mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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131 lines
5.0 KiB
C++
131 lines
5.0 KiB
C++
/*
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* SPDX-FileCopyrightText: Copyright (c) 1993-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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* 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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#pragma once
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#include "tensorrt_llm/common/cublasMMWrapper.h"
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#include "tensorrt_llm/common/quantization.h"
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#include "tensorrt_llm/kernels/contextFusedMultiHeadAttention/fmhaRunner.h"
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#include "tensorrt_llm/kernels/gptKernels.h"
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#include "tensorrt_llm/plugins/common/plugin.h"
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#include <cassert>
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#include <set>
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#include <string>
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#include <vector>
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namespace tensorrt_llm::plugins
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{
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class BertAttentionPlugin : public BasePlugin
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{
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public:
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BertAttentionPlugin() = delete;
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BertAttentionPlugin(int num_heads, int head_size, float q_scaling,
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tensorrt_llm::kernels::ContextFMHAType context_fmha_type, nvinfer1::DataType type,
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bool do_relative_attention = false, int max_distance = 0, bool remove_padding = false, bool sage_attn = false,
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int sage_attn_q_block_size = 0, int sage_attn_k_block_size = 0, int sage_attn_v_block_size = 0);
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BertAttentionPlugin(void const* data, size_t length);
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~BertAttentionPlugin() override = default;
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// IPluginV2DynamicExt Methods
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nvinfer1::IPluginV2DynamicExt* clone() const noexcept override;
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nvinfer1::DimsExprs getOutputDimensions(int outputIndex, nvinfer1::DimsExprs const* inputs, int nbInputs,
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nvinfer1::IExprBuilder& exprBuilder) noexcept override;
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bool supportsFormatCombination(
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int pos, nvinfer1::PluginTensorDesc const* inOut, int nbInputs, int nbOutputs) noexcept override;
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void configurePlugin(nvinfer1::DynamicPluginTensorDesc const* in, int nbInputs,
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nvinfer1::DynamicPluginTensorDesc const* out, int nbOutputs) noexcept override;
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size_t getWorkspaceSize(nvinfer1::PluginTensorDesc const* inputs, int nbInputs,
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nvinfer1::PluginTensorDesc const* outputs, int nbOutputs) const noexcept override;
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int 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 override;
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template <typename T>
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int enqueueImpl(nvinfer1::PluginTensorDesc const* inputDesc, nvinfer1::PluginTensorDesc const* outputDesc,
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void const* const* inputs, void* const* outputs, void* workspace, cudaStream_t stream);
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// IPluginV2Ext Methods
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nvinfer1::DataType getOutputDataType(
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int index, nvinfer1::DataType const* inputTypes, int nbInputs) const noexcept override;
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// IPluginV2 Methods
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char const* getPluginType() const noexcept override;
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char const* getPluginVersion() const noexcept override;
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int getNbOutputs() const noexcept override;
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int initialize() noexcept override;
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void terminate() noexcept override;
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size_t getSerializationSize() const noexcept override;
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void serialize(void* buffer) const noexcept override;
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void destroy() noexcept override;
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private:
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const std::string mLayerName;
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int mNumHeads;
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int mHeadSize;
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float mQScaling;
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nvinfer1::DataType mType;
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bool mRelativeAttention = false;
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int mMaxDistance = 0;
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bool mRemovePadding = false;
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// unfused mha
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bool mQKHalfAccum = false;
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// fmha runner (disable by default)
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bool mEnableContextFMHA = false;
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bool mFMHAForceFP32Acc = false;
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// sage attention
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bool mSageAttn = false;
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int mSageAttnQBlockSize = 0;
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int mSageAttnKBlockSize = 0;
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int mSageAttnVBlockSize = 0;
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std::set<std::vector<int>> mSageAttnSupportedBlockSizes{{64, 64, 256}};
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int mSM = tensorrt_llm::common::getSMVersion();
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// The default copy constructor will leave them as nullptr. clone() shall initialize it.
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UniqPtrWNullCopy<tensorrt_llm::kernels::FusedMHARunnerV2> mFMHARunner;
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UniqPtrWNullCopy<tensorrt_llm::common::CublasMMWrapper> mCublasWrapper;
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};
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class BertAttentionPluginCreator : public BaseCreator
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{
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public:
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BertAttentionPluginCreator();
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char const* getPluginName() const noexcept override;
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char const* getPluginVersion() const noexcept override;
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nvinfer1::PluginFieldCollection const* getFieldNames() noexcept override;
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nvinfer1::IPluginV2* createPlugin(char const* name, nvinfer1::PluginFieldCollection const* fc) noexcept override;
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nvinfer1::IPluginV2* deserializePlugin(
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char const* name, void const* serialData, size_t serialLength) noexcept override;
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private:
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static nvinfer1::PluginFieldCollection mFC;
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static std::vector<nvinfer1::PluginField> mPluginAttributes;
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};
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} // namespace tensorrt_llm::plugins
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