TensorRT-LLMs/cpp/tensorrt_llm/plugins/mambaConv1dPlugin/mambaConv1dPlugin.h
Kaiyu Xie 2d234357c6
Update TensorRT-LLM (#1954)
* Update TensorRT-LLM

---------

Co-authored-by: Altair-Alpha <62340011+Altair-Alpha@users.noreply.github.com>
2024-07-16 15:30:25 +08:00

177 lines
6.1 KiB
C++

/*
* SPDX-FileCopyrightText: Copyright (c) 1993-2024 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.
*/
#ifndef TRT_MAMBA_CONV1D_PLUGIN_H
#define TRT_MAMBA_CONV1D_PLUGIN_H
#include "tensorrt_llm/kernels/mambaConv1dKernels.h"
#include "tensorrt_llm/plugins/common/plugin.h"
#include <cassert>
namespace tensorrt_llm::plugins
{
// batch_size = num_ctx_requests or num_gen_requests
// num_ctx_requests = number of context requests (single sequence per request).
// num_gen_requests = number of generation requests (single sequences per request).
// can not support beam search
// inputs
// 0. input_tensor [batch_size, seq_len, dim] or [num_tokens, dim] for remove_input_padding
// 1. conv_state [batch_size, dconv - 1, dim] or host [1] containing only pointer for paged_state
// 2. weight [1, dconv, dim]
// 3. bias [dim]
// 4. host_request_types [batch_size] int32. 0: context; 1: generation; 2: none.
// 5. last_token_ids [batch_size] int32
// 6. host_context_lengths [batch_size] int32, optional for remove_input_padding
// 7. state_slot_mapping [batch_size] int32, optional
// outputs
// 0. output_tensor [batch_size, seq_len, dim] or [num_tokens, dim] for remove_input_padding
// 1. conv_state [batch_size, dconv - 1, dim]
class MambaConv1dPlugin : public BasePlugin
{
public:
MambaConv1dPlugin(int dim, int dconv, int preStride, int postStride, nvinfer1::DataType type, bool removePadding,
bool pagedState, bool applySilu);
MambaConv1dPlugin(void const* data, size_t length);
~MambaConv1dPlugin() 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;
template <typename T>
int enqueueImpl(nvinfer1::PluginTensorDesc const* inputDesc, nvinfer1::PluginTensorDesc const* outputDesc,
void const* const* inputs, void* const* outputs, void* workspace, cudaStream_t stream);
// 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;
enum class RequestType : int32_t
{
kCONTEXT = 0,
kGENERATION = 1
};
private:
using IndexType = std::int32_t;
IndexType getInputTensorIdx() const
{
return 0;
};
IndexType getConvStateIdx() const
{
return 1;
};
IndexType getWeightIdx() const
{
return 2;
};
IndexType getBiasIdx() const
{
return 3;
};
IndexType getHostRequestTypesIdx() const
{
return 4;
};
IndexType getLastTokenIdsIdx() const
{
return 5;
};
IndexType getHostContextLengthIdx() const
{
return 6;
};
IndexType getSlotMappingIdx() const
{
// if not remove input padding, host_context_length is not used, so the index is 6
return mRemovePadding ? 7 : 6;
};
void setMambaConv1dParams(tensorrt_llm::kernels::MambaConv1dParamsBase& params,
// sizes
const size_t batch, const size_t dim, const size_t maxSeqLen, const size_t dconv, const size_t preStride,
const size_t postStride,
// device pointers
void const* inPtr, void const* stateInPtr, void* stateOutPtr, void const* convWeight, void const* convBias,
void* outPtr, int const* lastTokenIds, int const* stateSlotMapping, bool removePadding, bool applySilu);
private:
int mDim;
int mDConv;
int mPreStride;
int mPostStride;
nvinfer1::DataType mType;
bool mRemovePadding = false;
bool mPagedState = false;
bool mApplySilu = true;
};
class MambaConv1dPluginCreator : public BaseCreator
{
public:
MambaConv1dPluginCreator();
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:
static nvinfer1::PluginFieldCollection mFC;
static std::vector<nvinfer1::PluginField> mPluginAttributes;
};
} // namespace tensorrt_llm::plugins
#endif // TRT_MAMBA_CONV1D_PLUGIN_H