mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
synced 2026-01-14 06:27:45 +08:00
447 lines
15 KiB
C++
447 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 "gemmSwigluPlugin.h"
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#include "cutlass_extensions/gemm_configs.h"
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#include <NvInferRuntimeBase.h>
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#include <numeric>
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using namespace nvinfer1;
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using namespace tensorrt_llm::common;
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using namespace tensorrt_llm::kernels::cutlass_kernels;
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using tensorrt_llm::plugins::GemmSwigluPluginCreator;
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using tensorrt_llm::plugins::GemmSwigluPlugin;
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using tensorrt_llm::plugins::GemmSwigluPluginProfiler;
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using tensorrt_llm::plugins::read;
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using tensorrt_llm::plugins::write;
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static char const* GEMM_SWIGLU_PLUGIN_VERSION{"1"};
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static char const* GEMM_SWIGLU_PLUGIN_NAME{"GemmSwiglu"};
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PluginFieldCollection GemmSwigluPluginCreator::mFC{};
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std::vector<nvinfer1::PluginField> GemmSwigluPluginCreator::mPluginAttributes;
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size_t GemmSwigluPluginProfiler::getBytePerElement(nvinfer1::DataType type)
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{
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size_t bpe;
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if (type == nvinfer1::DataType::kHALF || type == nvinfer1::DataType::kBF16)
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{
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bpe = 2;
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}
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else if (type == nvinfer1::DataType::kINT8 || type == nvinfer1::DataType::kFP8)
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{
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bpe = 1;
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}
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else
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{
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TLLM_THROW("Not recognized/implemented");
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}
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return bpe;
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}
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void GemmSwigluPluginProfiler::setQuantMode(tensorrt_llm::common::QuantMode const& quantMode)
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{
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mQuantMode = quantMode;
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}
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void GemmSwigluPluginProfiler::runTactic(
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int m, int n, int k, GemmSwigluPluginProfiler::Config const& tactic, char* workspace, cudaStream_t const& stream)
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{
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size_t bpe = getBytePerElement(mType);
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// Workspace size required by gemm runner
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// NB: this function will throw exception when selected tactic exceeds SMEM, which is then
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// caught by gemmPluginProfiler and it will register this tactic as invalid
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size_t wsSizeRunner = mRunner->getWorkspaceSize(m, n, k);
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// Workspace size required by profiling
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size_t wsByteOffset = 0;
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int8_t* wsBytePointer = reinterpret_cast<int8_t*>(workspace);
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void* aTmp = reinterpret_cast<void*>(nextWorkspacePtr(wsBytePointer, wsByteOffset, m * k * bpe));
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void* bTmp = reinterpret_cast<void*>(nextWorkspacePtr(wsBytePointer, wsByteOffset, n * k * bpe));
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void* cTmp = reinterpret_cast<void*>(nextWorkspacePtr(wsBytePointer, wsByteOffset, 1 * n * bpe));
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void* dTmp = reinterpret_cast<void*>(nextWorkspacePtr(wsBytePointer, wsByteOffset, m * (n / 2) * bpe));
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char* workspaceTmp = reinterpret_cast<char*>(nextWorkspacePtr(wsBytePointer, wsByteOffset, wsSizeRunner));
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// Run profiling
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mRunner->gemm(
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dTmp, aTmp, bTmp, cTmp, mQuantMode, m, n, k, 1.0, 1.0, 1.0, tactic, workspaceTmp, wsSizeRunner, stream);
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}
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int GemmSwigluPluginProfiler::getMaxProfileM() const
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{
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return 32768;
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}
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void GemmSwigluPluginProfiler::computeTmpSize(size_t maxM, size_t n, size_t k)
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{
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std::vector<size_t> workspaces = {
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maxM * k * getBytePerElement(mType), // A
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n * k * getBytePerElement(mType), // B
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1 * n * getBytePerElement(mType), // C_bias
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maxM * (n / 2) * getBytePerElement(mType), // D
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mRunner->getWorkspaceSize(maxM, n, k) // workspace
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};
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size_t bytes = calculateTotalWorkspaceSize(workspaces.data(), workspaces.size());
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setTmpWorkspaceSizeInBytes(bytes);
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}
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std::vector<GemmSwigluPluginProfiler::Config> GemmSwigluPluginProfiler::getTactics(int m, int n, int k) const
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{
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return mRunner->getConfigs();
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}
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GemmSwigluPlugin::GemmSwigluPlugin(QuantMode quantMode, nvinfer1::DataType type, bool hasBias, float scale_d0,
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float scale_d1, float scale_output, GemmSwigluPlugin::PluginProfilerPtr const& pluginProfiler)
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: mQuantMode(quantMode)
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, mPluginProfiler(pluginProfiler)
