mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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94 lines
2.9 KiB
C++
94 lines
2.9 KiB
C++
/*
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* Copyright (c) 2022-2023, NVIDIA CORPORATION. All rights reserved.
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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/cudaAllocator.h"
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#include "tensorrt_llm/runtime/bufferManager.h"
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#include "tensorrt_llm/runtime/decodingInput.h"
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#include "tensorrt_llm/runtime/decodingOutput.h"
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#include "tensorrt_llm/runtime/samplingConfig.h"
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#include <cstdint>
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#include <memory>
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#include <NvInferRuntime.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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// Forward declaration
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template <typename T>
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class DynamicDecodeLayer;
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} // namespace layers
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namespace runtime
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{
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class IGptDecoder
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{
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public:
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virtual ~IGptDecoder() = default;
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virtual void setup(SamplingConfig const& samplingConfig, size_t batchSize) = 0;
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virtual bool forward(DecodingOutput& output, DecodingInput const& input) = 0;
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virtual void forwardAsync(DecodingOutput& output, DecodingInput const& input) = 0;
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static void gatherTree(ITensor& finalOutputIds, DecodingOutput const& decodingOutput,
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DecodingInput const& decodingInput, BufferManager const& manager);
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static std::unique_ptr<IGptDecoder> create(
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nvinfer1::DataType dtype, size_t vocabSize, size_t vocabSizePadded, BufferManager::CudaStreamPtr const& stream);
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};
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template <typename T>
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class GptDecoder : public virtual IGptDecoder
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{
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public:
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using CudaStreamPtr = BufferManager::CudaStreamPtr;
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GptDecoder(size_t vocabSize, size_t vocabSizePadded, CudaStreamPtr const& stream);
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void setup(SamplingConfig const& samplingConfig, size_t batchSize) override;
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bool forward(DecodingOutput& output, DecodingInput const& input) override;
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void forwardAsync(DecodingOutput& output, DecodingInput const& input) override;
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private:
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BufferManager mManager;
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common::CudaAllocator mAllocator;
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std::shared_ptr<tensorrt_llm::layers::DynamicDecodeLayer<T>> mDynamicDecodeLayer;
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};
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inline std::unique_ptr<IGptDecoder> IGptDecoder::create(
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nvinfer1::DataType dtype, size_t vocabSize, size_t vocabSizePadded, BufferManager::CudaStreamPtr const& stream)
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{
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switch (dtype)
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{
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case nvinfer1::DataType::kFLOAT: return std::make_unique<GptDecoder<float>>(vocabSize, vocabSizePadded, stream);
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case nvinfer1::DataType::kHALF: return std::make_unique<GptDecoder<half>>(vocabSize, vocabSizePadded, stream);
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default: return nullptr;
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}
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}
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} // namespace runtime
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} // namespace tensorrt_llm
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