chore: import upstream snapshot with attribution
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Docker Image CI / build-ubuntu2004 (push) Has been cancelled
This commit is contained in:
wehub-resource-sync
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/*
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* SPDX-FileCopyrightText: Copyright (c) 1993-2026 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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#include "pillarScatter.h"
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#include "common/templates.h"
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#include <memory>
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#include <string_view>
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namespace nvinfer1::plugin
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{
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static char const* const kPLUGIN_VERSION{"1"};
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static char const* const kPLUGIN_NAME{"PillarScatterPlugin"};
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PillarScatterPlugin::PillarScatterPlugin(size_t h, size_t w)
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: feature_y_size_(h)
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, feature_x_size_(w)
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{
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}
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PillarScatterPlugin::PillarScatterPlugin(void const* data, size_t length)
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{
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auto const* d = toPointer<char const>(data);
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feature_y_size_ = readFromBuffer<size_t>(d);
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feature_x_size_ = readFromBuffer<size_t>(d);
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}
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nvinfer1::IPluginV2DynamicExt* PillarScatterPlugin::clone() const noexcept
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{
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try
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{
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auto plugin = std::make_unique<PillarScatterPlugin>(feature_y_size_, feature_x_size_);
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plugin->setPluginNamespace(mNamespace.c_str());
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return plugin.release();
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}
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catch (std::exception const& e)
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{
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caughtError(e);
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}
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return nullptr;
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}
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nvinfer1::DimsExprs PillarScatterPlugin::getOutputDimensions(int32_t outputIndex, nvinfer1::DimsExprs const* inputs,
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int32_t nbInputs, nvinfer1::IExprBuilder& exprBuilder) noexcept
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{
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PLUGIN_ASSERT(outputIndex == 0);
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nvinfer1::DimsExprs output;
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auto batch_size = inputs[0].d[0];
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output.nbDims = 4;
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output.d[0] = batch_size;
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output.d[1] = inputs[0].d[2];
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output.d[2] = exprBuilder.constant(feature_y_size_);
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output.d[3] = exprBuilder.constant(feature_x_size_);
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return output;
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}
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bool PillarScatterPlugin::supportsFormatCombination(
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int32_t pos, nvinfer1::PluginTensorDesc const* inOut, int32_t nbInputs, int32_t nbOutputs) noexcept
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{
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PLUGIN_ASSERT(nbInputs == 3);
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PLUGIN_ASSERT(nbOutputs == 1);
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PluginTensorDesc const& in = inOut[pos];
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if (pos == 0)
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{
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return (in.type == nvinfer1::DataType::kFLOAT || in.type == nvinfer1::DataType::kHALF)
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&& (in.format == TensorFormat::kLINEAR);
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}
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if (pos == 1)
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{
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return (in.type == nvinfer1::DataType::kINT32) && (in.format == TensorFormat::kLINEAR);
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}
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if (pos == 2)
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{
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return (in.type == nvinfer1::DataType::kINT32) && (in.format == TensorFormat::kLINEAR);
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}
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if (pos == 3)
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{
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return (in.type == inOut[0].type) && (in.format == TensorFormat::kLINEAR);
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}
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return false;
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}
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void PillarScatterPlugin::configurePlugin(nvinfer1::DynamicPluginTensorDesc const* in, int32_t nbInputs,
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nvinfer1::DynamicPluginTensorDesc const* out, int32_t nbOutputs) noexcept
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{
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return;
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}
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size_t PillarScatterPlugin::getWorkspaceSize(nvinfer1::PluginTensorDesc const* inputs, int32_t nbInputs,
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nvinfer1::PluginTensorDesc const* outputs, int32_t nbOutputs) const noexcept
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{
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return 0;
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}
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int32_t PillarScatterPlugin::enqueue(nvinfer1::PluginTensorDesc const* inputDesc,
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nvinfer1::PluginTensorDesc const* /* outputDesc */, void const* const* inputs, void* const* outputs,
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void* /* workspace */, cudaStream_t stream) noexcept
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{
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try
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{
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PLUGIN_VALIDATE(inputDesc != nullptr && inputs != nullptr && outputs != nullptr);
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int32_t batchSize = inputDesc[0].dims.d[0];
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int32_t maxPillarNum = inputDesc[0].dims.d[1];
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int32_t numFeatures = inputDesc[0].dims.d[2];
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nvinfer1::DataType inputType = inputDesc[0].type;
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auto coords_data = static_cast<uint32_t const*>(inputs[1]);
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auto params_data = static_cast<uint32_t const*>(inputs[2]);
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uint32_t featureY = feature_y_size_;
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uint32_t featureX = feature_x_size_;
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int32_t status = -1;
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if (inputType == nvinfer1::DataType::kHALF)
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{
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auto pillar_features_data = static_cast<half const*>(inputs[0]);
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auto spatial_feature_data = static_cast<half*>(outputs[0]);
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cudaMemsetAsync(
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spatial_feature_data, 0, batchSize * numFeatures * featureY * featureX * sizeof(half), stream);
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status = pillarScatterKernelLaunch<half>(batchSize, maxPillarNum, numFeatures, pillar_features_data,
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coords_data, params_data, featureX, featureY, spatial_feature_data, stream);
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}
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else if (inputType == nvinfer1::DataType::kFLOAT)
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{
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auto const* pillar_features_data = static_cast<float const*>(inputs[0]);
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auto* spatial_feature_data = static_cast<float*>(outputs[0]);
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cudaMemsetAsync(
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spatial_feature_data, 0, batchSize * numFeatures * featureY * featureX * sizeof(float), stream);
