wehub-resource-sync
529 lines
19 KiB
C++
529 lines
19 KiB
C++
/*
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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 "gridAnchorPlugin.h"
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#include <cmath>
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#include <iostream>
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#include <memory>
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#include <sstream>
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#include <string_view>
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#include <vector>
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using namespace nvinfer1;
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using namespace nvinfer1::pluginInternal;
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namespace nvinfer1::plugin
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{
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namespace
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{
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std::string const kGRID_ANCHOR_PLUGIN_NAMES[] = {"GridAnchor_TRT", "GridAnchorRect_TRT"};
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char const* const kGRID_ANCHOR_PLUGIN_VERSION = "1";
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} // namespace
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GridAnchorGenerator::GridAnchorGenerator(GridAnchorParameters const* paramIn, int32_t numLayers, char const* name)
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: mPluginName(name)
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, mNumLayers(numLayers)
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{
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PLUGIN_CUASSERT(cudaMallocHost((void**) &mNumPriors, mNumLayers * sizeof(int32_t)));
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PLUGIN_CUASSERT(cudaMallocHost((void**) &mDeviceWidths, mNumLayers * sizeof(Weights)));
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PLUGIN_CUASSERT(cudaMallocHost((void**) &mDeviceHeights, mNumLayers * sizeof(Weights)));
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mParam.resize(mNumLayers);
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for (int32_t id = 0; id < mNumLayers; id++)
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{
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mParam[id] = paramIn[id];
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PLUGIN_VALIDATE(mParam[id].numAspectRatios >= 0 && mParam[id].aspectRatios != nullptr);
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mParam[id].aspectRatios = (float*) malloc(sizeof(float) * mParam[id].numAspectRatios);
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for (int32_t i = 0; i < paramIn[id].numAspectRatios; ++i)
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{
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mParam[id].aspectRatios[i] = paramIn[id].aspectRatios[i];
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}
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for (int32_t i = 0; i < 4; ++i)
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{
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mParam[id].variance[i] = paramIn[id].variance[i];
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}
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std::vector<float> tmpScales(mNumLayers + 1);
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// Calculate the scales of SSD model for each layer
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for (int32_t i = 0; i < mNumLayers; i++)
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{
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tmpScales[i] = (mParam[id].minSize + (mParam[id].maxSize - mParam[id].minSize) * id / (mNumLayers - 1));
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}
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// Add another 1.0f to tmpScales to prevent going out side of the vector in calculating the scale_next.
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tmpScales.push_back(1.0F); // has 7 entries
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// scale0 are for the first layer specifically
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std::vector<float> scale0 = {0.1F, tmpScales[0], tmpScales[0]};
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std::vector<float> aspect_ratios;
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std::vector<float> scales;
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// The first layer is different
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if (id == 0)
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{
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for (int32_t i = 0; i < mParam[id].numAspectRatios; i++)
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{
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aspect_ratios.push_back(mParam[id].aspectRatios[i]);
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scales.push_back(scale0[i]);
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}
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mNumPriors[id] = mParam[id].numAspectRatios;
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}
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else
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{
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for (int32_t i = 0; i < mParam[id].numAspectRatios; i++)
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{
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aspect_ratios.push_back(mParam[id].aspectRatios[i]);
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}
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// Additional aspect ratio of 1.0 as described in the paper
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aspect_ratios.push_back(1.0);
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// scales
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for (int32_t i = 0; i < mParam[id].numAspectRatios; i++)
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{
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scales.push_back(tmpScales[id]);
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}
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auto scale_next = (id == mNumLayers - 1)
