Rajeev Rao
60d62e66d2
This graceful failure is needed to enable tests under `trt_mod_test`. `PLUGIN_ASSERT` is used in many places inside plugin methods, most of which are `noexcept` and do not contain try-catch blocks. So changing `PLUGIN_ASSERT` would require a major refactor which is beyond rel-8.4. Instead, this MR introduces `PLUGIN_VALIDATE` as a temporary replacement for `PLUGIN_ASSERT` in places where it is required to enable valid/invalid attribute tests (mostly `createPlugin` and plugin constructors). i.e. `PLUGIN_VALIDATE` implements the expected behavior of `PLUGIN_ASSERT` (throws) while `PLUGIN_ASSERT` still aborts. Signed-off-by: samurdhi karunaratne <skarunaratne@nvidia.com> Signed-off-by: Rajeev Rao <rajeevrao@nvidia.com>
342 lines
12 KiB
C++
342 lines
12 KiB
C++
/*
|
|
* SPDX-FileCopyrightText: Copyright (c) 1993-2022 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 "groupNormalizationPlugin.h"
|
|
#include <numeric>
|
|
#include <stdexcept>
|
|
|
|
using namespace nvinfer1;
|
|
using nvinfer1::plugin::GroupNormalizationPlugin;
|
|
using nvinfer1::plugin::GroupNormalizationPluginCreator;
|
|
|
|
#define PLUGIN_CHECK_CUDNN(call) \
|
|
do \
|
|
{ \
|
|
cudnnStatus_t status = call; \
|
|
if (status != CUDNN_STATUS_SUCCESS) \
|
|
{ \
|
|
return status; \
|
|
} \
|
|
} while (0)
|
|
|
|
namespace
|
|
{
|
|
constexpr const char* GROUP_NORM_VERSION{"1"};
|
|
constexpr const char* GROUP_NORM_NAME{"GroupNormalizationPlugin"};
|
|
} // namespace
|
|
|
|
// // Static class fields initialization
|
|
PluginFieldCollection GroupNormalizationPluginCreator::mFC{};
|
|
std::vector<nvinfer1::PluginField> GroupNormalizationPluginCreator::mPluginAttributes;
|
|
|
|
REGISTER_TENSORRT_PLUGIN(GroupNormalizationPluginCreator);
|
|
|
|
GroupNormalizationPlugin::GroupNormalizationPlugin(float epsilon, int nbGroups)
|
|
: mEpsilon(epsilon)
|
|
, mNbGroups(nbGroups)
|
|
{
|
|
// Number of groups should be positive
|
|
PLUGIN_VALIDATE(nbGroups > 0);
|
|
}
|
|
|
|
int GroupNormalizationPlugin::initialize() noexcept
|
|
{
|
|
return 0;
|
|
}
|
|
|
|
GroupNormalizationPlugin::GroupNormalizationPlugin(const void* data, size_t length)
|
|
{
|
|
// Deserialize in the same order as serialization
|
|
deserialize_value(&data, &length, &mEpsilon);
|
|
deserialize_value(&data, &length, &mNbGroups);
|
|
}
|
|
|
|
const char* GroupNormalizationPlugin::getPluginType() const noexcept
|
|
{
|
|
return GROUP_NORM_NAME;
|
|
}
|
|
|
|
const char* GroupNormalizationPlugin::getPluginVersion() const noexcept
|
|
{
|
|
return GROUP_NORM_VERSION;
|
|
}
|
|
|
|
int GroupNormalizationPlugin::getNbOutputs() const noexcept
|
|
{
|
|
return 1;
|
|
}
|
|
|
|
nvinfer1::DimsExprs GroupNormalizationPlugin::getOutputDimensions(
|
|
int index, const nvinfer1::DimsExprs* inputs, int nbInputs, nvinfer1::IExprBuilder& exprBuilder) noexcept
|
|
{
|
|
// Input (from previous layer), scale and bias are the three inputs to the plugin.