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, mHasBias(hasBias)
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, mScaleD0(scale_d0)
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, mScaleD1(scale_d1)
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, mScaleOutput(scale_output)
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{
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init(type);
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}
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// Parameterized constructor
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GemmSwigluPlugin::GemmSwigluPlugin(
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void const* data, size_t length, GemmSwigluPlugin::PluginProfilerPtr const& pluginProfiler)
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: mPluginProfiler(pluginProfiler)
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{
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char const *d = reinterpret_cast<char const*>(data), *a = d;
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nvinfer1::DataType type;
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unsigned int quantMode;
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read(d, quantMode);
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read(d, type);
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read(d, mHasBias);
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read(d, mScaleD0);
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read(d, mScaleD1);
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read(d, mScaleOutput);
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read(d, mDims);
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mQuantMode = QuantMode(quantMode);
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init(type);
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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 GemmSwigluPlugin::init(nvinfer1::DataType type)
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{
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mType = type;
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if (mType == nvinfer1::DataType::kFP8)
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{
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mGemmRunner = std::make_shared<CutlassFusedGatedGemmRunner<__nv_fp8_e4m3>>();
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}
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else
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{
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TLLM_THROW("Gemm Swiglu plugin only supports fp8 now");
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}
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mPluginProfiler->setQuantMode(mQuantMode);
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mGemmId = GemmIdCore(mDims.n, mDims.k, mType);
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}
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// IPluginV2DynamicExt Methods
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nvinfer1::IPluginV2DynamicExt* GemmSwigluPlugin::clone() const noexcept
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{
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auto* plugin = new GemmSwigluPlugin(*this);
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return plugin;
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}
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nvinfer1::DimsExprs GemmSwigluPlugin::getOutputDimensions(
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int outputIndex, nvinfer1::DimsExprs const* 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 == 3);
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TLLM_CHECK(outputIndex == 0);
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int const nbDimsA = inputs[0].nbDims;
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TLLM_CHECK(nbDimsA >= 2);
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DimsExprs ret;
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ret.nbDims = nbDimsA;
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for (int ii = 0; ii < nbDimsA - 1; ++ii)
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{
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ret.d[ii] = inputs[0].d[ii];
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}
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ret.d[nbDimsA - 1] = exprBuilder.constant(inputs[1].d[1]->getConstantValue() / 2);
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return ret;
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}
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catch (std::exception const& 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 GemmSwigluPlugin::supportsFormatCombination(
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int pos, nvinfer1::PluginTensorDesc const* inOut, int nbInputs, int nbOutputs) noexcept
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{
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switch (pos)
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{
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case 0:
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// activation
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return inOut[pos].type == mType && inOut[pos].format == TensorFormat::kLINEAR;
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case 1:
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// weights
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return inOut[pos].type == mType && inOut[pos].format == TensorFormat::kLINEAR;
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case 2:
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// bias
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return inOut[pos].type == mType && inOut[pos].format == TensorFormat::kLINEAR;
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case 3:
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// out
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return inOut[pos].type == mType && inOut[pos].format == TensorFormat::kLINEAR;
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default:
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// Never should be here
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TLLM_CHECK(false);
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return false;
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}
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}
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void GemmSwigluPlugin::configurePlugin(nvinfer1::DynamicPluginTensorDesc const* in, int nbInputs,
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nvinfer1::DynamicPluginTensorDesc const* out, int nbOutputs) noexcept
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{
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auto const minM = std::accumulate(in[0].min.d, in[0].min.d + in[0].min.nbDims - 1, 1, std::multiplies<int>());
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auto const maxM = std::accumulate(in[0].max.d, in[0].max.d + in[0].max.nbDims - 1, 1, std::multiplies<int>());
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int const maxK = in[0].max.d[in[0].max.nbDims - 1];
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int const maxN = in[1].max.d[1];
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int const minK = in[0].min.d[in[0].min.nbDims - 1];
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int const minN = in[1].min.d[1];
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TLLM_CHECK_WITH_INFO(minN == maxN, "Variable out channels is not allowed");
