt_llm::common::IAllocator> allocator, cudaDeviceProp* prop, bool isDeterministic = true);
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~TopPSamplingLayer();
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void setup(std::size_t batchSize, int32_t const* batchSlots, SetupParams const& setupParams) override;
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void forward(DecodingOutputParams& outputs, ForwardParams& inputs) override;
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const bool* getSkipDecodeHost() const
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{
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return mSkipDecodeHost;
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}
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protected:
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uint32_t* mRuntimeTopKDevice = nullptr;
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float* mRuntimeTopPDevice = nullptr;
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float mRuntimeMaxTopP{0.f};
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float* mInitialTopPDevice = nullptr;
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float* mTopPDecayDevice = nullptr;
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float* mTopPMinDevice = nullptr;
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int32_t* mTopPResetIdsDevice = nullptr;
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void* mSetupWorkspaceDevice = nullptr;
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int32_t* mTopPIdValsDevice = nullptr;
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int32_t* mTopPOffsetDevice = nullptr;
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int32_t* mBeginTopPOffsetDevice = nullptr;
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bool* mSkipDecodeDevice = nullptr;
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bool* mSkipDecodeHost = nullptr;
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size_t mCubTempStorageSize;
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bool mIsDeterministic = true;
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int mAirTopPBlockNum;
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using Base::mMaxBatchSize;
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using Base::mVocabSize;
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using Base::mVocabSizePadded;
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using Base::mSamplingWorkspaceSize;
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using Base::mAllocatedSize;
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using Base::mStream;
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using Base::mAllocator;
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using Base::mCudaDeviceProp;
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private:
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void allocateBuffer(std::size_t batchSize);
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void freeBuffer();
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};
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} // namespace layers
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} // namespace tensorrt_llm
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