/* * SPDX-FileCopyrightText: Copyright (c) 1993-2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved. * SPDX-License-Identifier: Apache-2.0 * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ #pragma once #include "tensorrt_llm/kernels/cutlass_kernels/fused_gated_gemm/fused_gated_gemm.h" #include "tensorrt_llm/plugins/common/gemmPluginProfiler.h" #include "tensorrt_llm/plugins/common/plugin.h" #include #include #include #include namespace tensorrt_llm::plugins { using GemmSwigluRunnerPtr = std::shared_ptr; class GemmSwigluPluginProfiler : public GemmPluginProfiler { public: using Config = tensorrt_llm::cutlass_extensions::CutlassGemmConfig; void setQuantMode(tensorrt_llm::common::QuantMode const& quantMode); virtual int getMaxProfileM() const override; protected: void runTactic(int m, int n, int k, Config const& tactic, char* workspace, cudaStream_t const& stream) override; void computeTmpSize(size_t maxM, size_t n, size_t k) override; // TODO(anchengc) implement checkTactic // bool checkTactic(int m, int n, int k, const Config& tactic) const override; std::vector getTactics(int m, int n, int k) const override; void initTmpData(int m, int n, int k, char* workspace, size_t size, cudaStream_t stream) override; private: size_t getBytePerElement(nvinfer1::DataType type); tensorrt_llm::common::QuantMode mQuantMode; }; class GemmSwigluPlugin : public BasePlugin { public: using PluginProfilerPtr = std::shared_ptr; GemmSwigluPlugin() = delete; GemmSwigluPlugin(tensorrt_llm::common::QuantMode quantMode, nvinfer1::DataType type, bool hasBias, float scale_d0, float scale_d1, float scale_output, PluginProfilerPtr const& pluginProfiler); GemmSwigluPlugin(void const* data, size_t length, PluginProfilerPtr const& profiler); ~GemmSwigluPlugin() override = default; // IPluginV2DynamicExt Methods nvinfer1::IPluginV2DynamicExt* clone() const noexcept override; nvinfer1::DimsExprs getOutputDimensions(int outputIndex, nvinfer1::DimsExprs const* inputs, int nbInputs, nvinfer1::IExprBuilder& exprBuilder) noexcept override; bool supportsFormatCombination( int pos, nvinfer1::PluginTensorDesc const* inOut, int nbInputs, int nbOutputs) noexcept override; void configurePlugin(nvinfer1::DynamicPluginTensorDesc const* in, int nbInputs, nvinfer1::DynamicPluginTensorDesc const* out, int nbOutputs) noexcept override; size_t getWorkspaceSize(nvinfer1::PluginTensorDesc const* inputs, int nbInputs, nvinfer1::PluginTensorDesc const* outputs, int nbOutputs) const noexcept override; int enqueue(nvinfer1::PluginTensorDesc const* inputDesc, nvinfer1::PluginTensorDesc const* outputDesc, void const* const* inputs, void* const* outputs, void* workspace, cudaStream_t stream) noexcept override; // IPluginV2Ext Methods nvinfer1::DataType getOutputDataType( int index, nvinfer1::DataType const* inputTypes, int nbInputs) const noexcept override; // IPluginV2 Methods char const* getPluginType() const noexcept override; char const* getPluginVersion() const noexcept override; int getNbOutputs() const noexcept override; int initialize() noexcept override; void terminate() noexcept override; size_t getSerializationSize() const noexcept override; void serialize(void* buffer) const noexcept override; void destroy() noexcept override; private: void init(nvinfer1::DataType type); void configGemm(); // void setGemmConfig(); private: const std::string mLayerName; GemmSwigluRunnerPtr mGemmRunner; tensorrt_llm::common::QuantMode mQuantMode; // not configurable yet size_t mWorkspaceMaxSize; GemmDims mDims{}; GemmIdCore mGemmId{}; PluginProfilerPtr mPluginProfiler; nvinfer1::DataType mType; bool mHasBias; float mScaleD0; float mScaleD1; float mScaleOutput; }; class GemmSwigluPluginCreator : public BaseCreator { public: GemmSwigluPluginCreator(); char const* getPluginName() const noexcept override; char const* getPluginVersion() const noexcept override; nvinfer1::PluginFieldCollection const* getFieldNames() noexcept override; nvinfer1::IPluginV2* createPlugin(char const* name, nvinfer1::PluginFieldCollection const* fc) noexcept override; nvinfer1::IPluginV2* deserializePlugin( char const* name, void const* serialData, size_t serialLength) noexcept override; private: GemmPluginProfilerManager mGemmPluginProfileManager; static nvinfer1::PluginFieldCollection mFC; static std::vector mPluginAttributes; }; } // namespace tensorrt_llm::plugins