|
|
PLUGIN_ASSERT(nbInputs == 3);
|
|
PLUGIN_ASSERT(index == 0);
|
|
nvinfer1::DimsExprs output(inputs[0]);
|
|
return output;
|
|
}
|
|
|
|
void GroupNormalizationPlugin::attachToContext(
|
|
cudnnContext* cudnnContext, cublasContext* cublasContext, IGpuAllocator* gpuAllocator) noexcept
|
|
{
|
|
_cudnn_handle = cudnnContext;
|
|
PLUGIN_CUDNNASSERT(cudnnCreateTensorDescriptor(&desc));
|
|
PLUGIN_CUDNNASSERT(cudnnCreateTensorDescriptor(&bnDesc));
|
|
}
|
|
|
|
// Detach the plugin object from its execution context.
|
|
void GroupNormalizationPlugin::detachFromContext() noexcept
|
|
{
|
|
PLUGIN_CUDNNASSERT(cudnnDestroyTensorDescriptor(desc));
|
|
PLUGIN_CUDNNASSERT(cudnnDestroyTensorDescriptor(bnDesc));
|
|
}
|
|
|
|
int GroupNormalizationPlugin::enqueue(const nvinfer1::PluginTensorDesc* inputDesc,
|
|
const nvinfer1::PluginTensorDesc* outputDesc, const void* const* inputs, void* const* outputs, void* workspace,
|
|
cudaStream_t stream) noexcept
|
|
{
|
|
// Get the input dimensions
|
|
nvinfer1::Dims input_dims = inputDesc[0].dims;
|
|
int batchSize = input_dims.d[0];
|
|
int nbChannels = input_dims.d[1];
|
|
|
|
// Calculate size of each group
|
|
int groupSize = nbChannels / mNbGroups;
|
|
|
|
mChannelVolume
|
|
= std::accumulate(input_dims.d + 2, input_dims.d + inputDesc[0].dims.nbDims, 1, std::multiplies<int>());
|
|
|
|
PLUGIN_CHECK_CUDNN(cudnnSetTensor4dDescriptor(desc, // descriptor
|
|
CUDNN_TENSOR_NCHW, // tensor format
|
|
CUDNN_DATA_FLOAT, // type
|
|
1, // Batchsize
|
|
batchSize * mNbGroups, // Channels
|
|
groupSize, // Height
|
|
mChannelVolume // Width
|
|
));
|
|
|
|
PLUGIN_CHECK_CUDNN(cudnnDeriveBNTensorDescriptor(bnDesc, desc, CUDNN_BATCHNORM_SPATIAL));
|
|
PLUGIN_CHECK_CUDNN(cudnnSetStream(_cudnn_handle, stream));
|
|
|
|
// Reshape the data according in the cudnnSetTensor4dDescriptor.
|
|
float a = 1.F;
|
|
float b = 0.F;
|
|
PLUGIN_CHECK_CUDNN(cudnnBatchNormalizationForwardTraining(_cudnn_handle, // handle
|
|
CUDNN_BATCHNORM_SPATIAL, // BatchNormMode_t, try also non persistent
|
|
&a, //
|
|
&b, //
|
|
desc, // in/out descriptor
|
|
inputs[0], // input
|
|
desc, // in/out descriptor
|
|
outputs[0], // output
|
|
bnDesc, //
|
|
bnScale, // 1
|
|
bnBias, // 0
|
|
0.0, // exponential average factor
|
|
nullptr, // resultRunningMean
|
|
nullptr, // resultRunningVar
|
|
mEpsilon, // eps
|
|
nullptr, // resultSaveMean
|
|
nullptr // resultSaveInvVar
|
|
));
|
|
|
|
float* output = static_cast<float*>(outputs[0]);
|
|
return scaleShiftChannelsInplace(output, batchSize, nbChannels, mChannelVolume, static_cast<const float*>(inputs[2]), static_cast<const float*>(inputs[1]), stream); //mBetaDev, mGammaDev,
|
|
}
|
|
|
|
size_t GroupNormalizationPlugin::getSerializationSize() const noexcept
