mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
synced 2026-01-14 06:27:45 +08:00
587d063e6d
* Update TensorRT-LLM --------- Co-authored-by: Shixiaowei02 <39303645+Shixiaowei02@users.noreply.github.com>
511 lines
15 KiB
C++
511 lines
15 KiB
C++
/*
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* SPDX-FileCopyrightText: Copyright (c) 1993-2022 NVIDIA CORPORATION &
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* AFFILIATES. All rights reserved. SPDX-License-Identifier: Apache-2.0
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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 "gemmPlugin.h"
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using namespace nvinfer1;
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using namespace tensorrt_llm::common;
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using tensorrt_llm::plugins::GemmPluginCreator;
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using tensorrt_llm::plugins::GemmPlugin;
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using tensorrt_llm::plugins::CublasLtGemmPluginProfiler;
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using tensorrt_llm::plugins::CublasGemmWrapperPtr;
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using tensorrt_llm::plugins::read;
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using tensorrt_llm::plugins::write;
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static const char* GEMM_PLUGIN_VERSION{"1"};
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static const char* GEMM_PLUGIN_NAME{"Gemm"};
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PluginFieldCollection GemmPluginCreator::mFC{};
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std::vector<nvinfer1::PluginField> GemmPluginCreator::mPluginAttributes;
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void getProblemParams(cublasOperation_t& transa, cublasOperation_t& transb, int& m, int& n, int& k, int& lda, int& ldb,
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int& ldc, bool transA, bool transB, int M, int N, int K)
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{
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transa = transB ? CUBLAS_OP_T : CUBLAS_OP_N;
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transb = transA ? CUBLAS_OP_T : CUBLAS_OP_N;
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m = N;
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n = M;
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k = K;
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lda = transB ? K : N;
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ldb = transA ? M : K;
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ldc = N;
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}
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void runGemm(const int M, const int N, const int K, const bool transA, const bool transB, const nvinfer1::DataType type,
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const CublasGemmWrapperPtr& cublasWrapperPtr, const void* act, const void* weight, void* output,
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const std::optional<cublasLtMatmulHeuristicResult_t>& heuristic, void* workspace, cudaStream_t stream)
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{
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cublasWrapperPtr->setStream(stream);
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cublasWrapperPtr->setWorkspace(workspace);
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cublasOperation_t transa, transb;
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int m, n, k;
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int lda, ldb, ldc;
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getProblemParams(transa, transb, m, n, k, lda, ldb, ldc, transA, transB, M, N, K);
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cublasWrapperPtr->createDescriptors(transa, transb, m, n, k, lda, ldb, ldc);
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cublasWrapperPtr->Gemm(transa, transb, m, n, k, weight, lda, act, ldb, output, ldc, heuristic);
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cublasWrapperPtr->destroyDescriptors();
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}
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void CublasLtGemmPluginProfiler::runTactic(
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int m, int n, int k, const CublasLtGemmPluginProfiler::Config& tactic, char* workspace, const cudaStream_t& stream)
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{
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size_t dataSize = sizeof(half);
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if (mType == DataType::kFLOAT)
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{
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dataSize = sizeof(float);
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}
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void* actPtr = reinterpret_cast<void*>(workspace);
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void* weightPtr = reinterpret_cast<void*>(
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nextWorkspacePtrWithAlignment(reinterpret_cast<int8_t*>(actPtr), m * k * dataSize, ALIGNMENT));
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void* outputPtr = reinterpret_cast<void*>(
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nextWorkspacePtrWithAlignment(reinterpret_cast<int8_t*>(weightPtr), n * k * dataSize, ALIGNMENT));
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char* workspacePtr = reinterpret_cast<char*>(
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nextWorkspacePtrWithAlignment(reinterpret_cast<int8_t*>(outputPtr), m * n * dataSize, ALIGNMENT));
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runGemm(m, n, k, mTransA, mTransB, mType, mRunner, actPtr, weightPtr, outputPtr, {tactic}, workspacePtr, stream);
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}
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bool CublasLtGemmPluginProfiler::checkTactic(int m, int n, int k, const Config& tactic) const
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{
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cublasOperation_t transa, transb;
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int M = m, N = n, K = k;
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int lda, ldb, ldc;
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getProblemParams(transa, transb, m, n, k, lda, ldb, ldc, mTransA, mTransB, M, N, K);
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mRunner->createDescriptors(transa, transb, m, n, k, lda, ldb, ldc);
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const auto checkResult = mRunner->checkTactic(transa, transb, m, n, k, lda, ldb, ldc, tactic.algo);
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mRunner->destroyDescriptors();
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return checkResult;
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}
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void CublasLtGemmPluginProfiler::computeTmpSize(int maxM, int n, int k)
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{
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size_t dataSize = sizeof(half);
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if (mType == DataType::kFLOAT)
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{
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dataSize = sizeof(float);
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}
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std::vector<size_t> workspaces = {
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maxM * k * dataSize, // A
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n * k * dataSize, // B
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maxM * n * dataSize, // C
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CUBLAS_WORKSPACE_SIZE // workspace
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};
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size_t bytes = calculateTotalWorkspaceSize(workspaces.data(), workspaces.size(), ALIGNMENT);
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setTmpWorkspaceSizeInBytes(bytes);
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}
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std::vector<CublasLtGemmPluginProfiler::Config> CublasLtGemmPluginProfiler::getTactics(int M, int N, int K) const
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{
