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* Update TensorRT-LLM --------- Co-authored-by: Altair-Alpha <62340011+Altair-Alpha@users.noreply.github.com>
177 lines
6.1 KiB
C++
177 lines
6.1 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_MAMBA_CONV1D_PLUGIN_H
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#define TRT_MAMBA_CONV1D_PLUGIN_H
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#include "tensorrt_llm/kernels/mambaConv1dKernels.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. input_tensor [batch_size, seq_len, dim] or [num_tokens, dim] for remove_input_padding
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// 1. conv_state [batch_size, dconv - 1, dim] or host [1] containing only pointer for paged_state
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// 2. weight [1, dconv, dim]
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// 3. bias [dim]
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// 4. host_request_types [batch_size] int32. 0: context; 1: generation; 2: none.
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// 5. last_token_ids [batch_size] int32
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// 6. host_context_lengths [batch_size] int32, optional for remove_input_padding
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// 7. state_slot_mapping [batch_size] int32, optional
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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. conv_state [batch_size, dconv - 1, dim]
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class MambaConv1dPlugin : public BasePlugin
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{
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public:
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MambaConv1dPlugin(int dim, int dconv, int preStride, int postStride, nvinfer1::DataType type, bool removePadding,
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bool pagedState, bool applySilu);
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MambaConv1dPlugin(void const* data, size_t length);
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~MambaConv1dPlugin() 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 getInputTensorIdx() const
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{
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return 0;
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};
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IndexType getConvStateIdx() const
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{
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return 1;
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};
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IndexType getWeightIdx() const
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{
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return 2;
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};
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IndexType getBiasIdx() const
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{
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return 3;
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};
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IndexType getHostRequestTypesIdx() const
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{
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return 4;
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};
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IndexType getLastTokenIdsIdx() const
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{
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return 5;
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};
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IndexType getHostContextLengthIdx() const
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{
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return 6;
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};
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IndexType getSlotMappingIdx() const
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{
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// if not remove input padding, host_context_length is not used, so the index is 6
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return mRemovePadding ? 7 : 6;
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};
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void setMambaConv1dParams(tensorrt_llm::kernels::MambaConv1dParamsBase& params,
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// sizes
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const size_t batch, const size_t dim, const size_t maxSeqLen, const size_t dconv, const size_t preStride,
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const size_t postStride,
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// device pointers
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void const* inPtr, void const* stateInPtr, void* stateOutPtr, void const* convWeight, void const* convBias,
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void* outPtr, int const* lastTokenIds, int const* stateSlotMapping, bool removePadding, bool applySilu);
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private:
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int mDim;
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int mDConv;
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int mPreStride;
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int mPostStride;
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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 mApplySilu = true;
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};
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class MambaConv1dPluginCreator : public BaseCreator
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{
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public:
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MambaConv1dPluginCreator();
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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_MAMBA_CONV1D_PLUGIN_H
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