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? 1.0
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: (mParam[id].minSize + (mParam[id].maxSize - mParam[id].minSize) * (id + 1) / (mNumLayers - 1));
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scales.push_back(std::sqrt(tmpScales[id] * scale_next));
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mNumPriors[id] = mParam[id].numAspectRatios + 1;
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}
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std::vector<float> tmpWidths;
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std::vector<float> tmpHeights;
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// Calculate the width and height of the prior boxes
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for (int32_t i = 0; i < mNumPriors[id]; i++)
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{
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float sqrt_AR = std::sqrt(aspect_ratios[i]);
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tmpWidths.push_back(scales[i] * sqrt_AR);
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tmpHeights.push_back(scales[i] / sqrt_AR);
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}
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mDeviceWidths[id] = copyToDevice(tmpWidths.data(), tmpWidths.size());
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mDeviceHeights[id] = copyToDevice(tmpHeights.data(), tmpHeights.size());
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}
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}
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GridAnchorGenerator::GridAnchorGenerator(void const* data, size_t length, char const* name)
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: mPluginName(name)
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{
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char const *d = reinterpret_cast<char const*>(data), *a = d;
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mNumLayers = read<int32_t>(d);
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PLUGIN_CUASSERT(cudaMallocHost((void**) &mNumPriors, mNumLayers * sizeof(int32_t)));
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PLUGIN_CUASSERT(cudaMallocHost((void**) &mDeviceWidths, mNumLayers * sizeof(Weights)));
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PLUGIN_CUASSERT(cudaMallocHost((void**) &mDeviceHeights, mNumLayers * sizeof(Weights)));
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mParam.resize(mNumLayers);
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for (int32_t id = 0; id < mNumLayers; id++)
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{
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// we have to deserialize GridAnchorParameters by hand
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mParam[id].minSize = read<float>(d);
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mParam[id].maxSize = read<float>(d);
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mParam[id].numAspectRatios = read<int32_t>(d);
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mParam[id].aspectRatios = (float*) malloc(sizeof(float) * mParam[id].numAspectRatios);
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for (int32_t i = 0; i < mParam[id].numAspectRatios; ++i)
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{
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mParam[id].aspectRatios[i] = read<float>(d);
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}
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mParam[id].H = read<int32_t>(d);
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mParam[id].W = read<int32_t>(d);
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for (int32_t i = 0; i < 4; ++i)
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{
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mParam[id].variance[i] = read<float>(d);
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}
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mNumPriors[id] = read<int32_t>(d);
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mDeviceWidths[id] = deserializeToDevice(d, mNumPriors[id]);
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mDeviceHeights[id] = deserializeToDevice(d, mNumPriors[id]);
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}
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PLUGIN_VALIDATE(d == a + length);
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}
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GridAnchorGenerator::~GridAnchorGenerator()
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{
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for (int32_t id = 0; id < mNumLayers; id++)
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{
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PLUGIN_CUERROR(cudaFree(const_cast<void*>(mDeviceWidths[id].values)));
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PLUGIN_CUERROR(cudaFree(const_cast<void*>(mDeviceHeights[id].values)));
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free(mParam[id].aspectRatios);
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}
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PLUGIN_CUERROR(cudaFreeHost(mNumPriors));
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PLUGIN_CUERROR(cudaFreeHost(mDeviceWidths));
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PLUGIN_CUERROR(cudaFreeHost(mDeviceHeights));
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}
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int32_t GridAnchorGenerator::getNbOutputs() const noexcept
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{
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return mNumLayers;
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}
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Dims GridAnchorGenerator::getOutputDimensions(int32_t index, Dims const* inputs, int32_t nbInputDims) noexcept
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{
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// Particularity of the PriorBox layer: no batchSize dimension needed
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// 2 channels. First channel stores the mean of each prior coordinate.
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// Second channel stores the variance of each prior coordinate.
