NvDsInfer Segmentation Fault When Running TLT Models

We are currently running a custom TLT model through Deepstream on a live stream and we consistently reach a segmentation fault error after a given period of time. The seg fault appears to happen in the dequeueOutputBatch call that is in the gst_nvinfer_output_loop method of gstnvinfer.cpp. The call stack for the fault is given below:

<unknown> 0x00007fdeabbdccff
std::__copy_move<true, true, std::random_access_iterator_tag>::__copy_m<float> stl_algobase.h:368
std::__copy_move_a<true, float*, float*> stl_algobase.h:386
std::__copy_move_a2<true, float*, float*> stl_algobase.h:424
std::copy<std::move_iterator<float*>, float*> stl_algobase.h:456
std::__uninitialized_copy<true>::__uninit_copy<std::move_iterator<float*>, float*> stl_uninitialized.h:101
std::uninitialized_copy<std::move_iterator<float*>, float*> stl_uninitialized.h:134
std::__uninitialized_copy_a<std::move_iterator<float*>, float*, float> stl_uninitialized.h:289
std::__uninitialized_move_if_noexcept_a<float*, float*, std::allocator<float> > stl_uninitialized.h:312
std::vector<float, std::allocator<float> >::_M_realloc_insert<float> vector.tcc:431
std::vector<float, std::allocator<float> >::emplace_back<float> vector.tcc:105
std::vector<float, std::allocator<float> >::push_back stl_vector.h:954
NvDsInferParseCustomFrcnnTLT nvdsinfer_custombboxparser_frcnn_tlt.cpp:325
nvdsinfer::DetectPostprocessor::fillDetectionOutput nvdsinfer_context_impl_output_parsing.cpp:721
nvdsinfer::DetectPostprocessor::parseEachBatch nvdsinfer_context_impl.cpp:711
nvdsinfer::InferPostprocessor::postProcessHost nvdsinfer_context_impl.cpp:584
nvdsinfer::NvDsInferContextImpl::dequeueOutputBatch nvdsinfer_context_impl.cpp:1577
gst_nvinfer_output_loop gstnvinfer.cpp:2014
<unknown> 0x00007fdeaddfd2a5
start_thread 0x00007fdeace176db
clone 0x00007fdeabb6f71f

This sometime occurs after a few minutes, sometime it occurs after several hours. However, it regularly occurs during the stream processing

Sorry for the late response, we will do the update soon. Thanks

How about running mp4 file instead of live stream?