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https://github.com/NVIDIA/TensorRT-LLM.git
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* Update TensorRT-LLM --------- Co-authored-by: Denis Kayshev <topenkoff@gmail.com> Co-authored-by: akhoroshev <arthoroshev@gmail.com> Co-authored-by: Patrick Reiter Horn <patrick.horn@gmail.com> Update
174 lines
6.5 KiB
C++
174 lines
6.5 KiB
C++
/*
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* Copyright (c) 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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#include "tensorrt_llm/kernels/logitsBitmask.h"
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#include "tensorrt_llm/runtime/bufferManager.h"
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#include "tensorrt_llm/runtime/iBuffer.h"
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#include <gtest/gtest.h>
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#include <cstdint>
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#include <random>
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namespace tk = tensorrt_llm::kernels;
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namespace tc = tensorrt_llm::common;
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using namespace tensorrt_llm::runtime;
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namespace
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{
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template <typename T>
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class LogitsBitmaskTest : public testing::Test
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{
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public:
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using TensorPtr = ITensor::SharedPtr;
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using BitmaskT = uint32_t;
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void SetUp() override
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{
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mStream = std::make_shared<CudaStream>();
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mBufferManager = std::make_shared<BufferManager>(mStream);
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}
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void TearDown() override {}
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void initData(SizeType32 seed, SizeType32 batchSize, SizeType32 vocabSizePadded)
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{
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std::mt19937 generator(seed);
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std::vector<int32_t> index(batchSize);
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std::iota(index.begin(), index.end(), 0);
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std::shuffle(index.begin(), index.end(), generator);
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std::uniform_int_distribution<BitmaskT> dist(
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std::numeric_limits<BitmaskT>::min(), std::numeric_limits<BitmaskT>::max());
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mBatchSize = batchSize;
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mVocabSizePadded = vocabSizePadded;
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mBitmaskSize = tc::ceilDiv(vocabSizePadded, 32);
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auto constexpr logitsDtype = TRTDataType<T>::value;
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auto constexpr logitsPtrDtype = TRTDataType<T*>::value;
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auto constexpr bitmaskDtype = TRTDataType<BitmaskT>::value;
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auto constexpr bitmaskPtrDtype = TRTDataType<BitmaskT*>::value;
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mLogitsBitmask = mBufferManager->gpu(ITensor::makeShape({mBatchSize, mBitmaskSize}), bitmaskDtype);
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mLogitsBitmaskHost = BufferManager::pinned(ITensor::makeShape({mBatchSize, mBitmaskSize}), bitmaskDtype);
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mLogitsBitmaskPtrVec = mBufferManager->gpu(ITensor::makeShape({mBatchSize}), bitmaskPtrDtype);
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mLogitsBitmaskPtrVecHost = BufferManager::pinned(ITensor::makeShape({mBatchSize}), bitmaskPtrDtype);
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mLogits = mBufferManager->gpu(ITensor::makeShape({mBatchSize, mVocabSizePadded}), logitsDtype);
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mLogitsHost = BufferManager::pinned(ITensor::makeShape({mBatchSize, mVocabSizePadded}), logitsDtype);
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mLogitsPtrVec = mBufferManager->gpu(ITensor::makeShape({mBatchSize}), logitsPtrDtype);
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mLogitsPtrVecHost = BufferManager::pinned(ITensor::makeShape({mBatchSize}), logitsPtrDtype);
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auto logitsHost = BufferRange<T>(*mLogitsHost);
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auto logitsBitmaskHost = BufferRange<BitmaskT>(*mLogitsBitmaskHost);
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auto logitsPtrVecHost = BufferRange<T*>(*mLogitsPtrVecHost);
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auto logitsBitmaskPtrVecHost = BufferRange<BitmaskT*>(*mLogitsBitmaskPtrVecHost);
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for (int i = 0; i < mBatchSize; i++)
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{
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for (int j = 0; j < mVocabSizePadded; j++)
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{
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logitsHost[i * mVocabSizePadded + j] = static_cast<T>(0.0f);
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}
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for (int j = 0; j < mBitmaskSize; j++)
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{
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logitsBitmaskHost[i * mBitmaskSize + j] = dist(generator);