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TLLM_CHECK_WITH_INFO(minK == maxK, "Variable in channels is not allowed");
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if (!mDims.isInitialized())
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{
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mDims = {minM, maxM, maxN, maxK};
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}
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mGemmId = {maxN, maxK, mType};
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mWorkspaceMaxSize = mGemmRunner->getWorkspaceSize(maxM, maxN, maxK);
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}
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size_t GemmSwigluPlugin::getWorkspaceSize(nvinfer1::PluginTensorDesc const* inputs, int nbInputs,
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nvinfer1::PluginTensorDesc const* outputs, int nbOutputs) const noexcept
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{
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return mWorkspaceMaxSize;
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}
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int GemmSwigluPlugin::enqueue(nvinfer1::PluginTensorDesc const* inputDesc, nvinfer1::PluginTensorDesc const* outputDesc,
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void const* 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]
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// mat2 [K, N]
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// bias [1, N]
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// outputs
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// mat [M(*), N / 2]
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int m = 1;
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for (int ii = 0; ii < inputDesc[0].dims.nbDims - 1; ++ii)
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{
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m *= inputDesc[0].dims.d[ii];
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}
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int const n = inputDesc[1].dims.d[1];
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int const k = inputDesc[0].dims.d[inputDesc[0].dims.nbDims - 1];
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size_t const wsSize = mGemmRunner->getWorkspaceSize(m, n, k);
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auto const bestTactic = mPluginProfiler->getBestConfig(m, mGemmId);
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TLLM_CHECK_WITH_INFO(bestTactic, "No valid GEMM tactic");
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mGemmRunner->gemm(outputs[0], inputs[0], inputs[1], inputs[2], mQuantMode, m, n, k, mScaleD0, mScaleD1,
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mScaleOutput, *bestTactic, reinterpret_cast<char*>(workspace), wsSize, stream);
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return 0;
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}
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// IPluginV2Ext Methods
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nvinfer1::DataType GemmSwigluPlugin::getOutputDataType(
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int index, nvinfer1::DataType const* inputTypes, int nbInputs) const noexcept
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{
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TLLM_CHECK(index == 0);
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return mType;
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}
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// IPluginV2 Methods
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char const* GemmSwigluPlugin::getPluginType() const noexcept
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{
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return GEMM_SWIGLU_PLUGIN_NAME;
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}
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char const* GemmSwigluPlugin::getPluginVersion() const noexcept
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{
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return GEMM_SWIGLU_PLUGIN_VERSION;
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}
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int GemmSwigluPlugin::getNbOutputs() const noexcept
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{
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return 1;
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}
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int GemmSwigluPlugin::initialize() noexcept
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{
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configGemm(); // gemm profiler in action
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return 0;
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}
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void GemmSwigluPlugin::terminate() noexcept {}
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size_t GemmSwigluPlugin::getSerializationSize() const noexcept
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{
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return sizeof(unsigned int) + // QuantMode
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sizeof(nvinfer1::DataType) + // dtype
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sizeof(bool) + // hasBias
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sizeof(float) * 3 + // scales
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sizeof(mDims) + // Dimensions
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mPluginProfiler->getSerializationSize(mGemmId); // selected tactics container size
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}
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void GemmSwigluPlugin::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, mQuantMode.value());
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write(d, mType);
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write(d, mHasBias);
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write(d, mScaleD0);
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write(d, mScaleD1);
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write(d, mScaleOutput);
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write(d, mDims);
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mPluginProfiler->serialize(d, mGemmId);
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TLLM_CHECK(d == a + getSerializationSize());
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}
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void GemmSwigluPlugin::destroy() noexcept
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{
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// This gets called when the network containing plugin is destroyed
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delete this;
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}
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void GemmSwigluPlugin::configGemm()
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{
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mPluginProfiler->profileTactics(mGemmRunner, mType, mDims, mGemmId);
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}
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///////////////
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GemmSwigluPluginCreator::GemmSwigluPluginCreator()
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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("type_id", nullptr, PluginFieldType::kINT32));
