TensorRT-LLMs/cpp/tests/layers/dynamicDecodeLayerTest.h
Kaiyu Xie 0f041b7b57
Update TensorRT-LLM (#1098)
* Update TensorRT-LLM

* update submodule

* Remove unused binaries
2024-02-18 15:48:08 +08:00

150 lines
5.0 KiB
C++

/*
* Copyright (c) 2022-2024, NVIDIA CORPORATION. All rights reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#pragma once
#include <gtest/gtest.h>
#include <memory>
#include "tensorrt_llm/layers/dynamicDecodeLayer.h"
#include "tensorrt_llm/runtime/bufferManager.h"
#include "tensorrt_llm/runtime/cudaStream.h"
#include "tensorrt_llm/kernels/penaltyKernels.h"
#include "tensorrt_llm/kernels/samplingTopKKernels.h"
#include "tensorrt_llm/kernels/samplingTopPKernels.h"
#include "tensorrt_llm/runtime/bufferManager.h"
#include "tensorrt_llm/runtime/cudaStream.h"
#include "tensorrt_llm/runtime/runtimeKernels.h"
#include "tensorrt_llm/runtime/tllmLogger.h"
#include "tensorrt_llm/common/cudaAllocator.h"
#include "tensorrt_llm/common/tensorConversion.h"
#include "tensorrt_llm/common/tllmException.h"
namespace tensorrt_llm::tests::layers::sampling
{
struct SamplingParams
{
std::vector<uint32_t> topKs;
std::vector<float> topPs;
std::vector<float> temperatures;
std::vector<float> repetitionPenalties;
std::vector<float> presencePenalties;
std::vector<float> frequencyPenalties;
std::vector<int32_t> minLengths;
std::vector<float> decay;
std::vector<float> minTopP;
std::vector<int32_t> topPResetIds;
std::vector<std::vector<std::vector<int32_t>>> badWords;
std::vector<std::vector<std::vector<int32_t>>> stopWords;
bool useBias = false;
};
template <typename T>
class DynamicDecodeLayerTest : public testing::Test
{
private:
void SetUp() override;
using TensorPtr = tensorrt_llm::runtime::ITensor::SharedPtr;
using BufferPtr = tensorrt_llm::runtime::IBuffer::SharedPtr;
int32_t seed = 0;
const static uint64_t mMaxSeed = 32;
int32_t const mBatchSize = 6;
int32_t const mMaxBatchSize = 2 * mBatchSize;
int32_t const mBeamWidth = 1;
int32_t const mBatchBeam = mBatchSize * mBeamWidth;
int32_t const mVocabSize = 8;
int32_t const mVocabSizePadded = mVocabSize;
int32_t const mMaxInputLen = 0; // has no effect.
int32_t const mMaxOutputLen = 4;
int32_t const mMaxSeqLen = mMaxInputLen + mMaxOutputLen;
int32_t const mSinkTokenLength = 0;
int32_t mEndId = mVocabSize;
bool mUseLogitsVec = false;
TensorPtr mLogitsDevice;
TensorPtr mLogitsRefHost;
TensorPtr mContextLengthDevice;
TensorPtr mSeqLengthsDevice;
TensorPtr mFinishedDevice;
TensorPtr mFinishedSumDevice;
TensorPtr mOutputIdsDevice;
TensorPtr mNewTokens;
TensorPtr mEndIdsDevice;
TensorPtr mBatchSlots;
TensorPtr mBadWordsLens;
TensorPtr mBadWords;
TensorPtr mBadWordsPtrs;
TensorPtr mStopWordsLens;
TensorPtr mStopWords;
TensorPtr mStopWordsPtrs;
TensorPtr mEmbeddingBiasHost;
TensorPtr mEmbeddingBiasDevice;
TensorPtr mCumLogProbsDevice;
std::vector<tensorrt_llm::common::Tensor> mLogitsVec;
struct cudaDeviceProp mDeviceProp;
const tensorrt_llm::common::DataType data_type = tensorrt_llm::common::getTensorType<T>();
// Order is important because we pass mAllocator to mDecodeLayer and it is used in destructor
std::shared_ptr<tensorrt_llm::runtime::CudaStream> mStream;
std::shared_ptr<tensorrt_llm::runtime::BufferManager> mBufferManager;
std::shared_ptr<tensorrt_llm::common::CudaAllocator> mAllocator;
std::shared_ptr<tensorrt_llm::layers::DynamicDecodeLayer<T>> mDecodeLayer;
std::vector<T> mTestLogitsInit;
int32_t mMaxBadWordsLen{0};
int32_t mMaxStopWordsLen{0};
private:
void setup(uint64_t seed, SamplingParams const& params);
int32_t getMaxWordsLen(std::vector<std::vector<std::vector<int32_t>>> const& inputWords);
void initXWordsTensors(int32_t* batchSlotsPtr, int32_t* wordsData, int32_t** wordsPtr, int32_t* wordsLenData,
int32_t maxWordsLen, std::vector<std::vector<std::vector<int32_t>>> const& inputWords);
typename tensorrt_llm::layers::DynamicDecodeLayer<T>::ForwardParams createInputTensors(int32_t step);
typename tensorrt_llm::layers::DynamicDecodeLayer<T>::OutputParams createOutputTensors();
void batchCopy(int32_t step);
bool checkResult(int32_t* outputIds, std::vector<std::set<int32_t>>& expectedIds, int32_t* seqLens,
int32_t leadingDim, int32_t stride, int32_t step);
void runTestImpl(
std::vector<std::set<int32_t>> expectedOutputIds, SamplingParams const& params, int32_t endId = -1);
public:
void runTest(std::vector<std::set<int32_t>> expectedOutputIds, SamplingParams const& params, int32_t endId = -1);
};
typedef testing::Types<float, half> FloatAndHalfTypes;
} // namespace tensorrt_llm::tests::layers::sampling