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status = pillarScatterKernelLaunch<float>(batchSize, maxPillarNum, numFeatures, pillar_features_data,
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coords_data, params_data, featureX, featureY, spatial_feature_data, stream);
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}
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PLUGIN_ASSERT(status == STATUS_SUCCESS);
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return status;
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}
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catch (std::exception const& e)
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{
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caughtError(e);
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}
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return -1;
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}
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nvinfer1::DataType PillarScatterPlugin::getOutputDataType(
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int32_t index, nvinfer1::DataType const* inputTypes, int32_t nbInputs) const noexcept
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{
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return inputTypes[0];
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}
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char const* PillarScatterPlugin::getPluginType() const noexcept
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{
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return kPLUGIN_NAME;
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}
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char const* PillarScatterPlugin::getPluginVersion() const noexcept
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{
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return kPLUGIN_VERSION;
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}
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int32_t PillarScatterPlugin::getNbOutputs() const noexcept
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{
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return 1;
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}
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int32_t PillarScatterPlugin::initialize() noexcept
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{
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return 0;
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}
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void PillarScatterPlugin::terminate() noexcept {}
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size_t PillarScatterPlugin::getSerializationSize() const noexcept
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{
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return 3 * sizeof(size_t);
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}
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void PillarScatterPlugin::serialize(void* buffer) const noexcept
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{
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char* d = reinterpret_cast<char*>(buffer);
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writeToBuffer<size_t>(d, feature_y_size_);
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writeToBuffer<size_t>(d, feature_x_size_);
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}
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void PillarScatterPlugin::destroy() noexcept
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{
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delete this;
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}
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void PillarScatterPlugin::setPluginNamespace(char const* libNamespace) noexcept
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{
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mNamespace = libNamespace;
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}
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char const* PillarScatterPlugin::getPluginNamespace() const noexcept
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{
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return mNamespace.c_str();
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}
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PillarScatterPluginCreator::PillarScatterPluginCreator()
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{
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mPluginAttributes.clear();
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mPluginAttributes.emplace_back(PluginField("dense_shape", nullptr, PluginFieldType::kINT32, 1));
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mFC.nbFields = mPluginAttributes.size();
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mFC.fields = mPluginAttributes.data();
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}
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char const* PillarScatterPluginCreator::getPluginName() const noexcept
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{
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return kPLUGIN_NAME;
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}
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char const* PillarScatterPluginCreator::getPluginVersion() const noexcept
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{
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return kPLUGIN_VERSION;
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}
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PluginFieldCollection const* PillarScatterPluginCreator::getFieldNames() noexcept
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{
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return &mFC;
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}
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IPluginV2* PillarScatterPluginCreator::createPlugin(char const* name, PluginFieldCollection const* fc) noexcept
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{
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try
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{
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PluginField const* fields = fc->fields;
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int32_t nbFields = fc->nbFields;
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int32_t targetH = 0;
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int32_t targetW = 0;
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using namespace std::string_view_literals;
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plugin::validateRequiredAttributesExist({"dense_shape"}, fc);
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for (int32_t i = 0; i < nbFields; ++i)
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{
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if (fields[i].name == "dense_shape"sv)
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{
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int32_t const* ts = static_cast<int32_t const*>(fields[i].data);
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targetH = ts[0];
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targetW = ts[1];
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PLUGIN_VALIDATE(targetH > 0 && targetW > 0);
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}
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}
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auto plugin = std::make_unique<PillarScatterPlugin>(targetH, targetW);
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return plugin.release();
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}
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catch (std::exception const& e)
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{
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caughtError(e);
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}
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return nullptr;
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}
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IPluginV2* PillarScatterPluginCreator::deserializePlugin(
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char const* name, void const* serialData, size_t serialLength) noexcept
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{
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try
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{
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// This object will be deleted when the network is destroyed,
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auto plugin = std::make_unique<PillarScatterPlugin>(serialData, serialLength);
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return plugin.release();
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}
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catch (std::exception const& e)
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{
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caughtError(e);
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}
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return nullptr;
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}
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void PillarScatterPluginCreator::setPluginNamespace(char const* libNamespace) noexcept
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{
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mNamespace = libNamespace;
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}
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char const* PillarScatterPluginCreator::getPluginNamespace() const noexcept
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{
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return mNamespace.c_str();
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}
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} // namespace nvinfer1::plugin
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