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cublasOperation_t transa, transb;
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int m, n, k;
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int lda, ldb, ldc;
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getProblemParams(transa, transb, m, n, k, lda, ldb, ldc, mTransA, mTransB, M, N, K);
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mRunner->createDescriptors(transa, transb, m, n, k, lda, ldb, ldc);
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const auto heruistics = mRunner->getTactics(transa, transb, m, n, k, lda, ldb, ldc);
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mRunner->destroyDescriptors();
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return heruistics;
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}
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GemmPlugin::GemmPlugin(
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int transA, int transB, nvinfer1::DataType type, bool useFp8, const GemmPlugin::PluginProfilerPtr& pluginProfiler)
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: mTransA(transA)
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, mTransB(transB)
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, mType(type)
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, mUseFp8(useFp8)
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, mPluginProfiler(pluginProfiler)
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{
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init();
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}
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// Parameterized constructor
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GemmPlugin::GemmPlugin(const void* data, size_t length, const GemmPlugin::PluginProfilerPtr& pluginProfiler)
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: mPluginProfiler(pluginProfiler)
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{
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const char *d = reinterpret_cast<const char*>(data), *a = d;
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read(d, mTransA);
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read(d, mTransB);
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read(d, mType);
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read(d, mUseFp8);
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read(d, mDims);
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init();
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mPluginProfiler->deserialize(d, mDims, mGemmId);
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TLLM_CHECK(d == a + length);
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}
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void GemmPlugin::init()
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{
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auto cublasHandle = getCublasHandle();
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auto cublasLtHandle = getCublasLtHandle();
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mCublasWrapper = std::make_shared<CublasMMWrapper>(cublasHandle, cublasLtHandle, nullptr, nullptr);
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mPluginProfiler->setTranspose(mTransA, mTransB);
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mGemmId = GemmIdCublas(mDims.n, mDims.k, mType, mTransA, mTransB);
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}
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void GemmPlugin::setGemmConfig()
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{
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if (mType == DataType::kHALF)
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{
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mCublasWrapper->setFP16GemmConfig();
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}
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else if (mType == DataType::kFLOAT)
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{
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mCublasWrapper->setFP32GemmConfig();
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}
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#ifdef ENABLE_BF16
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else if (mType == DataType::kBF16)
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{
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mCublasWrapper->setBF16GemmConfig();
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}
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#endif
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#ifdef ENABLE_FP8
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if (mUseFp8)
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{
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mCublasWrapper->setFP8GemmConfig(trtToCublasDtype(mType));
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}
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#endif
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}
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void GemmPlugin::configGemm()
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{
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if (!mDims.isInitialized())
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{
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return;
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}
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setGemmConfig();
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mPluginProfiler->profileTactics(mCublasWrapper, mType, mDims, mGemmId);
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}
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// IPluginV2DynamicExt Methods
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nvinfer1::IPluginV2DynamicExt* GemmPlugin::clone() const noexcept
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{
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auto* plugin = new GemmPlugin(*this);
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return plugin;
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}
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nvinfer1::DimsExprs GemmPlugin::getOutputDimensions(
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int outputIndex, const nvinfer1::DimsExprs* inputs, int nbInputs, nvinfer1::IExprBuilder& exprBuilder) noexcept
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{
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try
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{
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TLLM_CHECK(nbInputs == 2);
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TLLM_CHECK(outputIndex == 0);
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const int nbDimsA = inputs[0].nbDims;
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const int nbDimsB = inputs[1].nbDims;
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DimsExprs ret;
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ret.nbDims = nbDimsA + nbDimsB - 2;
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if (mTransA)
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{
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for (int i = 1; i < nbDimsA; ++i)
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{
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ret.d[i - 1] = inputs[0].d[i];
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}
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}
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else
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{
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for (int i = 0; i < nbDimsA - 1; ++i)
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{
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ret.d[i] = inputs[0].d[i];
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}
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}
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if (mTransB)
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{
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for (int i = 0; i < nbDimsB - 1; ++i)
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{
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ret.d[nbDimsA - 1 + i] = inputs[1].d[i];
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}
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}
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else
