chore: import upstream snapshot with attribution

include/NvInferPluginUtils.h

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+/*
+ * SPDX-FileCopyrightText: Copyright (c) 1993-2026 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 NV_INFER_PLUGIN_UTILS_H
+#define NV_INFER_PLUGIN_UTILS_H
+
+#include "NvInferRuntimeCommon.h"
+
+//!
+//! \file NvInferPluginUtils.h
+//!
+//! This is the API for the Nvidia provided TensorRT plugin utilities.
+//! It lists all the parameters utilized by the TensorRT plugins.
+//!
+
+namespace nvinfer1
+{
+namespace plugin
+{
+
+//!
+//! \struct PriorBoxParameters
+//!
+//! \brief The PriorBox plugin layer generates the prior boxes of designated sizes and aspect ratios across all
+//! dimensions (H x W).
+//!
+//! PriorBoxParameters defines a set of parameters for creating the PriorBox plugin layer.
+//!
+struct PriorBoxParameters
+{
+    float *minSize;          //!< Minimum box size in pixels. Can not be nullptr.
+    float *maxSize;          //!< Maximum box size in pixels. Can be nullptr.
+    float *aspectRatios;     //!< Aspect ratios of the boxes. Can be nullptr.
+    int32_t numMinSize;      //!< Number of elements in minSize. Must be larger than 0.
+    int32_t numMaxSize;      //!< Number of elements in maxSize. Can be 0 or same as numMinSize.
+    int32_t numAspectRatios; //!< Number of elements in aspectRatios. Can be 0.
+    bool flip;               //!< If true, will flip each aspect ratio. For example,
+                             //!< if there is an aspect ratio "r", the aspect ratio "1.0/r" will be generated as well.
+    bool clip;               //!< If true, will clip the prior so that it is within [0,1].
+    float variance[4];       //!< Variance for adjusting the prior boxes.
+    int32_t imgH;            //!< Image height. If 0, then the H dimension of the data tensor will be used.
+    int32_t imgW;            //!< Image width. If 0, then the W dimension of the data tensor will be used.
+    float stepH;             //!< Step in H. If 0, then (float)imgH/h will be used where h is the H dimension of the 1st input tensor.
+    float stepW;             //!< Step in W. If 0, then (float)imgW/w will be used where w is the W dimension of the 1st input tensor.
+    float offset;            //!< Offset to the top left corner of each cell.
+};
+
+//!
+//! \struct RPROIParams
+//!
+//! \brief RPROIParams is used to create the RPROIPlugin instance.
+//!
+struct RPROIParams
+{
+    int32_t poolingH;          //!< Height of the output in pixels after ROI pooling on feature map.
+    int32_t poolingW;          //!< Width of the output in pixels after ROI pooling on feature map.
+    int32_t featureStride;     //!< Feature stride; ratio of input image size to feature map size.
+                               //!< Assuming that max pooling layers in the neural network use square filters.
+    int32_t preNmsTop;         //!< Number of proposals to keep before applying NMS.
+    int32_t nmsMaxOut;         //!< Number of remaining proposals after applying NMS.
+    int32_t anchorsRatioCount; //!< Number of anchor box ratios.
+    int32_t anchorsScaleCount; //!< Number of anchor box scales.
+    float iouThreshold;        //!< IoU (Intersection over Union) threshold used for the NMS step.
+    float minBoxSize;          //!< Minimum allowed bounding box size before scaling, used for anchor box calculation.
+    float spatialScale;        //!< Spatial scale between the input image and the last feature map.
+};
+
+//!
+//! \struct GridAnchorParameters
+//!
+//! \brief The Anchor Generator plugin layer generates the prior boxes of designated sizes and aspect ratios across all dimensions (H x W).
+//! GridAnchorParameters defines a set of parameters for creating the plugin layer for all feature maps.
+//!
+struct GridAnchorParameters
+{
+    float minSize;           //!< Scale of anchors corresponding to finest resolution.
+    float maxSize;           //!< Scale of anchors corresponding to coarsest resolution.
+    float* aspectRatios;     //!< List of aspect ratios to place on each grid point.
+    int32_t numAspectRatios; //!< Number of elements in aspectRatios.
+    int32_t H;               //!< Height of feature map to generate anchors for.
+    int32_t W;               //!< Width of feature map to generate anchors for.
+    float variance[4];       //!< Variance for adjusting the prior boxes.
+};
+
+//!
+//! \brief When performing yolo9000, softmaxTree is helping to do softmax on confidence scores,
+//! for element to get the precise classification through word-tree structured classification definition.
+//!
+struct softmaxTree
+{
+    int32_t* leaf;
+    int32_t n;
+    int32_t* parent;
+    int32_t* child;
+    int32_t* group;
+    char** name;
+    int32_t groups;
+    int32_t* groupSize;
+    int32_t* groupOffset;
+};
+
+//!
+//! \brief The Region plugin layer performs region proposal calculation.
+//!
+//! Generate 5 bounding boxes per cell (for yolo9000, generate 3 bounding boxes per cell).
+//! For each box, calculating its probabilities of objects detections from 80 pre-defined classifications
+//! (yolo9000 has 9418 pre-defined classifications, and these 9418 items are organized as work-tree structure).
+//! RegionParameters defines a set of parameters for creating the Region plugin layer.
+//!
+struct RegionParameters
+{
+    int32_t num;         //!< Number of predicted bounding box for each grid cell.
+    int32_t coords;      //!< Number of coordinates for a bounding box.
+    int32_t classes;     //!< Number of classifications to be predicted.
+    softmaxTree* smTree; //!< Helping structure to do softmax on confidence scores.
+};
+
+} // namespace plugin
+} // namespace nvinfer1
+
+#endif // NV_INFER_PLUGIN_UTILS_H