|
|
{
|
|
return sizeof(mNbGroups) + sizeof(mEpsilon);
|
|
}
|
|
|
|
void GroupNormalizationPlugin::serialize(void* buffer) const noexcept
|
|
{
|
|
serialize_value(&buffer, mEpsilon);
|
|
serialize_value(&buffer, mNbGroups);
|
|
}
|
|
|
|
bool GroupNormalizationPlugin::supportsFormatCombination(
|
|
int pos, const nvinfer1::PluginTensorDesc* inOut, int nbInputs, int nbOutputs) noexcept
|
|
{
|
|
PLUGIN_ASSERT(inOut && pos < (nbInputs + nbOutputs));
|
|
return ((inOut[pos].type == nvinfer1::DataType::kFLOAT) && inOut[pos].format == nvinfer1::PluginFormat::kLINEAR
|
|
&& inOut[pos].type == inOut[0].type);
|
|
}
|
|
|
|
void GroupNormalizationPlugin::terminate() noexcept
|
|
{
|
|
PLUGIN_CUASSERT(cudaFree(bnScale));
|
|
PLUGIN_CUASSERT(cudaFree(bnBias));
|
|
}
|
|
|
|
void GroupNormalizationPlugin::destroy() noexcept
|
|
{
|
|
// This gets called when the network containing plugin is destroyed
|
|
delete this;
|
|
}
|
|
|
|
IPluginV2DynamicExt* GroupNormalizationPlugin::clone() const noexcept
|
|
{
|
|
try
|
|
{
|
|
auto* plugin = new GroupNormalizationPlugin(mEpsilon, mNbGroups);
|
|
plugin->setPluginNamespace(mPluginNamespace);
|
|
return plugin;
|
|
}
|
|
catch (std::exception const& e)
|
|
{
|
|
caughtError(e);
|
|
}
|
|
return nullptr;
|
|
}
|
|
|
|
void GroupNormalizationPlugin::configurePlugin(const nvinfer1::DynamicPluginTensorDesc* in, int nbInputs,
|
|
const nvinfer1::DynamicPluginTensorDesc* out, int nbOutputs) noexcept
|
|
{
|
|
|
|
for (int i = 0; i < nbInputs; i++)
|
|
{
|
|
for (int j = 0; j < in[0].desc.dims.nbDims; j++)
|
|
{
|
|
// Do not support dynamic dimensions
|
|
PLUGIN_ASSERT(in[0].desc.dims.d[j] != -1);
|
|
}
|
|
}
|
|
|
|
int batchSize = in[0].desc.dims.d[0];
|
|
int nbChannels = in[0].desc.dims.d[1];
|
|
|
|
// Allocate device memory and initialize scale and bias values
|
|
PLUGIN_CUASSERT(cudaMalloc(&bnScale, batchSize * nbChannels * sizeof(float)));
|
|
PLUGIN_CUASSERT(cudaMalloc(&bnBias, batchSize * nbChannels * sizeof(float)));
|
|
|
|
// allot ones and zeros to bn parameters
|
|
std::vector<float> ones(nbChannels, 1.F);
|
|
PLUGIN_CUASSERT(cudaMemcpy(bnScale, ones.data(), nbChannels * sizeof(float), cudaMemcpyHostToDevice));
|
|
|
|
std::vector<float> zeroes(nbChannels, 0.F);
|
|
PLUGIN_CUASSERT(cudaMemcpy(bnBias, zeroes.data(), nbChannels * sizeof(float), cudaMemcpyHostToDevice));
|
|
}
|
|
|
|
nvinfer1::DataType GroupNormalizationPlugin::getOutputDataType(
|
|
int index, const nvinfer1::DataType* inputTypes, int nbInputs) const noexcept
|
|
{
|
|
PLUGIN_ASSERT(inputTypes && nbInputs > 0 && index == 0);
|
|
return inputTypes[0];
|
|
}
|
|
|
|
size_t GroupNormalizationPlugin::getWorkspaceSize(const nvinfer1::PluginTensorDesc* inputs, int nbInputs,