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{
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for (int i = 1; i < nbDimsB; ++i)
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{
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ret.d[nbDimsA - 2 + i] = inputs[1].d[i];
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}
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}
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return ret;
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}
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catch (const std::exception& e)
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{
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caughtError(e);
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}
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return DimsExprs{};
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}
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bool GemmPlugin::supportsFormatCombination(
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int pos, const nvinfer1::PluginTensorDesc* inOut, int nbInputs, int nbOutputs) noexcept
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{
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return (inOut[pos].type == mType) && (inOut[pos].format == TensorFormat::kLINEAR);
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}
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int32_t computeMDimension(bool transA, const int32_t nbDims, const int32_t* dims)
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{
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int32_t M = 1;
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if (transA)
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{
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for (int i = nbDims - 1; i > 0; --i)
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{
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M *= dims[i];
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}
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}
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else
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{
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for (int i = 0; i < nbDims - 1; ++i)
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{
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M *= dims[i];
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}
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}
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return M;
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}
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int32_t computeNDimension(bool transB, const int32_t nbDims, const int32_t* dims)
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{
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int32_t N = 1;
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if (transB)
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{
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for (int i = 0; i < nbDims - 1; ++i)
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{
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N *= dims[i];
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}
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}
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else
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{
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for (int i = nbDims - 1; i > 0; --i)
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{
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N *= dims[i];
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}
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}
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return N;
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}
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void GemmPlugin::configurePlugin(const nvinfer1::DynamicPluginTensorDesc* in, int nbInputs,
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const nvinfer1::DynamicPluginTensorDesc* out, int nbOutputs) noexcept
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{
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const int nbDimsA = in[0].max.nbDims;
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const int nbDimsB = in[1].max.nbDims;
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const auto minM = computeMDimension(mTransA, nbDimsA, in[0].min.d);
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const auto maxM = computeMDimension(mTransA, nbDimsA, in[0].max.d);
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const auto N = computeNDimension(mTransB, nbDimsB, in[1].max.d);
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const auto K = mTransA ? in[0].max.d[0] : in[0].max.d[nbDimsA - 1];
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if (!mDims.isInitialized())
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{
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mDims = {minM, maxM, N, K};
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}
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mGemmId.n = N;
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mGemmId.k = K;
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}
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size_t GemmPlugin::getWorkspaceSize(const nvinfer1::PluginTensorDesc* inputs, int nbInputs,
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const nvinfer1::PluginTensorDesc* outputs, int nbOutputs) const noexcept
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{
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return CUBLAS_WORKSPACE_SIZE;
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}
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int GemmPlugin::enqueue(const nvinfer1::PluginTensorDesc* inputDesc, const nvinfer1::PluginTensorDesc* outputDesc,
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const void* const* inputs, void* const* outputs, void* workspace, cudaStream_t stream) noexcept
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{
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// inputs
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// mat1 [M, K] (mTransA = False)
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// mat2 [K, N] (mTransB = False)
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// outputs
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// mat [M, N]
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setGemmConfig();
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const int nbDimsA = inputDesc[0].dims.nbDims;
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const int nbDimsB = inputDesc[1].dims.nbDims;
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const auto M = computeMDimension(mTransA, nbDimsA, inputDesc[0].dims.d);
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const auto N = computeNDimension(mTransB, nbDimsB, inputDesc[1].dims.d);
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const int K = mTransA ? inputDesc[0].dims.d[0] : inputDesc[0].dims.d[nbDimsA - 1];
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auto bestTactic = mPluginProfiler->getBestConfig(M, mGemmId);
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runGemm(M, N, K, mTransA, mTransB, mType, mCublasWrapper, inputs[0], inputs[1], outputs[0], bestTactic, workspace,
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stream);
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return 0;
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}
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// IPluginV2Ext Methods
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nvinfer1::DataType GemmPlugin::getOutputDataType(
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int index, const nvinfer1::DataType* inputTypes, int nbInputs) const noexcept
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{
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TLLM_CHECK(index == 0);
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return inputTypes[0];
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}
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// IPluginV2 Methods
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const char* GemmPlugin::getPluginType() const noexcept
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{
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return GEMM_PLUGIN_NAME;
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}
