TensorRT-LLMs/cpp/tensorrt_llm/plugins/selectiveScanPlugin/selectiveScanPlugin.cpp
Kaiyu Xie b57221b764
Update TensorRT-LLM (#941)
* Update TensorRT-LLM

---------

Co-authored-by: Shixiaowei02 <39303645+Shixiaowei02@users.noreply.github.com>
2024-01-23 23:22:35 +08:00

418 lines
15 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.
*/
#include "selectiveScanPlugin.h"
#include "tensorrt_llm/common/assert.h"
using namespace nvinfer1;
using namespace tensorrt_llm::kernels;
using namespace tensorrt_llm::common;
using tensorrt_llm::plugins::SelectiveScanPluginCreator;
using tensorrt_llm::plugins::SelectiveScanPlugin;
static const char* SELECTIVE_SCAN_PLUGIN_VERSION{"1"};
static const char* SELECTIVE_SCAN_PLUGIN_NAME{"SelectiveScan"};
PluginFieldCollection SelectiveScanPluginCreator::mFC{};
std::vector<nvinfer1::PluginField> SelectiveScanPluginCreator::mPluginAttributes;
SelectiveScanPlugin::SelectiveScanPlugin(
int dim, int dstate, bool isVariableB, bool isVariableC, bool deltaSoftplus, nvinfer1::DataType type)
: mDim(dim)
, mDState(dstate)
, mIsVariableB(isVariableB)
, mIsVariableC(isVariableC)
, mDeltaSoftplus(deltaSoftplus)
, mType(type)
{
TLLM_CHECK_WITH_INFO((getSMVersion() >= 80) || (mType != DataType::kBF16),
"Unsupported data type, pre SM 80 GPUs do not support bfloat16");
TLLM_CHECK_WITH_INFO((mType == DataType::kBF16) || (mType == DataType::kFLOAT) || (mType == DataType::kHALF),
"Only support float, half, and bfloat16.");
}
// Parameterized constructor
SelectiveScanPlugin::SelectiveScanPlugin(const void* data, size_t length)
{
const char *d = reinterpret_cast<const char*>(data), *a = d;
read(d, mDim);
read(d, mDState);
read(d, mIsVariableB);
read(d, mIsVariableC);
read(d, mDeltaSoftplus);
read(d, mType);
TLLM_CHECK(d == a + length);
TLLM_CHECK_WITH_INFO((getSMVersion() >= 80) || (mType != DataType::kBF16), "Unsupported data type");
TLLM_CHECK_WITH_INFO((mType == DataType::kBF16) || (mType == DataType::kFLOAT) || (mType == DataType::kHALF),
"Only support float, half, and bfloat16.");
}
// IPluginV2DynamicExt Methods
nvinfer1::IPluginV2DynamicExt* SelectiveScanPlugin::clone() const noexcept
{
auto* plugin = new SelectiveScanPlugin(mDim, mDState, mIsVariableB, mIsVariableC, mDeltaSoftplus, mType);
plugin->setPluginNamespace(mNamespace.c_str());
return plugin;
}
// Outputs
// output_tensor: [batch_size, dim, seq_len]
// state: [batch_size, dim, dstate]
nvinfer1::DimsExprs SelectiveScanPlugin::getOutputDimensions(
int outputIndex, const nvinfer1::DimsExprs* inputs, int nbInputs, nvinfer1::IExprBuilder& exprBuilder) noexcept
{
if (outputIndex == 0)
{
return inputs[getInputTensorIdx()];
}
return inputs[getStateIdx()];
}
bool SelectiveScanPlugin::supportsFormatCombination(
int pos, const nvinfer1::PluginTensorDesc* inOut, int nbInputs, int nbOutputs) noexcept
{
if (pos == getHostRequestTypesIdx())
{
return inOut[pos].type == nvinfer1::DataType::kINT32;
}
else if (pos == getAIdx() || pos == getDeltaBiasIdx() || pos == getDIdx() || pos == nbInputs + 1)
{
return (inOut[pos].type == nvinfer1::DataType::kFLOAT) && (inOut[pos].format == TensorFormat::kLINEAR);
}
else
{
return (inOut[pos].type == mType) && (inOut[pos].format == TensorFormat::kLINEAR);
}
}