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return Dims3(2, mParam[index].H * mParam[index].W * mNumPriors[index] * 4, 1);
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}
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int32_t GridAnchorGenerator::initialize() noexcept
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{
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return STATUS_SUCCESS;
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}
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void GridAnchorGenerator::terminate() noexcept {}
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size_t GridAnchorGenerator::getWorkspaceSize(int32_t maxBatchSize) const noexcept
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{
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return 0;
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}
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int32_t GridAnchorGenerator::enqueue(
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int32_t batchSize, void const* const* inputs, void* const* outputs, void* workspace, cudaStream_t stream) noexcept
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{
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// Generate prior boxes for each layer
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for (int32_t id = 0; id < mNumLayers; id++)
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{
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void* outputData = outputs[id];
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pluginStatus_t status = anchorGridInference(
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stream, mParam[id], mNumPriors[id], mDeviceWidths[id].values, mDeviceHeights[id].values, outputData);
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if (status != STATUS_SUCCESS)
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{
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return status;
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}
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}
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return STATUS_SUCCESS;
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}
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size_t GridAnchorGenerator::getSerializationSize() const noexcept
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{
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size_t sum = sizeof(int32_t); // mNumLayers
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for (int32_t i = 0; i < mNumLayers; i++)
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{
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sum += 4 * sizeof(int32_t); // mNumPriors, mParam[i].{numAspectRatios, H, W}
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sum += (6 + mParam[i].numAspectRatios)
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* sizeof(float); // mParam[i].{minSize, maxSize, aspectRatios, variance[4]}
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sum += mDeviceWidths[i].count * sizeof(float);
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sum += mDeviceHeights[i].count * sizeof(float);
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}
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return sum;
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}
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void GridAnchorGenerator::serialize(void* buffer) const noexcept
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{
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char *d = reinterpret_cast<char*>(buffer), *a = d;
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write(d, mNumLayers);
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for (int32_t id = 0; id < mNumLayers; id++)
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{
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// we have to serialize GridAnchorParameters by hand
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write(d, mParam[id].minSize);
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write(d, mParam[id].maxSize);
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write(d, mParam[id].numAspectRatios);
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for (int32_t i = 0; i < mParam[id].numAspectRatios; ++i)
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{
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write(d, mParam[id].aspectRatios[i]);
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}
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write(d, mParam[id].H);
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write(d, mParam[id].W);
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for (int32_t i = 0; i < 4; ++i)
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{
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write(d, mParam[id].variance[i]);
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}
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write(d, mNumPriors[id]);
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serializeFromDevice(d, mDeviceWidths[id]);
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serializeFromDevice(d, mDeviceHeights[id]);
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}
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PLUGIN_ASSERT(d == a + getSerializationSize());
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}
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Weights GridAnchorGenerator::copyToDevice(void const* hostData, size_t count) noexcept
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{
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void* deviceData;
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PLUGIN_CUASSERT(cudaMalloc(&deviceData, count * sizeof(float)));
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PLUGIN_CUASSERT(cudaMemcpy(deviceData, hostData, count * sizeof(float), cudaMemcpyHostToDevice));
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return Weights{DataType::kFLOAT, deviceData, int64_t(count)};
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}
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void GridAnchorGenerator::serializeFromDevice(char*& hostBuffer, Weights deviceWeights) const noexcept
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{
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PLUGIN_CUASSERT(
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cudaMemcpy(hostBuffer, deviceWeights.values, deviceWeights.count * sizeof(float), cudaMemcpyDeviceToHost));
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hostBuffer += deviceWeights.count * sizeof(float);
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}
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Weights GridAnchorGenerator::deserializeToDevice(char const*& hostBuffer, size_t count) noexcept
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{
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Weights w = copyToDevice(hostBuffer, count);
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hostBuffer += count * sizeof(float);
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return w;
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}
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bool GridAnchorGenerator::supportsFormat(DataType type, PluginFormat format) const noexcept
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{
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return (type == DataType::kFLOAT && format == PluginFormat::kLINEAR);
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}
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char const* GridAnchorGenerator::getPluginType() const noexcept
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{
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return mPluginName.c_str();
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}
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char const* GridAnchorGenerator::getPluginVersion() const noexcept
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{
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return kGRID_ANCHOR_PLUGIN_VERSION;
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}
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// Set plugin namespace
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void GridAnchorGenerator::setPluginNamespace(char const* pluginNamespace) noexcept
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{
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mPluginNamespace = pluginNamespace;
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}
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char const* GridAnchorGenerator::getPluginNamespace() const noexcept
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{
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return mPluginNamespace.c_str();
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}
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#include <iostream>
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// Return the DataType of the plugin output at the requested index
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DataType GridAnchorGenerator::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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PLUGIN_ASSERT(index < mNumLayers);
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return DataType::kFLOAT;
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}
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// Configure the layer with input and output data types.
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void GridAnchorGenerator::configurePlugin(Dims const* inputDims, int32_t nbInputs, Dims const* outputDims,
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int32_t nbOutputs, DataType const* inputTypes, DataType const* outputTypes, bool const* inputIsBroadcast,
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bool const* outputIsBroadcast, PluginFormat floatFormat, int32_t maxBatchSize) noexcept
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{
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PLUGIN_ASSERT(nbOutputs == mNumLayers);
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PLUGIN_ASSERT(outputDims[0].nbDims == 3);
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}
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// Attach the plugin object to an execution context and grant the plugin the access to some context resource.
