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https://github.com/NVIDIA/TensorRT-LLM.git
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* Update TensorRT-LLM --------- Co-authored-by: IbrahimAmin <ibrahimamin532@gmail.com> Co-authored-by: Fabian Joswig <fjosw@users.noreply.github.com> Co-authored-by: Pzzzzz <hello-cd.plus@hotmail.com> Co-authored-by: CoderHam <hemant@cohere.com> Co-authored-by: Konstantin Lopuhin <kostia.lopuhin@gmail.com>
240 lines
7.7 KiB
C++
240 lines
7.7 KiB
C++
/*
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* SPDX-FileCopyrightText: Copyright (c) 1993-2024 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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#ifndef TRT_LRU_PLUGIN_H
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#define TRT_LRU_PLUGIN_H
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#include "tensorrt_llm/kernels/lruKernel.h"
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#include "tensorrt_llm/plugins/common/plugin.h"
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#include <cassert>
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namespace tensorrt_llm::plugins
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{
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// batch_size = num_ctx_requests or num_gen_requests
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// num_ctx_requests = number of context requests (single sequence per request).
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// num_gen_requests = number of generation requests (single sequences per request).
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// can not support beam search
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// inputs
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// 0. x [batch_size, seq_len, dim] or [num_tokens, dim] for remove_input_padding
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// 1. A [dim]
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// 2. state [batch_size, dim] or host [1] containing only pointer for paged_state
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// 3. host_request_types [batch_size] int32. 0: context; 1: generation; 2: none.
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// 4. last_token_ids [batch_size] int32
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// 5. state_slot_mapping [batch_size] int32, optional for paged state
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// 6. y [batch_size, seq_len, dim] or [num_tokens, dim] for remove_input_padding
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// 7. y_bias [dim]
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// 8. gate [batch_size, seq_len, 2 * dim] or [num_tokens, 2 * dim] for remove_input_padding
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// 9. gate_bias [2 * dim]
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// 10. gate_x [batch_size, seq_len, dim] or [num_tokens, dim] for remove_input_padding
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// 11. gate_a [batch_size, seq_len, dim] or [num_tokens, dim] for remove_input_padding
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// 12. gate_x_bias [2 * dim]
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// 13. gate_a_bias [2 * dim]
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// outputs
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// 0. output_tensor [batch_size, seq_len, dim] or [num_tokens, dim] for remove_input_padding
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// 1. state [batch_size, dim]
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class lruPlugin : public BasePlugin
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{
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public:
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lruPlugin(int dim, int block_size, nvinfer1::DataType type, bool removePadding, bool pagedState, bool yEnabled,
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bool yBiasEnabled, bool fuseGateEnabled, bool gateBiasEnabled);
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lruPlugin(void const* data, size_t length);
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~lruPlugin() 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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enum class RequestType : int32_t
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{
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kCONTEXT = 0,
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kGENERATION = 1
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};
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private:
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using IndexType = std::int32_t;
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IndexType getXIdx() const
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{
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return 0;
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};
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IndexType getAIdx() const
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{
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return 1;
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};
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IndexType getStateIdx() const
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{
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return 2;
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};
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IndexType getHostRequestTypesIdx() const
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{
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return 3;
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};
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IndexType getLastTokenIdsIdx() const
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{
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return 4;
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};
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IndexType getSlotMappingIdx() const
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{
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if (mPagedState)
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return 5;
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else
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return 4;
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};
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IndexType getYIdx() const
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{
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if (mYEnabled)
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return getSlotMappingIdx() + 1;
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else
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return getSlotMappingIdx();
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};
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IndexType getYBiasIdx() const
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{
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if (mYBiasEnabled)
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return getYIdx() + 1;
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else
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return getYIdx();
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};
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IndexType getGateIdx() const
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{
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if (mFuseGateEnabled)
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return getYBiasIdx() + 1;
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else
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return getYBiasIdx();
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};
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IndexType getGateBiasIdx() const
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{
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if (mFuseGateEnabled && mGateBiasEnabled)
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return getGateIdx() + 1;
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else
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return getGateIdx();
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};
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IndexType getGateXIdx() const
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{
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if (mFuseGateEnabled)
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return getGateBiasIdx();
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else
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return getGateBiasIdx() + 1;
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};
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IndexType getGateAIdx() const
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{
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if (mFuseGateEnabled)
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return getGateXIdx();
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else
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return getGateXIdx() + 1;
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};
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IndexType getGateXBiasIdx() const
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{
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if (!mFuseGateEnabled && mGateBiasEnabled)
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return getGateAIdx() + 1;
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else
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return getGateAIdx();
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};
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IndexType getGateABiasIdx() const
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{
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if (!mFuseGateEnabled && mGateBiasEnabled)
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return getGateXBiasIdx() + 1;
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else
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return getGateXBiasIdx();
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};
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static void setLruParams(tensorrt_llm::kernels::lruParams& params,
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// sizes
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const size_t batch, const size_t dim, const size_t block_size, const size_t maxSeqLen,
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// device pointers
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void* statePtr, void const* x, void const* gate, void const* gate_bias, void const* gate_x,
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void const* gate_x_bias, void const* gate_a, void const* gate_a_bias, void const* y, void const* y_bias,
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void const* A, int const* lastTokenIds, int const* slotMapping, void* out, bool removePadding);
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private:
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int mDim;
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int mBlockSize;
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nvinfer1::DataType mType;
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bool mRemovePadding = false;
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bool mPagedState = false;
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bool mYEnabled = false;
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bool mYBiasEnabled = false;
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bool mFuseGateEnabled = false;
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bool mGateBiasEnabled = false;
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};
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class lruPluginCreator : public BaseCreator
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{
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public:
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lruPluginCreator();
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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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#endif // TRT_LRU_PLUGIN_H
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