void SelectiveScanPlugin::configurePlugin(const nvinfer1::DynamicPluginTensorDesc* in, int nbInputs,
const nvinfer1::DynamicPluginTensorDesc* out, int nbOutputs) noexcept
{
}
size_t SelectiveScanPlugin::getWorkspaceSize(const nvinfer1::PluginTensorDesc* inputs, int nbInputs,
const nvinfer1::PluginTensorDesc* outputs, int nbOutputs) const noexcept
{
return 0;
}
void SelectiveScanPlugin::setSSMParams(SSMParamsBase& params, const size_t batch, const size_t dim, const size_t seqLen,
const size_t dstate, const size_t nChunks, const bool isVariableB, const bool isVariableC, void* statePtr,
const void* x, const void* delta, const void* deltaBias, const void* A, const void* B, const void* C, const void* D,
const void* z, void* out, const size_t strideXBatch, const size_t strideDtBatch, const size_t strideADim,
const size_t strideBBatch, const size_t strideCBatch, const size_t strideZBatch, const size_t strideOutBatch,
const size_t strideStateBatch, const size_t strideStateDim, bool deltaSoftplus)
{
// Reset the parameters
memset(&params, 0, sizeof(params));
params.batch = batch;
params.dim = dim;
params.seqlen = seqLen;
params.dstate = dstate;
params.n_groups = 1;
params.n_chunks = nChunks;
params.dim_ngroups_ratio = dim;
params.delta_softplus = deltaSoftplus;
params.is_variable_B = isVariableB;
params.is_variable_C = isVariableC;
// Set the pointers and strides.
params.u_ptr = const_cast<void*>(x);
params.delta_ptr = const_cast<void*>(delta);
params.A_ptr = const_cast<void*>(A);
params.B_ptr = const_cast<void*>(B);
params.C_ptr = const_cast<void*>(C);
params.D_ptr = const_cast<void*>(D);
params.delta_bias_ptr = const_cast<void*>(deltaBias);
params.out_ptr = out;
params.x_ptr = statePtr;
params.z_ptr = const_cast<void*>(z);
// All stride are in elements, not bytes.
params.A_d_stride = strideADim;
params.A_dstate_stride = 1;
if (!isVariableB)
{
params.B_d_stride = dim * dstate;
}
else
{
params.B_batch_stride = strideBBatch;
params.B_group_stride = strideBBatch;
}
params.B_dstate_stride = !isVariableB ? dstate : seqLen;
if (!isVariableC)
{
params.C_d_stride = dim * dstate;
}
else
{
params.C_batch_stride = strideCBatch;
params.C_group_stride = strideCBatch;
}
params.C_dstate_stride = !isVariableC ? dstate : seqLen;
params.u_batch_stride = strideXBatch;
params.u_d_stride = seqLen;
params.delta_batch_stride = strideDtBatch;
params.delta_d_stride = seqLen;
params.z_batch_stride = strideZBatch;
params.z_d_stride = seqLen;
params.out_batch_stride = strideOutBatch;
params.out_d_stride = seqLen;
params.state_batch_stride = strideStateBatch;
params.state_d_stride = strideStateDim;
}
template <typename T>
int SelectiveScanPlugin::enqueueImpl(const nvinfer1::PluginTensorDesc* inputDesc,
const nvinfer1::PluginTensorDesc* outputDesc, const void* const* inputs, void* const* outputs, void* workspace,
cudaStream_t stream)
{
// inputs
// 0. input_tensor [batch_size, dim, seq_len]
// 1. state [batch_size, dim, dstate]
// 2. delta [batch_size, dim, seq_len]
// 3. delta_bias [dim]
// 4. A [dim, dstate]
// 5. B [batch_size, dstate, seq_len]
// 6. C [batch_size, dstate, seq_len]
// 7. D [dim]
// 8. z [batch_size, dim, seq_len]
// 9. host_request_types [batch_size] int32. 0: context; 1: generation.
