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https://github.com/NVIDIA/TensorRT-LLM.git
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80 lines
2.5 KiB
C++
80 lines
2.5 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/memoryUtils.h"
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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 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 TopK logits.
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//! When both TopK and TopP are specified, layer jointly samples using TopK and TopP.
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//! When no TopK param is specified, sampling is skipped for particular request.
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template <typename T>
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class TopKSamplingLayer : 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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TopKSamplingLayer(runtime::SizeType maxBatchSize, runtime::SizeType vocabSize, runtime::SizeType vocabSizePadded,
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cudaStream_t stream, std::shared_ptr<tensorrt_llm::common::IAllocator> allocator);
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~TopKSamplingLayer();
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void setup(
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runtime::SizeType batchSize, runtime::SizeType const* batchSlots, SetupParams const& setupParams) override;
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void forward(DecodingOutputParams& outputs, ForwardParams& inputs) override;
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bool const* 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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bool mNormalizeLogProbs = true;
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runtime::SizeType mRuntimeMaxTopK = 0;
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runtime::SizeType* mRuntimeTopKDevice = nullptr;
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float* mRuntimeTopPDevice = nullptr;
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void* mSetupWorkspaceDevice = nullptr;
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bool* mSkipDecodeDevice = nullptr;
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bool* mSkipDecodeHost = nullptr;
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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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private:
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void allocateBuffer(runtime::SizeType 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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