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mPluginAttributes.emplace_back(PluginField("has_bias", nullptr, PluginFieldType::kINT8));
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mPluginAttributes.emplace_back(PluginField("scale_d0", nullptr, PluginFieldType::kFLOAT32));
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mPluginAttributes.emplace_back(PluginField("scale_d1", nullptr, PluginFieldType::kFLOAT32));
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mPluginAttributes.emplace_back(PluginField("scale_output", nullptr, PluginFieldType::kFLOAT32));
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mFC.nbFields = mPluginAttributes.size();
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mFC.fields = mPluginAttributes.data();
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}
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char const* GemmSwigluPluginCreator::getPluginName() const noexcept
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{
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return GEMM_SWIGLU_PLUGIN_NAME;
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}
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char const* GemmSwigluPluginCreator::getPluginVersion() const noexcept
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{
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return GEMM_SWIGLU_PLUGIN_VERSION;
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}
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PluginFieldCollection const* GemmSwigluPluginCreator::getFieldNames() noexcept
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{
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return &mFC;
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}
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IPluginV2* GemmSwigluPluginCreator::createPlugin(char const* name, PluginFieldCollection const* fc) noexcept
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{
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PluginField const* fields = fc->fields;
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TLLM_CHECK(fc->nbFields == 5);
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nvinfer1::DataType type{};
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bool hasBias{};
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float scale_d0{};
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float scale_d1{};
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float scale_output{};
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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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char const* attrName = fields[i].name;
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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<nvinfer1::DataType const*>(fields[i].data)));
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}
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else if (!strcmp(attrName, "has_bias"))
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{
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TLLM_CHECK(fields[i].type == PluginFieldType::kINT8);
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hasBias = static_cast<bool>(*(static_cast<int8_t const*>(fields[i].data)));
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}
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else if (!strcmp(attrName, "scale_d0"))
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{
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TLLM_CHECK(fields[i].type == PluginFieldType::kFLOAT32);
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scale_d0 = static_cast<float>(*(static_cast<float const*>(fields[i].data)));
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}
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else if (!strcmp(attrName, "scale_d1"))
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{
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TLLM_CHECK(fields[i].type == PluginFieldType::kFLOAT32);
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scale_d1 = static_cast<float>(*(static_cast<float const*>(fields[i].data)));
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}
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else if (!strcmp(attrName, "scale_output"))
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{
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TLLM_CHECK(fields[i].type == PluginFieldType::kFLOAT32);
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scale_output = static_cast<float>(*(static_cast<float const*>(fields[i].data)));
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}
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}
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try
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{
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// GemmSwigluPluginCreator is unique and shared for an engine generation
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// Create plugin profiler with shared tactics map
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auto pluginProfiler = mGemmPluginProfileManager.createGemmPluginProfiler(/* inference */ false);
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QuantMode quantMode = QuantMode::fromDescription();
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auto* obj = new GemmSwigluPlugin(quantMode, type, hasBias, scale_d0, scale_d1, scale_output, pluginProfiler);
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obj->setPluginNamespace(mNamespace.c_str());
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return obj;
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}
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catch (std::exception const& e)
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{
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caughtError(e);
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}
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return nullptr;
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}
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IPluginV2* GemmSwigluPluginCreator::deserializePlugin(
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char const* name, void const* serialData, size_t serialLength) noexcept
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{
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// This object will be deleted when the network is destroyed, which will
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// call GemmSwigluPlugin::destroy()
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try
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{
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// Create plugin profiler with private tactics map which is read from the serialized engine
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auto pluginProfiler = mGemmPluginProfileManager.createGemmPluginProfiler(/* inference */ true);
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auto* obj = new GemmSwigluPlugin(serialData, serialLength, pluginProfiler);
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obj->setPluginNamespace(mNamespace.c_str());
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return obj;
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}
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catch (std::exception const& e)
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{
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caughtError(e);
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}
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return nullptr;
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}
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