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https://github.com/NVIDIA/TensorRT-LLM.git
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f430a4b447
* Update TensorRT-LLM --------- Co-authored-by: IbrahimAmin <ibrahimamin532@gmail.com> Co-authored-by: Fabian Joswig <fjosw@users.noreply.github.com> Co-authored-by: Pzzzzz <hello-cd.plus@hotmail.com> Co-authored-by: CoderHam <hemant@cohere.com> Co-authored-by: Konstantin Lopuhin <kostia.lopuhin@gmail.com>
77 lines
2.4 KiB
C++
77 lines
2.4 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 "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/baseLayer.h"
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#include "tensorrt_llm/layers/samplingParams.h"
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#include "tensorrt_llm/runtime/common.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 BaseLayer
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{
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using Base = BaseLayer;
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public:
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TopKSamplingLayer(DecoderDomain const& decoderDomain, cudaStream_t stream,
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std::shared_ptr<tensorrt_llm::common::IAllocator> allocator);
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~TopKSamplingLayer();
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void setup(runtime::SizeType32 batchSize, runtime::SizeType32 beamWidth, runtime::SizeType32 const* batchSlots,
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std::shared_ptr<BaseSetupParams> setupParams) override;
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void forwardAsync(std::shared_ptr<BaseOutputParams> outputs, std::shared_ptr<BaseInputParams> 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::SizeType32 mRuntimeMaxTopK{0};
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runtime::SizeType32* 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::mDecoderDomain;
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using Base::mWorkspaceSize;
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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::SizeType32 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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