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const char* GemmPlugin::getPluginVersion() const noexcept
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{
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return GEMM_PLUGIN_VERSION;
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}
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int GemmPlugin::getNbOutputs() const noexcept
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{
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return 1;
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}
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int GemmPlugin::initialize() noexcept
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{
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configGemm();
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return 0;
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}
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void GemmPlugin::destroy() noexcept
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{
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delete this;
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}
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size_t GemmPlugin::getSerializationSize() const noexcept
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{
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return sizeof(mTransA) + sizeof(mTransB) + sizeof(mType) + sizeof(mDims) + sizeof(mUseFp8)
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+ mPluginProfiler->getSerializationSize(mGemmId); // selected tactics container size
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}
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void GemmPlugin::serialize(void* buffer) const noexcept
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{
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char *d = static_cast<char*>(buffer), *a = d;
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write(d, mTransA);
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write(d, mTransB);
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write(d, mType);
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write(d, mUseFp8);
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write(d, mDims);
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mPluginProfiler->serialize(d, mGemmId);
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assert(d == a + getSerializationSize());
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}
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void GemmPlugin::terminate() noexcept {}
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///////////////
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GemmPluginCreator::GemmPluginCreator()
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{
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// Fill PluginFieldCollection with PluginField arguments metadata
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mPluginAttributes.clear();
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mPluginAttributes.emplace_back(PluginField("transA", nullptr, PluginFieldType::kINT32, 0));
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mPluginAttributes.emplace_back(PluginField("transB", nullptr, PluginFieldType::kINT32, 0));
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mPluginAttributes.emplace_back(PluginField("type_id", nullptr, PluginFieldType::kINT32, 1));
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mPluginAttributes.emplace_back(PluginField("use_fp8", nullptr, PluginFieldType::kINT32, 0));
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mFC.nbFields = mPluginAttributes.size();
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mFC.fields = mPluginAttributes.data();
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}
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const char* GemmPluginCreator::getPluginName() const noexcept
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{
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return GEMM_PLUGIN_NAME;
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}
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const char* GemmPluginCreator::getPluginVersion() const noexcept
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{
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return GEMM_PLUGIN_VERSION;
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}
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const PluginFieldCollection* GemmPluginCreator::getFieldNames() noexcept
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{
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return &mFC;
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}
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IPluginV2* GemmPluginCreator::createPlugin(const char* name, const PluginFieldCollection* fc) noexcept
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{
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const PluginField* fields = fc->fields;
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int transA, transB;
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nvinfer1::DataType type;
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int useFp8;
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// Read configurations from each fields
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for (int i = 0; i < fc->nbFields; ++i)
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{
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const char* attrName = fields[i].name;
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if (!strcmp(attrName, "transa"))
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{
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TLLM_CHECK(fields[i].type == PluginFieldType::kINT32);
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transA = static_cast<int>(*(static_cast<const int*>(fields[i].data)));
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}
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else if (!strcmp(attrName, "transb"))
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{
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TLLM_CHECK(fields[i].type == PluginFieldType::kINT32);
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transB = static_cast<int>(*(static_cast<const int*>(fields[i].data)));
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}
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else if (!strcmp(attrName, "type_id"))
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{
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TLLM_CHECK(fields[i].type == PluginFieldType::kINT32);
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type = static_cast<nvinfer1::DataType>(*(static_cast<const nvinfer1::DataType*>(fields[i].data)));
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}
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else if (!strcmp(attrName, "use_fp8"))
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{
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TLLM_CHECK(fields[i].type == PluginFieldType::kINT32);
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useFp8 = static_cast<int>(*(static_cast<const int*>(fields[i].data)));
|
|
}
|
|
}
|
|
try
|
|
{
|
|
// GemmPluginCreator is unique and shared for an engine generation
|
|
// Create plugin profiler with shared tactics map
|
|
// FIXME enable tactic profiler
|
|
auto pluginProfiler = gemmPluginProfileManager.createGemmPluginProfiler(/* inference */ false, /* skip */ true);
|
|
auto* obj = new GemmPlugin(transA, transB, type, useFp8, pluginProfiler);
|
|
obj->setPluginNamespace(mNamespace.c_str());
|
|
return obj;
|
|
}
|
|
catch (const std::exception& e)
|
|
{
|
|
caughtError(e);
|
|
}
|
|
return nullptr;
|
|
}
|
|
|
|
IPluginV2* GemmPluginCreator::deserializePlugin(const char* name, const void* serialData, size_t serialLength) noexcept
|
|
{
|
|
// This object will be deleted when the network is destroyed, which will
|
|
// call GemmPlugin::destroy()
|
|
try
|
|
{
|
|
// GemmPluginCreator is unique and shared for an engine generation
|
|
// Create plugin profiler with shared tactics map
|
|
// FIXME enable tactic profiler
|
|
auto pluginProfiler = gemmPluginProfileManager.createGemmPluginProfiler(/* inference */ true, /* skip */ true);
|
|
auto* obj = new GemmPlugin(serialData, serialLength, pluginProfiler);
|
|
obj->setPluginNamespace(mNamespace.c_str());
|
|
return obj;
|
|
}
|
|
catch (const std::exception& e)
|
|
{
|
|
caughtError(e);
|
|
}
|
|
return nullptr;
|
|
}
|