// outputs
// 0. output_tensor [batch_size, dim, seq_len]
// 1. state [batch_size, dim, dstate]
auto const batch_size = inputDesc[getInputTensorIdx()].dims.d[0];
auto const seq_len = inputDesc[getInputTensorIdx()].dims.d[2];
auto const stride_state_batch = mDim * mDState;
auto const stride_state_dim = mDState;
auto const stride_x_batch = mDim * seq_len;
auto const stride_dt_batch = mDim * seq_len;
auto const stride_A_dim = mDState;
auto const stride_B_batch = mDState * seq_len;
auto const stride_C_batch = mDState * seq_len;
auto const stride_z_batch = mDim * seq_len;
auto const stride_out_batch = mDim * seq_len;
// only support context or generation, not for both of them
RequestType const* reqTypes = static_cast<RequestType const*>(inputs[getHostRequestTypesIdx()]);
auto const n_chunks = (seq_len + 2048 - 1) / 2048;
SSMParamsBase ssm_params;
setSSMParams(ssm_params, batch_size, mDim, seq_len, mDState, n_chunks, mIsVariableB, mIsVariableC, outputs[1],
inputs[getInputTensorIdx()], inputs[getDeltaIdx()], inputs[getDeltaBiasIdx()], inputs[getAIdx()],
inputs[getBIdx()], inputs[getCIdx()], inputs[getDIdx()], inputs[getZIdx()], outputs[0], stride_x_batch,
stride_dt_batch, stride_A_dim, stride_B_batch, stride_C_batch, stride_z_batch, stride_out_batch,
stride_state_batch, stride_state_dim, mDeltaSoftplus);
if (reqTypes[0] == RequestType::kCONTEXT)
{
invokeSelectiveScan<T, float>(ssm_params, stream);
}
else if (reqTypes[0] == RequestType::kGENERATION)
{
invokeSelectiveScanUpdate<T, float>(ssm_params, stream);
}
return 0;
}
int SelectiveScanPlugin::enqueue(const nvinfer1::PluginTensorDesc* inputDesc,
const nvinfer1::PluginTensorDesc* outputDesc, const void* const* inputs, void* const* outputs, void* workspace,
cudaStream_t stream) noexcept
{
if (mType == DataType::kHALF)
{
return enqueueImpl<half>(inputDesc, outputDesc, inputs, outputs, workspace, stream);
}
else if (mType == DataType::kFLOAT)
{
return enqueueImpl<float>(inputDesc, outputDesc, inputs, outputs, workspace, stream);
}
#ifdef ENABLE_BF16
else if (mType == DataType::kBF16)
{
return enqueueImpl<__nv_bfloat16>(inputDesc, outputDesc, inputs, outputs, workspace, stream);
}
#endif
return 0;
}
// IPluginV2Ext Methods
nvinfer1::DataType SelectiveScanPlugin::getOutputDataType(
int index, const nvinfer1::DataType* inputTypes, int nbInputs) const noexcept
{
if (index == 0)
{
return inputTypes[getInputTensorIdx()];
}
else
{
return inputTypes[getStateIdx()];
}
}
// IPluginV2 Methods
const char* SelectiveScanPlugin::getPluginType() const noexcept
{
return SELECTIVE_SCAN_PLUGIN_NAME;
}
const char* SelectiveScanPlugin::getPluginVersion() const noexcept
{
return SELECTIVE_SCAN_PLUGIN_VERSION;
}
int SelectiveScanPlugin::getNbOutputs() const noexcept
{
return 2;
}
int SelectiveScanPlugin::initialize() noexcept
{
return 0;
}
void SelectiveScanPlugin::terminate() noexcept {}
size_t SelectiveScanPlugin::getSerializationSize() const noexcept
{
return sizeof(mDim) + sizeof(mDState) + sizeof(mIsVariableB) + sizeof(mIsVariableC) + sizeof(mDeltaSoftplus)
+ sizeof(mType);
}
void SelectiveScanPlugin::serialize(void* buffer) const noexcept
{
char *d = static_cast<char*>(buffer), *a = d;
write(d, mDim);
write(d, mDState);
write(d, mIsVariableB);
write(d, mIsVariableC);
write(d, mDeltaSoftplus);
write(d, mType);
assert(d == a + getSerializationSize());
