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https://github.com/NVIDIA/TensorRT-LLM.git
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* Update TensorRT-LLM --------- Co-authored-by: Shixiaowei02 <39303645+Shixiaowei02@users.noreply.github.com>
177 lines
7.6 KiB
C++
177 lines
7.6 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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#ifndef TOP_LEVEL_DIR
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#error "Define TOP_LEVEL_DIR"
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#endif
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#include "tests/kernels/sampling/samplingTest.h"
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#include <random>
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namespace tc = tensorrt_llm::common;
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namespace tk = tensorrt_llm::kernels;
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namespace trk = tensorrt_llm::runtime::kernels;
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using namespace tensorrt_llm::runtime;
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using namespace tensorrt_llm::tests::kernels::sampling;
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namespace
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{
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template <typename T>
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class TopPSamplingKernelTest : public SamplingKernelTest<T>
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{
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protected:
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const int32_t endId = 0;
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using SamplingKernelTest<T>::mSeed;
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using SamplingKernelTest<T>::mStream;
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using SamplingKernelTest<T>::mBufferManager;
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private:
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size_t getWorkspaceSize(const SamplingKernelTestParam& params) override
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{
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size_t workspaceSize;
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size_t cubTempStorageSize;
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tk::invokeBatchTopPSampling<T>(nullptr, // workspace
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workspaceSize, cubTempStorageSize,
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nullptr, // output_ids
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nullptr, // sequence_length
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nullptr, // finished_buffer
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nullptr, // finished_buffer
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nullptr, // cum_log_probs
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nullptr, // output_log_probs
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nullptr, // log_probs
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bufferCast<int32_t>(*this->mTopPIdValsDevice), bufferCast<int32_t>(*this->mEndOffsetsDevice),
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bufferCast<int32_t>(*this->mBeginOffsetsDevice), this->mCurandStatesDevice, params.batchSize,
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params.vocabSize, nullptr, this->mMaxTopP, bufferCast<float>(*this->mTopPsDevice), this->mStream->get(),
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nullptr);
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return workspaceSize;
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}
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void callTestedFunction(const SamplingKernelTestParam& params, bool hasDiffRuntimeArgs, size_t workspaceSize,
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tensorrt_llm::runtime::ITensor::SharedPtr& workspaceDevice) override
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{
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size_t cubTempStorageSize;
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tk::invokeBatchTopPSampling<T>(nullptr, // workspace
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workspaceSize, cubTempStorageSize,
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nullptr, // output_ids
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nullptr, // sequence_length
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nullptr, // finished_buffer
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nullptr, // finished_buffer
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nullptr, // cum_log_probs
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nullptr, // output_log_probs
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nullptr, // log_probs
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bufferCast<int32_t>(*this->mTopPIdValsDevice), bufferCast<int32_t>(*this->mEndOffsetsDevice),
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bufferCast<int32_t>(*this->mBeginOffsetsDevice), this->mCurandStatesDevice, params.batchSize,
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params.vocabSize, nullptr, this->mMaxTopP, bufferCast<float>(*this->mTopPsDevice), this->mStream->get(),
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nullptr);
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// Perform batched TopK sampling
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tk::invokeTopPInitialize(bufferCast<int32_t>(*this->mTopPIdValsDevice),
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bufferCast<int32_t>(*this->mEndOffsetsDevice), bufferCast<int32_t>(*this->mBeginOffsetsDevice),
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params.batchSize, params.vocabSize, this->mStream->get());
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// Perform batched TopP sampling
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tk::invokeBatchTopPSampling<T>(workspaceDevice->data(), workspaceSize, cubTempStorageSize,
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bufferCast<int*>(*this->mIdsPtrHost), bufferCast<int32_t>(*this->mSeqLengthsDevice),
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bufferCast<bool>(*this->mFinishedDevice), bufferCast<bool>(*this->mFinishedDevice),
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bufferCast<float>(*this->mCumLogProbsDevice), bufferCast<float>(*this->mOutputLogProbsDevice),
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// Note that the kernel needs vocab probs instead of
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// log-prob if cum_log_probs or output_log_probs are
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// provided. It's because the sampling layer already
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// preprocesses log_prob_buf when those are provided.
