mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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118 lines
4.0 KiB
C++
118 lines
4.0 KiB
C++
/*
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* Copyright (c) 2023-2024, 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 <gtest/gtest.h>
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#include <memory>
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#include "tensorrt_llm/layers/medusaDecodingLayer.h"
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#include "tensorrt_llm/runtime/bufferManager.h"
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#include "tensorrt_llm/runtime/cudaStream.h"
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#include "tensorrt_llm/runtime/bufferManager.h"
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#include "tensorrt_llm/runtime/cudaStream.h"
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namespace tensorrt_llm::tests::layers
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{
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struct SamplingParams
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{
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tensorrt_llm::runtime::SizeType32 batchSize;
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std::vector<tensorrt_llm::runtime::SizeType32> runtimeTopK;
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std::vector<std::vector<tensorrt_llm::runtime::SizeType32>> runtimeHeadsTopK;
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std::vector<std::vector<tensorrt_llm::runtime::TokenIdType>> draftIds;
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std::vector<std::vector<tensorrt_llm::runtime::SizeType32>> paths;
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std::vector<std::vector<tensorrt_llm::runtime::SizeType32>> treeIds;
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std::vector<tensorrt_llm::runtime::SizeType32> tokensPerStep;
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std::vector<tensorrt_llm::runtime::SizeType32> acceptedCumSum;
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std::vector<tensorrt_llm::runtime::SizeType32> packedPaths;
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std::optional<tensorrt_llm::runtime::TokenIdType> endId;
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};
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template <typename T>
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class MedusaDecodingLayerTest : public testing::Test
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{
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private:
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void SetUp() override;
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public:
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using TensorPtr = tensorrt_llm::runtime::ITensor::SharedPtr;
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using BufferPtr = tensorrt_llm::runtime::IBuffer::SharedPtr;
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using SizeType32 = tensorrt_llm::runtime::SizeType32;
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using TokenIdType = tensorrt_llm::runtime::TokenIdType;
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private:
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SizeType32 mBatchSize{6};
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SizeType32 mMaxBatchSize{2 * mBatchSize};
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SizeType32 const mVocabSize{9};
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SizeType32 const mVocabSizePadded{mVocabSize};
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SizeType32 const mMaxDecodingTokens{12};
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SizeType32 const mMaxDraftPathLen{4};
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SizeType32 const mMaxSeqLen{mMaxDecodingTokens};
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TokenIdType mEndId{mVocabSize};
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bool mUseLogitsVec{false};
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TensorPtr mTargetLogitsDevice;
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TensorPtr mMedusaLogitsDevice;
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TensorPtr mFinishedDevice;
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TensorPtr mSeqLengthsDevice;
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TensorPtr mAcceptedLengths;
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TensorPtr mOutputIdsDevice;
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TensorPtr mNextDraftTokensDevice;
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TensorPtr mPathsDevice;
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TensorPtr mTreeIdsDevice;
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TensorPtr mAcceptedLengthCumSumDevice;
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TensorPtr mPackedPathsDevice;
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TensorPtr mEndIdsDevice;
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TensorPtr mBatchSlots;
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TensorPtr mTokensPerStepDevice;
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std::vector<TensorPtr> mLogitsVec;
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std::shared_ptr<tensorrt_llm::runtime::CudaStream> mStream;
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std::shared_ptr<tensorrt_llm::runtime::BufferManager> mBufferManager;
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std::shared_ptr<tensorrt_llm::layers::MedusaDecodingLayer<T>> mMedusaDecodingLayer;
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std::shared_ptr<runtime::DecodingLayerWorkspace> mDecodingWorkspace;
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private:
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void allocateBuffers();
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void setup(SamplingParams& params);
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std::shared_ptr<tensorrt_llm::layers::MedusaDecodingInputs> createInputTensors();
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std::shared_ptr<tensorrt_llm::layers::SpeculativeDecodingOutputs> createOutputTensors();
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void checkResult(std::vector<std::vector<std::set<TokenIdType>>> const& expectedOutTokens,
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std::vector<std::vector<TokenIdType>> const& expectedDraftTokens, std::vector<bool> const& finished,
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SamplingParams& params);
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public:
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void runTest(std::vector<std::vector<std::set<TokenIdType>>> const& expectedOutTokens,
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std::vector<std::vector<TokenIdType>> const& expectedDraftTokens, std::vector<bool> const& finished,
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SamplingParams& params);
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};
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typedef testing::Types<float, half> FloatAndHalfTypes;
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} // namespace tensorrt_llm::tests::layers
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