}
void SelectiveScanPlugin::destroy() noexcept
{
delete this;
}
///////////////
SelectiveScanPluginCreator::SelectiveScanPluginCreator()
{
// Fill PluginFieldCollection with PluginField arguments metadata
mPluginAttributes.clear();
mPluginAttributes.emplace_back(PluginField("dim", nullptr, PluginFieldType::kINT32, 16));
mPluginAttributes.emplace_back(PluginField("dstate", nullptr, PluginFieldType::kINT32, 16));
mPluginAttributes.emplace_back(PluginField("is_variable_B", nullptr, PluginFieldType::kINT32, 1));
mPluginAttributes.emplace_back(PluginField("is_variable_C", nullptr, PluginFieldType::kINT32, 1));
mPluginAttributes.emplace_back(PluginField("delta_softplus", nullptr, PluginFieldType::kINT32, 1));
mPluginAttributes.emplace_back(PluginField("type_id", nullptr, PluginFieldType::kINT32, 1));
mFC.nbFields = mPluginAttributes.size();
mFC.fields = mPluginAttributes.data();
}
const char* SelectiveScanPluginCreator::getPluginName() const noexcept
{
return SELECTIVE_SCAN_PLUGIN_NAME;
}
const char* SelectiveScanPluginCreator::getPluginVersion() const noexcept
{
return SELECTIVE_SCAN_PLUGIN_VERSION;
}
const PluginFieldCollection* SelectiveScanPluginCreator::getFieldNames() noexcept
{
return &mFC;
}
IPluginV2* SelectiveScanPluginCreator::createPlugin(const char* name, const PluginFieldCollection* fc) noexcept
{
const PluginField* fields = fc->fields;
int dim, dstate;
bool isVariableB, isVariableC, deltaSoftplus;
nvinfer1::DataType type;
// Read configurations from each fields
for (int i = 0; i < fc->nbFields; ++i)
{
const char* attrName = fields[i].name;
if (!strcmp(attrName, "dim"))
{
TLLM_CHECK(fields[i].type == PluginFieldType::kINT32);
dim = static_cast<int>(*(static_cast<const int*>(fields[i].data)));
}
else if (!strcmp(attrName, "dstate"))
{
TLLM_CHECK(fields[i].type == PluginFieldType::kINT32);
dstate = static_cast<int>(*(static_cast<const int*>(fields[i].data)));
}
else if (!strcmp(attrName, "is_variable_B"))
{
TLLM_CHECK(fields[i].type == PluginFieldType::kINT8);
isVariableB = static_cast<bool>(*(static_cast<const bool*>(fields[i].data)));
}
else if (!strcmp(attrName, "is_variable_C"))
{
TLLM_CHECK(fields[i].type == PluginFieldType::kINT8);
isVariableC = static_cast<bool>(*(static_cast<const bool*>(fields[i].data)));
}
else if (!strcmp(attrName, "delta_softplus"))
{
TLLM_CHECK(fields[i].type == PluginFieldType::kINT8);
deltaSoftplus = static_cast<bool>(*(static_cast<const bool*>(fields[i].data)));
}
else if (!strcmp(attrName, "type_id"))
{
TLLM_CHECK(fields[i].type == PluginFieldType::kINT32);
type = static_cast<nvinfer1::DataType>(*(static_cast<const nvinfer1::DataType*>(fields[i].data)));
}
}
try
{
auto* obj = new SelectiveScanPlugin(dim, dstate, isVariableB, isVariableC, deltaSoftplus, type);
obj->setPluginNamespace(mNamespace.c_str());
return obj;
}
catch (const std::exception& e)
{
caughtError(e);
}
return nullptr;
}
IPluginV2* SelectiveScanPluginCreator::deserializePlugin(
const char* name, const void* serialData, size_t serialLength) noexcept
{
// This object will be deleted when the network is destroyed, which will
// call SelectiveScanPlugin::destroy()
try
{
auto* obj = new SelectiveScanPlugin(serialData, serialLength);
obj->setPluginNamespace(mNamespace.c_str());
return obj;
}
catch (const std::exception& e)
{
caughtError(e);
}
return nullptr;
}