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bufferCast<T>(*this->mProbsDevice), bufferCast<int32_t>(*this->mTopPIdValsDevice),
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bufferCast<int32_t>(*this->mEndOffsetsDevice), bufferCast<int32_t>(*this->mBeginOffsetsDevice),
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this->mCurandStatesDevice, params.batchSize, params.vocabSize, bufferCast<int32_t>(*this->mEndIdsDevice),
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this->mMaxTopP, hasDiffRuntimeArgs ? bufferCast<float>(*this->mTopPsDevice) : nullptr, this->mStream->get(),
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bufferCast<bool>(*this->mSkipDecodeDevice));
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}
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};
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TYPED_TEST_SUITE(TopPSamplingKernelTest, FloatAndHalfTypes);
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TYPED_TEST(TopPSamplingKernelTest, CorrectnessSmallP)
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{
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this->runTest(SamplingKernelTestParam().setBatchSize(6).setVocabSize(4).setTopK(0).setTopP(0.2f).setOutputLen(1));
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};
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TYPED_TEST(TopPSamplingKernelTest, CorrectnessLargeP)
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{
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this->runTest(SamplingKernelTestParam().setBatchSize(6).setVocabSize(4).setTopK(0).setTopP(0.9f).setOutputLen(1));
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};
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TYPED_TEST(TopPSamplingKernelTest, CorrectnessAncestral)
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{
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this->runTest(SamplingKernelTestParam().setBatchSize(6).setVocabSize(4).setTopK(0).setTopP(1.0f).setOutputLen(1));
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};
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TYPED_TEST(TopPSamplingKernelTest, CorrectnessLargeVocabSmallP)
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{
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this->runTest(
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SamplingKernelTestParam().setBatchSize(32).setVocabSize(51200).setTopK(0).setTopP(0.2f).setOutputLen(16));
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};
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TYPED_TEST(TopPSamplingKernelTest, CorrectnessLargeVocabLargeP)
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{
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this->runTest(
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SamplingKernelTestParam().setBatchSize(32).setVocabSize(51200).setTopK(0).setTopP(0.9f).setOutputLen(16));
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};
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class TopPSamplingKernelUtilsTest : public SamplingKernelTest<float>
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{
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};
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TEST_F(TopPSamplingKernelUtilsTest, invokeTopPInitialize)
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{
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const int32_t batchSize = 8;
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const int32_t vocabSize = 256;
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const auto topPIdValsDevice
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= this->mBufferManager->gpu(ITensor::makeShape({batchSize, vocabSize}), nvinfer1::DataType::kINT32);
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const auto beginOffsetsDevice
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= this->mBufferManager->gpu(ITensor::makeShape({batchSize + 1}), nvinfer1::DataType::kINT32);
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const auto endOffsetsDevice
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= this->mBufferManager->gpu(ITensor::makeShape({batchSize + 1}), nvinfer1::DataType::kINT32);
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tk::invokeTopPInitialize(bufferCast<int32_t>(*topPIdValsDevice), bufferCast<int32_t>(*endOffsetsDevice),
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bufferCast<int32_t>(*beginOffsetsDevice), batchSize, vocabSize, this->mStream->get());
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const auto topPIdValsHost = this->mBufferManager->copyFrom(*topPIdValsDevice, MemoryType::kCPU);
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const auto endOffsetsHost = this->mBufferManager->copyFrom(*endOffsetsDevice, MemoryType::kCPU);
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const auto beginOffsetsHost = this->mBufferManager->copyFrom(*beginOffsetsDevice, MemoryType::kCPU);
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this->mStream->synchronize();
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const auto topPIdValsHostPtr = bufferCast<int32_t>(*topPIdValsHost);
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const auto endOffsetsHostPtr = bufferCast<int32_t>(*endOffsetsHost);
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const auto beginOffsetsHostPtr = bufferCast<int32_t>(*beginOffsetsHost);
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for (int32_t bi = 0; bi < batchSize + 1; ++bi)
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{
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EXPECT_EQ(endOffsetsHostPtr[bi], bi * vocabSize);
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EXPECT_EQ(beginOffsetsHostPtr[bi], bi * vocabSize);
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}
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for (int32_t bi = 0; bi < batchSize; ++bi)
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{
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for (int32_t vi = 0; vi < vocabSize; ++vi)
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{
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EXPECT_EQ(topPIdValsHostPtr[bi * vocabSize + vi], vi);
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}
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}
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};
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} // end of namespace
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