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void GridAnchorGenerator::attachToContext(
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cudnnContext* cudnnContext, cublasContext* cublasContext, IGpuAllocator* gpuAllocator) noexcept
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{
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}
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// Detach the plugin object from its execution context.
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void GridAnchorGenerator::detachFromContext() noexcept {}
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void GridAnchorGenerator::destroy() noexcept
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{
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delete this;
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}
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IPluginV2Ext* GridAnchorGenerator::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<GridAnchorGenerator>(mParam.data(), mNumLayers, mPluginName.c_str());
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plugin->setPluginNamespace(mPluginNamespace.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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GridAnchorBasePluginCreator::GridAnchorBasePluginCreator()
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{
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mPluginAttributes.clear();
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mPluginAttributes.emplace_back(PluginField("minSize", nullptr, PluginFieldType::kFLOAT32, 1));
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mPluginAttributes.emplace_back(PluginField("maxSize", nullptr, PluginFieldType::kFLOAT32, 1));
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mPluginAttributes.emplace_back(PluginField("aspectRatios", nullptr, PluginFieldType::kFLOAT32, 1));
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mPluginAttributes.emplace_back(PluginField("featureMapShapes", nullptr, PluginFieldType::kINT32, 1));
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mPluginAttributes.emplace_back(PluginField("variance", nullptr, PluginFieldType::kFLOAT32, 4));
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mPluginAttributes.emplace_back(PluginField("numLayers", 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* GridAnchorBasePluginCreator::getPluginName() const noexcept
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{
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return mPluginName.c_str();
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}
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char const* GridAnchorBasePluginCreator::getPluginVersion() const noexcept
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{
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return kGRID_ANCHOR_PLUGIN_VERSION;
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}
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PluginFieldCollection const* GridAnchorBasePluginCreator::getFieldNames() noexcept
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{
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return &mFC;
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}
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// NOLINTNEXTLINE(readability-function-cognitive-complexity)
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IPluginV2Ext* GridAnchorBasePluginCreator::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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using namespace std::string_view_literals;
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float minScale = 0.2F, maxScale = 0.95F;
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int32_t numLayers = 6;
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std::vector<float> aspectRatios;
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std::vector<int32_t> fMapShapes;
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std::vector<float> layerVariances;
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PluginField const* fields = fc->fields;
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bool const isFMapRect = (kGRID_ANCHOR_PLUGIN_NAMES[1] == mPluginName);
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for (int32_t i = 0; i < fc->nbFields; ++i)
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{
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std::string_view const attrName = fields[i].name;
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if (attrName == "numLayers"sv)
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{
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PLUGIN_VALIDATE(fields[i].type == PluginFieldType::kINT32);
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numLayers = static_cast<int32_t>(*(static_cast<int32_t const*>(fields[i].data)));
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}
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else if (attrName == "minSize"sv)
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{
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PLUGIN_VALIDATE(fields[i].type == PluginFieldType::kFLOAT32);
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minScale = static_cast<float>(*(static_cast<float const*>(fields[i].data)));
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}
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else if (attrName == "maxSize"sv)
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{
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PLUGIN_VALIDATE(fields[i].type == PluginFieldType::kFLOAT32);
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maxScale = static_cast<float>(*(static_cast<float const*>(fields[i].data)));
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}
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else if (attrName == "variance"sv)
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{
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PLUGIN_VALIDATE(fields[i].type == PluginFieldType::kFLOAT32);
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int32_t size = fields[i].length;
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layerVariances.reserve(size);
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auto const* lVar = static_cast<float const*>(fields[i].data);
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for (int32_t j = 0; j < size; j++)
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{
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layerVariances.push_back(*lVar);
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lVar++;
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}
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}
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else if (attrName == "aspectRatios"sv)
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{
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PLUGIN_VALIDATE(fields[i].type == PluginFieldType::kFLOAT32);
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int32_t size = fields[i].length;
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aspectRatios.reserve(size);
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auto const* aR = static_cast<float const*>(fields[i].data);
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for (int32_t j = 0; j < size; j++)
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{
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aspectRatios.push_back(*aR);
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aR++;
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}
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}
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else if (attrName == "featureMapShapes"sv)
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{
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PLUGIN_VALIDATE(fields[i].type == PluginFieldType::kINT32);
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int32_t size = fields[i].length;
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PLUGIN_VALIDATE(!isFMapRect || (size % 2 == 0));
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fMapShapes.reserve(size);
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int32_t const* fMap = static_cast<int32_t const*>(fields[i].data);
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for (int32_t j = 0; j < size; j++)
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{
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fMapShapes.push_back(*fMap);
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fMap++;
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}
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}
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}
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// Reducing the number of boxes predicted by the first layer.
