mmdeploy/backend_ops/tensorrt/batched_nms/gatherNMSOutputs.cu

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// modify from
// https://github.com/NVIDIA/TensorRT/tree/master/plugin/batchedNMSPlugin
#include <vector>
#include "kernel.h"
#include "trt_plugin_helper.hpp"
template <typename T_BBOX, typename T_SCORE, unsigned nthds_per_cta>
__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,
T_BBOX *nmsedDets, int *nmsedLabels,
bool clipBoxes) {
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) {
nmsedLabels[i] = -1;
nmsedDets[i * 5] = 0;
nmsedDets[i * 5 + 1] = 0;
nmsedDets[i * 5 + 2] = 0;
nmsedDets[i * 5 + 3] = 0;
nmsedDets[i * 5 + 4] = 0;
} else {
const int bboxOffset =
imgId *
(shareLocation ? numPredsPerClass : (numClasses * numPredsPerClass));
const int bboxId =
((shareLocation ? (index % numPredsPerClass)
: index % (numClasses * numPredsPerClass)) +
bboxOffset) *
4;
nmsedLabels[i] = (index % (numClasses * numPredsPerClass)) /
numPredsPerClass; // label
// clipped bbox xmin
nmsedDets[i * 5] =
clipBoxes ? max(min(bboxData[bboxId], T_BBOX(1.)), T_BBOX(0.))
: bboxData[bboxId];
// clipped bbox ymin
nmsedDets[i * 5 + 1] =
clipBoxes ? max(min(bboxData[bboxId + 1], T_BBOX(1.)), T_BBOX(0.))
: bboxData[bboxId + 1];
// clipped bbox xmax
nmsedDets[i * 5 + 2] =
clipBoxes ? max(min(bboxData[bboxId + 2], T_BBOX(1.)), T_BBOX(0.))
: bboxData[bboxId + 2];
// clipped bbox ymax
nmsedDets[i * 5 + 3] =
clipBoxes ? max(min(bboxData[bboxId + 3], T_BBOX(1.)), T_BBOX(0.))
: bboxData[bboxId + 3];
nmsedDets[i * 5 + 4] = score;
}
}
}
template <typename T_BBOX, typename T_SCORE>
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 *nmsedDets, void *nmsedLabels, bool clipBoxes) {
const int BS = 32;
const int GS = 32;
gatherNMSOutputs_kernel<T_BBOX, T_SCORE, BS><<<GS, BS, 0, stream>>>(
shareLocation, numImages, numPredsPerClass, numClasses, topK, keepTopK,
(int *)indices, (T_SCORE *)scores, (T_BBOX *)bboxData,
(T_BBOX *)nmsedDets, (int *)nmsedLabels, clipBoxes);
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 *, bool);
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) {}
nmsOutLaunchConfig(DataType t_bbox, DataType t_score, nmsOutFunc function)
: t_bbox(t_bbox), t_score(t_score), function(function) {}
bool operator==(const nmsOutLaunchConfig &other) {
return t_bbox == other.t_bbox && t_score == other.t_score;
}
};
using nvinfer1::DataType;
static std::vector<nmsOutLaunchConfig> nmsOutFuncVec;
bool nmsOutputInit() {
nmsOutFuncVec.push_back(nmsOutLaunchConfig(
DataType::kFLOAT, DataType::kFLOAT, gatherNMSOutputs_gpu<float, float>));
return true;
}
static bool initialized = nmsOutputInit();
//}}}
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 *nmsedDets, void *nmsedLabels,
bool clipBoxes) {
nmsOutLaunchConfig lc = nmsOutLaunchConfig(DT_BBOX, DT_SCORE);
for (unsigned i = 0; i < nmsOutFuncVec.size(); ++i) {
if (lc == nmsOutFuncVec[i]) {
DEBUG_PRINTF("gatherNMSOutputs kernel %d\n", i);
return nmsOutFuncVec[i].function(stream, shareLocation, numImages,
numPredsPerClass, numClasses, topK,
keepTopK, indices, scores, bboxData,
nmsedDets, nmsedLabels, clipBoxes);
}
}
return STATUS_BAD_PARAM;
}