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}
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// Map to randomly shuffled addresses
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logitsPtrVecHost[i] = bufferCast<T>(*ITensor::at(mLogits, {index[i]}));
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logitsBitmaskPtrVecHost[i] = bufferCast<BitmaskT>(*ITensor::at(mLogitsBitmask, {index[i]}));
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}
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mBufferManager->copy(*mLogitsHost, *mLogits);
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mBufferManager->copy(*mLogitsBitmaskHost, *mLogitsBitmask);
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mBufferManager->copy(*mLogitsPtrVecHost, *mLogitsPtrVec);
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mBufferManager->copy(*mLogitsBitmaskPtrVecHost, *mLogitsBitmaskPtrVec);
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}
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void runTest()
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{
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auto logitsPtrVec = bufferCast<T*>(*mLogitsPtrVec);
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auto logitsBitmaskPtrVec = bufferCast<BitmaskT const*>(*mLogitsBitmaskPtrVec);
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tk::invokeLogitsBitmask<T>(logitsPtrVec, logitsBitmaskPtrVec, mBatchSize, mVocabSizePadded, mStream->get());
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mBufferManager->copy(*mLogits, *mLogitsHost);
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mStream->synchronize();
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auto logitsHost = BufferRange<T>(*mLogitsHost);
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auto logitsBitmaskHost = BufferRange<BitmaskT>(*mLogitsBitmaskHost);
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for (int i = 0; i < mBatchSize; i++)
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{
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for (int j = 0; j < mBitmaskSize; j++)
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{
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auto bitmaskVal = logitsBitmaskHost[i * mBitmaskSize + j];
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for (int k = 0; k < 32; k++)
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{
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if (j * 32 + k >= mVocabSizePadded)
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{
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break;
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}
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auto logitsVal = static_cast<float>(logitsHost[i * mVocabSizePadded + j * 32 + k]);
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if (!(bitmaskVal & 1))
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{
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EXPECT_LT(logitsVal, -1e6);
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}
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else
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{
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EXPECT_FLOAT_EQ(logitsVal, 0);
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}
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bitmaskVal >>= 1;
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}
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}
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}
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}
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protected:
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std::shared_ptr<BufferManager> mBufferManager;
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std::shared_ptr<CudaStream> mStream;
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SizeType32 mBatchSize;
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SizeType32 mVocabSizePadded;
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SizeType32 mBitmaskSize; // CeilDiv(vocabSizePadded, 32)
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TensorPtr mLogitsBitmask; // [mBatchSize, mBitmaskSize]
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TensorPtr mLogitsBitmaskHost; // [mBatchSize, mBitmaskSize]
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TensorPtr mLogitsBitmaskPtrVec; // [mBatchSize], pointers to the logitsBitmask in a batch
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TensorPtr mLogitsBitmaskPtrVecHost; // [mBatchSize]
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TensorPtr mLogits; // [mBatchSize, mVocabSizePadded]
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TensorPtr mLogitsHost; // [mBatchSize, mVocabSizePadded]
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TensorPtr mLogitsPtrVec; // [mBatchSize], pointers to the logits in a batch
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TensorPtr mLogitsPtrVecHost; // [mBatchSize]
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};
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using TestingTypes = testing::Types<float, half, __nv_bfloat16>;
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TYPED_TEST_SUITE(LogitsBitmaskTest, TestingTypes);
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TYPED_TEST(LogitsBitmaskTest, Aligned)
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{
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this->initData(0, 16, 128000);
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this->runTest();
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}
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TYPED_TEST(LogitsBitmaskTest, NotAligned)
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{
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this->initData(515, 123, 1234);
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this->runTest();
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}
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} // namespace
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