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// This is in accordance with the standard implementation.
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std::vector<float> firstLayerAspectRatios;
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PLUGIN_VALIDATE(numLayers > 0);
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int32_t const numExpectedLayers = static_cast<int32_t>(fMapShapes.size()) >> (isFMapRect ? 1 : 0);
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PLUGIN_VALIDATE(numExpectedLayers == numLayers);
|
|
|
|
int32_t numFirstLayerARs = 3;
|
|
// First layer only has the first 3 aspect ratios from aspectRatios
|
|
firstLayerAspectRatios.reserve(numFirstLayerARs);
|
|
for (int32_t i = 0; i < numFirstLayerARs; ++i)
|
|
{
|
|
firstLayerAspectRatios.push_back(aspectRatios[i]);
|
|
}
|
|
// A comprehensive list of box parameters that are required by anchor generator
|
|
std::vector<GridAnchorParameters> boxParams(numLayers);
|
|
|
|
// One set of box parameters for one layer
|
|
for (int32_t i = 0; i < numLayers; i++)
|
|
{
|
|
int32_t hOffset = (isFMapRect ? i * 2 : i);
|
|
int32_t wOffset = (isFMapRect ? i * 2 + 1 : i);
|
|
// Only the first layer is different
|
|
if (i == 0)
|
|
{
|
|
boxParams[i] = {minScale, maxScale, firstLayerAspectRatios.data(),
|
|
(int32_t) firstLayerAspectRatios.size(), fMapShapes[hOffset], fMapShapes[wOffset],
|
|
{layerVariances[0], layerVariances[1], layerVariances[2], layerVariances[3]}};
|
|
}
|
|
else
|
|
{
|
|
boxParams[i] = {minScale, maxScale, aspectRatios.data(), (int32_t) aspectRatios.size(),
|
|
fMapShapes[hOffset], fMapShapes[wOffset],
|
|
{layerVariances[0], layerVariances[1], layerVariances[2], layerVariances[3]}};
|
|
}
|
|
}
|
|
|
|
auto obj = std::make_unique<GridAnchorGenerator>(boxParams.data(), numLayers, mPluginName.c_str());
|
|
obj->setPluginNamespace(mNamespace.c_str());
|
|
return obj.release();
|
|
}
|
|
catch (std::exception const& e)
|
|
{
|
|
caughtError(e);
|
|
}
|
|
return nullptr;
|
|
}
|
|
|
|
IPluginV2Ext* GridAnchorBasePluginCreator::deserializePlugin(
|
|
char const* name, void const* serialData, size_t serialLength) noexcept
|
|
{
|
|
try
|
|
{
|
|
// This object will be deleted when the network is destroyed, which will
|
|
// call GridAnchor::destroy()
|
|
auto obj = std::make_unique<GridAnchorGenerator>(serialData, serialLength, mPluginName.c_str());
|
|
obj->setPluginNamespace(mNamespace.c_str());
|
|
return obj.release();
|
|
}
|
|
catch (std::exception const& e)
|
|
{
|
|
caughtError(e);
|
|
}
|
|
return nullptr;
|
|
}
|
|
|
|
GridAnchorPluginCreator::GridAnchorPluginCreator()
|
|
{
|
|
mPluginName = kGRID_ANCHOR_PLUGIN_NAMES[0];
|
|
}
|
|
|
|
GridAnchorRectPluginCreator::GridAnchorRectPluginCreator()
|
|
{
|
|
mPluginName = kGRID_ANCHOR_PLUGIN_NAMES[1];
|
|
}
|
|
|
|
} // namespace nvinfer1::plugin
|