|
|
const nvinfer1::PluginTensorDesc* outputs, int nbOutputs) const noexcept
|
|
{
|
|
return 0;
|
|
}
|
|
|
|
void GroupNormalizationPlugin::setPluginNamespace(const char* libNamespace) noexcept
|
|
{
|
|
mPluginNamespace = libNamespace;
|
|
}
|
|
|
|
const char* GroupNormalizationPlugin::getPluginNamespace() const noexcept
|
|
{
|
|
return mPluginNamespace;
|
|
}
|
|
|
|
GroupNormalizationPluginCreator::GroupNormalizationPluginCreator()
|
|
{
|
|
mPluginAttributes.clear();
|
|
mPluginAttributes.emplace_back(PluginField("eps", nullptr, PluginFieldType::kFLOAT32, 1));
|
|
mPluginAttributes.emplace_back(PluginField("num_groups", nullptr, PluginFieldType::kINT32, 1));
|
|
|
|
mFC.nbFields = mPluginAttributes.size();
|
|
mFC.fields = mPluginAttributes.data();
|
|
}
|
|
|
|
const char* GroupNormalizationPluginCreator::getPluginName() const noexcept
|
|
{
|
|
return GROUP_NORM_NAME;
|
|
}
|
|
|
|
const char* GroupNormalizationPluginCreator::getPluginVersion() const noexcept
|
|
{
|
|
return GROUP_NORM_VERSION;
|
|
}
|
|
|
|
const PluginFieldCollection* GroupNormalizationPluginCreator::getFieldNames() noexcept
|
|
{
|
|
return &mFC;
|
|
}
|
|
|
|
const char* GroupNormalizationPluginCreator::getPluginNamespace() const noexcept
|
|
{
|
|
return mNamespace.c_str();
|
|
}
|
|
|
|
void GroupNormalizationPluginCreator::setPluginNamespace(const char* libNamespace) noexcept
|
|
{
|
|
mNamespace = libNamespace;
|
|
}
|
|
|
|
IPluginV2DynamicExt* GroupNormalizationPluginCreator::createPlugin(
|
|
const char* name, const PluginFieldCollection* fc) noexcept
|
|
{
|
|
try
|
|
{
|
|
// Set default values
|
|
int nbGroups{1};
|
|
float epsilon{0.00001F};
|
|
for (int i = 0; i < fc->nbFields; i++)
|
|
{
|
|
std::string field_name(fc->fields[i].name);
|
|
if (field_name.compare("eps") == 0)
|
|
{
|
|
epsilon = *static_cast<const float*>(fc->fields[i].data);
|
|
}
|
|
if (field_name.compare("num_groups") == 0)
|
|
{
|
|
nbGroups = *static_cast<const int*>(fc->fields[i].data);
|
|
}
|
|
}
|
|
|
|
GroupNormalizationPlugin* plugin = new GroupNormalizationPlugin(epsilon, nbGroups);
|
|
plugin->setPluginNamespace(mNamespace.c_str());
|
|
|
|
return plugin;
|
|
}
|
|
catch (std::exception const& e)
|
|
{
|
|
caughtError(e);
|
|
}
|
|
return nullptr;
|
|
}
|
|
|
|
IPluginV2DynamicExt* GroupNormalizationPluginCreator::deserializePlugin(
|
|
const char* name, const void* serialData, size_t serialLength) noexcept
|
|
{
|
|
try
|
|
{
|
|
GroupNormalizationPlugin* plugin = new GroupNormalizationPlugin(serialData, serialLength);
|
|
plugin->setPluginNamespace(mNamespace.c_str());
|
|
|
|
return plugin;
|
|
}
|
|
catch (std::exception const& e)
|
|
{
|
|
caughtError(e);
|
|
}
|
|
return nullptr;
|
|
}
|