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d879430b04
* Update TensorRT-LLM --------- Co-authored-by: Shixiaowei02 <39303645+Shixiaowei02@users.noreply.github.com>
117 lines
3.8 KiB
C++
117 lines
3.8 KiB
C++
/*
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* Copyright (c) 2022-2024, 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/topKSamplingLayer.h"
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#include "tensorrt_llm/layers/topPSamplingLayer.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/kernels/penaltyKernels.h"
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#include "tensorrt_llm/kernels/samplingTopKKernels.h"
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#include "tensorrt_llm/kernels/samplingTopPKernels.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/runtimeKernels.h"
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#include "tensorrt_llm/runtime/tllmLogger.h"
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#include "tensorrt_llm/common/cudaAllocator.h"
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#include "tensorrt_llm/common/tensorConversion.h"
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#include "tensorrt_llm/common/tllmException.h"
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namespace tensorrt_llm::tests::layers::sampling
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{
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struct SamplingParams
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{
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std::vector<uint32_t> topKs;
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std::vector<float> topPs;
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std::vector<float> temperatures;
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std::vector<float> repetitionPenalties;
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std::vector<float> presencePenalties;
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std::vector<float> frequencyPenalties;
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std::vector<int32_t> minLengths;
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std::vector<float> decay;
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std::vector<float> minTopP;
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std::vector<int32_t> topPResetIds;
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bool useBias = false;
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};
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template <typename T>
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class SamplingLayerTest : public testing::Test
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{
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protected:
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using TensorPtr = tensorrt_llm::runtime::ITensor::SharedPtr;
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int32_t seed = 0;
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const static uint64_t mMaxSeed = 32;
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const int32_t mBatchSize = 6;
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const int32_t mBeamWidth = 1;
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const int32_t mBatchBeam = mBatchSize * mBeamWidth;
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const int32_t mVocabSize = 8;
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const int32_t mVocabSizePadded = mVocabSize;
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const int32_t mMaxInputLen = 0; // has no effect.
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const int32_t mMaxOutputLen = 4;
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const int32_t mMaxSeqLen = mMaxInputLen + mMaxOutputLen;
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int32_t mEndId = mVocabSize;
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TensorPtr mLogitsDevice;
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TensorPtr mPenaltyWorkspaceDevice;
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TensorPtr mContextLengthDevice;
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TensorPtr mSeqLengthsDevice;
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TensorPtr mFinishedDevice;
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TensorPtr mOutputIdsDevice;
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TensorPtr mEndIdsDevice;
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TensorPtr mIdsPtrHost;
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TensorPtr mEmbeddingBiasHost;
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TensorPtr mEmbeddingBiasDevice;
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TensorPtr mCumLogProbsDevice;
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const tensorrt_llm::common::DataType data_type = tensorrt_llm::common::getTensorType<T>();
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// Order is important because we pass mAllocator to mSamplingLayer and it is used in destructor
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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::common::CudaAllocator> mAllocator;
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std::shared_ptr<tensorrt_llm::layers::BaseSamplingLayer<T>> mSamplingLayer;
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std::vector<T> mTestLogitsInit;
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void setup(uint64_t seed, SamplingParams const& params);
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typename tensorrt_llm::layers::BaseSamplingLayer<T>::ForwardParams createInputTensors(int32_t step);
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tensorrt_llm::layers::DecodingOutputParams createOutputTensors();
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void batchCopy(int32_t step);
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bool checkResult(int32_t* outputIds, std::vector<std::set<int32_t>>& expectedIds);
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public:
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void runTest(std::vector<std::set<int32_t>> expectedOutputIds, SamplingParams const& params, int32_t endId = -1);
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};
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typedef testing::Types<float, half> FloatAndHalfTypes;
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} // namespace tensorrt_llm::tests::layers::sampling
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