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https://github.com/NVIDIA/TensorRT-LLM.git
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71 lines
2.3 KiB
C++
71 lines
2.3 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/common/tensor.h"
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#include "tensorrt_llm/layers/baseLayer.h"
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#include "tensorrt_llm/layers/beamSearchLayer.h"
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#include "tensorrt_llm/layers/decodingParams.h"
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#include "tensorrt_llm/layers/medusaDecodingLayer.h"
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#include "tensorrt_llm/layers/samplingLayer.h"
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#include "tensorrt_llm/runtime/decodingMode.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 performs token decoding using sampling (beamWidth=1), beam search (beamWidth>1) or Medusa.
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template <typename T>
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class DecodingLayer : public BaseLayer
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{
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public:
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DecodingLayer(runtime::DecodingMode const& mode, DecoderDomain const& decoderDomain, cudaStream_t stream,
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std::shared_ptr<tensorrt_llm::common::IAllocator> allocator);
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~DecodingLayer() override = default;
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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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//! \brief Calls single SamplingLayer::forward in batched mode
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//! or runs BeamSearchLayer::forward in the loop for each request.
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//! Modifies outputs->logits in-place.
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void forward(std::shared_ptr<BaseOutputParams> outputs, std::shared_ptr<BaseInputParams> inputs) override;
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private:
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using BaseLayer::mWorkspaceSize;
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using BaseLayer::mAllocatedSize;
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using BaseLayer::mStream;
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using BaseLayer::mAllocator;
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runtime::DecodingMode mDecodingMode;
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std::unique_ptr<BaseLayer> mDecodingLayer;
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bool mHasDiffRuntimeArgs{false};
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};
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} // namespace layers
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} // namespace tensorrt_llm
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