Please provide complete information as applicable to your setup.
• Hardware Platform (Jetson / GPU) GPU
• DeepStream Version 5.0.1
• TensorRT Version TRT 7.0.0
• NVIDIA GPU Driver Version (valid for GPU only) R450.51
• Issue Type( questions, new requirements, bugs)
• How to reproduce the issue ? (This is for bugs. Including which sample app is using, the configuration files content, the command line used and other details for reproducing)
################################################################################
#
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# 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.
#
################################################################################
[application]
enable-perf-measurement=1
perf-measurement-interval-sec=600
#gie-kitti-output-dir=streamscl
[tiled-display]
enable=1
rows=4
columns=3
width=1280
height=720
gpu-id=0
#(0): nvbuf-mem-default - Default memory allocated, specific to particular platform
#(1): nvbuf-mem-cuda-pinned - Allocate Pinned/Host cuda memory, applicable for Tesla
#(2): nvbuf-mem-cuda-device - Allocate Device cuda memory, applicable for Tesla
#(3): nvbuf-mem-cuda-unified - Allocate Unified cuda memory, applicable for Tesla
#(4): nvbuf-mem-surface-array - Allocate Surface Array memory, applicable for Jetson
nvbuf-memory-type=0
sources removed
[sink0]
enable=1
#Type - 1=FakeSink 2=EglSink 3=File
type=1
sync=0
source-id=0
gpu-id=0
nvbuf-memory-type=0
#1=mp4 2=mkv
container=1
#1=h264 2=h265
codec=1
output-file=yolov4.mp4
[sink1]
enable=1
#Type - 1=FakeSink 2=EglSink 3=File 4=UDPSink 5=nvoverlaysink 6=MsgConvBroker
type=6
#msg-conv-config=dstest5_msgconv_sample_config.txt
#(0): PAYLOAD_DEEPSTREAM - Deepstream schema payload
#(1): PAYLOAD_DEEPSTREAM_MINIMAL - Deepstream schema payload minimal
#(256): PAYLOAD_RESERVED - Reserved type
#(257): PAYLOAD_CUSTOM - Custom schema payload
msg-conv-payload-type=0
msg-conv-config=/opt/nvidia/deepstream/deepstream-5.0/sources/deepstream_yolov4/msgconv.txt
msg-broker-proto-lib=/opt/nvidia/deepstream/deepstream-5.0/lib/libnvds_kafka_proto.so
#msg-broker-conn-str=
msg-broker-conn-str=
topic=Raw_Data
#Optional:
msg-broker-config=/opt/nvidia/deepstream/deepstream-5.0/sources/libs/kafka_protocol_adaptor/cfg_kafka.txt
[sink2]
enable=1
#Type - 1=FakeSink 2=EglSink 3=File
type=4
sync=0
source-id=0
gpu-id=0
nvbuf-memory-type=0
codec=2
bitrate=4000000
iframeinterval=10
rtsp-port=8554
profile=0
udp-buffer-size=100000
[osd]
enable=1
gpu-id=0
border-width=1
text-size=12
text-color=1;1;1;1;
text-bg-color=0.3;0.3;0.3;1
font=Serif
show-clock=0
clock-x-offset=800
clock-y-offset=820
clock-text-size=12
clock-color=1;0;0;0
nvbuf-memory-type=0
[streammux]
gpu-id=0
##Boolean property to inform muxer that sources are live
live-source=1
batch-size=10
##time out in usec, to wait after the first buffer is available
##to push the batch even if the complete batch is not formed
batched-push-timeout=40000
## Set muxer output width and height
width=1280
height=720
##Enable to maintain aspect ratio wrt source, and allow black borders, works
##along with width, height properties
enable-padding=0
nvbuf-memory-type=0
# config-file property is mandatory for any gie section.
# Other properties are optional and if set will override the properties set in
# the infer config file.
[primary-gie]
enable=1
gpu-id=0
#model-engine-file=yolov4_1_3_320_512_fp16.engine
labelfile-path=labels.txt
batch-size=10
force-implicit-batch-dim=1
#Required by the app for OSD, not a plugin property
bbox-border-color0=1;0;0;1
bbox-border-color1=0;1;1;1
bbox-border-color2=0;0;1;1
bbox-border-color3=0;1;0;1
interval=0
gie-unique-id=1
nvbuf-memory-type=0
config-file=config_infer_primary_yoloV4.txt
[tracker]
enable=1
tracker-width=640
tracker-height=384
gpu-id=0
#ll-lib-file=/opt/nvidia/deepstream/deepstream-5.0/lib/libnvds_mot_klt.so
ll-lib-file=/opt/nvidia/deepstream/deepstream-5.0/lib/libnvds_nvdcf.so
ll-config-file=tracker_config.yml
enable-batch-process=1
After running for 10hours+ we are getting the below seg fault, has happened 3x now after a few weeks of running.
ERROR: nvdsinfer_context_impl.cpp:1572 Failed to synchronize on cuda copy-coplete-event, cuda err_no:719, err_str:cudaErrorLaunchFailure
12:25:37.866070983 17263 0x55db8604b370 WARN nvinfer gstnvinfer.cpp:2012:gst_nvinfer_output_loop:<primary_gie> error: Failed to dequeue output from inferencing. NvDsInferContext error: NVDSINFER_CUDA_ERROR
ERROR from primary_gie: Failed to dequeue output from inferencing. NvDsInferContext error: NVDSINFER_CUDA_ERROR
Debug info: gstnvinfer.cpp(2012): gst_nvinfer_output_loop (): /GstPipeline:pipeline/GstBin:primary_gie_bin/GstNvInfer:primary_gie
12:25:37.866296196 17263 0x55db8604b370 WARN nvinfer gstnvinfer.cpp:616:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Warning from NvDsInferContextImpl::releaseBatchOutput() <nvdsinfer_context_impl.cpp:1606> [UID = 1]: Tried to release an outputBatchID which is already with the context
Cuda failure: status=719 in CreateTextureObj at line 2555
nvbufsurftransform.cpp:2624: => Transformation Failed -2
Segmentation fault