/* * 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 "common/kernels/kernel.h" #include "common/kernels/saturate.h" #include "common/plugin.h" #include #include "gatherNMSOutputs.h" #include using namespace nvinfer1; // __half minus with fallback to float for old sm inline __device__ __half minus_fb(const __half& a, const __half& b) { #if __CUDA_ARCH__ >= 530 return a - b; #else return __float2half(__half2float(a) - __half2float(b)); #endif } // overload for float inline __device__ float minus_fb(const float & a, const float & b) { return a - b; } template __launch_bounds__(nthds_per_cta) __global__ void gatherNMSOutputs_kernel( const bool shareLocation, const int numImages, const int numPredsPerClass, const int numClasses, const int topK, const int keepTopK, const int* indices, const T_SCORE* scores, const T_BBOX* bboxData, int* numDetections, T_BBOX* nmsedBoxes, T_BBOX* nmsedScores, T_BBOX* nmsedClasses, bool clipBoxes, const T_SCORE scoreShift ) { if (keepTopK > topK) return; for (int i = blockIdx.x * nthds_per_cta + threadIdx.x; i < numImages * keepTopK; i += gridDim.x * nthds_per_cta) { const int imgId = i / keepTopK; const int detId = i % keepTopK; const int offset = imgId * numClasses * topK; const int index = indices[offset + detId]; const T_SCORE score = scores[offset + detId]; if (index == -1) { nmsedClasses[i] = -1; nmsedScores[i] = 0; nmsedBoxes[i * 4] = 0; nmsedBoxes[i * 4 + 1] = 0; nmsedBoxes[i * 4 + 2] = 0; nmsedBoxes[i * 4 + 3] = 0; } else { const int bboxOffset = imgId * (shareLocation ? numPredsPerClass : (numClasses * numPredsPerClass)); const int bboxId = ((shareLocation ? (index % numPredsPerClass) : index % (numClasses * numPredsPerClass)) + bboxOffset) * 4; nmsedClasses[i] = (index % (numClasses * numPredsPerClass)) / numPredsPerClass; // label nmsedScores[i] = score; // confidence score nmsedScores[i] = minus_fb(nmsedScores[i], scoreShift); const T_BBOX xMin = bboxData[bboxId]; const T_BBOX yMin = bboxData[bboxId + 1]; const T_BBOX xMax = bboxData[bboxId + 2]; const T_BBOX yMax = bboxData[bboxId + 3]; // clipped bbox xmin nmsedBoxes[i * 4] = clipBoxes ? saturate(xMin) : xMin; // clipped bbox ymin nmsedBoxes[i * 4 + 1] = clipBoxes ? saturate(yMin) : yMin; // clipped bbox xmax nmsedBoxes[i * 4 + 2] = clipBoxes ? saturate(xMax) : xMax; // clipped bbox ymax nmsedBoxes[i * 4 + 3] = clipBoxes ? saturate(yMax) : yMax; atomicAdd(&numDetections[i / keepTopK], 1); } } } template pluginStatus_t gatherNMSOutputs_gpu( cudaStream_t stream, const bool shareLocation, const int numImages, const int numPredsPerClass, const int numClasses, const int topK, const int keepTopK, const void* indices, const void* scores, const void* bboxData, void* numDetections, void* nmsedBoxes, void* nmsedScores, void* nmsedClasses, bool clipBoxes, const float scoreShift ) { CSC(cudaMemsetAsync(numDetections, 0, numImages * sizeof(int), stream), STATUS_FAILURE); const int BS = 32; const int GS = 32; gatherNMSOutputs_kernel<<>>(shareLocation, numImages, numPredsPerClass, numClasses, topK, keepTopK, (int*) indices, (T_SCORE*) scores, (T_BBOX*) bboxData, (int*) numDetections, (T_BBOX*) nmsedBoxes, (T_BBOX*) nmsedScores, (T_BBOX*) nmsedClasses, clipBoxes, T_SCORE(scoreShift) ); CSC(cudaGetLastError(), STATUS_FAILURE); return STATUS_SUCCESS; } // gatherNMSOutputs LAUNCH CONFIG {{{ typedef pluginStatus_t (*nmsOutFunc)(cudaStream_t, const bool, const int, const int, const int, const int, const int, const void*, const void*, const void*, void*, void*, void*, void*, bool, const float); struct nmsOutLaunchConfig { DataType t_bbox; DataType t_score; nmsOutFunc function; nmsOutLaunchConfig(DataType t_bbox, DataType t_score) : t_bbox(t_bbox) , t_score(t_score) , function(nullptr) { } nmsOutLaunchConfig(DataType t_bbox, DataType t_score, nmsOutFunc function) : t_bbox(t_bbox) , t_score(t_score) , function(function) { } bool operator==(nmsOutLaunchConfig const& other) const { return t_bbox == other.t_bbox && t_score == other.t_score; } }; using nvinfer1::DataType; static std::array nmsOutLCOptions = { nmsOutLaunchConfig(DataType::kFLOAT, DataType::kFLOAT, gatherNMSOutputs_gpu), nmsOutLaunchConfig(DataType::kHALF, DataType::kHALF, gatherNMSOutputs_gpu<__half, __half>) }; pluginStatus_t gatherNMSOutputs( cudaStream_t stream, const bool shareLocation, const int numImages, const int numPredsPerClass, const int numClasses, const int topK, const int keepTopK, const DataType DT_BBOX, const DataType DT_SCORE, const void* indices, const void* scores, const void* bboxData, void* numDetections, void* nmsedBoxes, void* nmsedScores, void* nmsedClasses, bool clipBoxes, const float scoreShift ) { nmsOutLaunchConfig lc = nmsOutLaunchConfig(DT_BBOX, DT_SCORE); for (unsigned i = 0; i < nmsOutLCOptions.size(); ++i) { if (lc == nmsOutLCOptions[i]) { DEBUG_PRINTF("gatherNMSOutputs kernel %d\n", i); return nmsOutLCOptions[i].function(stream, shareLocation, numImages, numPredsPerClass, numClasses, topK, keepTopK, indices, scores, bboxData, numDetections, nmsedBoxes, nmsedScores, nmsedClasses, clipBoxes, scoreShift ); } } return STATUS_BAD_PARAM; }