I’m struggling with setting up TensorRT to work with tensorflow-gpu1.14
dpkg -l | grep TensorRT
ii graphsurgeon-tf 5.1.2-1+cuda10.0 amd64 GraphSurgeon for TensorRT package
ii libnvinfer-dev 5.1.2-1+cuda10.0 amd64 TensorRT development libraries and headers
ii libnvinfer-samples 5.1.2-1+cuda10.0 all TensorRT samples and documentation
ii libnvinfer5 5.1.2-1+cuda10.0 amd64 TensorRT runtime libraries
ii python-libnvinfer 5.1.2-1+cuda10.0 amd64 Python bindings for TensorRT
ii python-libnvinfer-dev 5.1.2-1+cuda10.0 amd64 Python development package for TensorRT
ii python3-libnvinfer 5.1.2-1+cuda10.0 amd64 Python 3 bindings for TensorRT
ii python3-libnvinfer-dev 5.1.2-1+cuda10.0 amd64 Python 3 development package for TensorRT
ii tensorrt 5.1.2.2-1+cuda10.0 amd64 Meta package of TensorRT
ii uff-converter-tf 5.1.2-1+cuda10.0 amd64 UFF converter for TensorRT package
I have installed version 5.1.2-1+cuda10.0 (also tried from the latest version 6.0.1.5).
But when I run in terminal trtexec, I get the following error:
trtexec: error while loading shared libraries: libcudart.so.10.1: cannot open shared object file: No such file or directory
I have installed cuda-10.0 and all necessary dependencies.
When I run my tensorflow script, somewhere in log I get:
Running FP32 graph
INFO:tensorflow:Linked TensorRT version: (0, 0, 0)
INFO:tensorflow:Loaded TensorRT version: (0, 0, 0)
INFO:tensorflow:Running against TensorRT version 0.0.0
2019-10-04 13:25:21.803379: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcuda.so.1
2019-10-04 13:25:21.821876: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-10-04 13:25:21.822137: I tensorflow/core/grappler/devices.cc:55] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1
2019-10-04 13:25:21.822180: I tensorflow/core/grappler/clusters/single_machine.cc:359] Starting new session
2019-10-04 13:25:21.822501: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-10-04 13:25:21.903012: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-10-04 13:25:21.903394: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x501dc90 executing computations on platform CUDA. Devices:
2019-10-04 13:25:21.903407: I tensorflow/compiler/xla/service/service.cc:175] StreamExecutor device (0): GeForce GTX 1080 Ti, Compute Capability 6.1
2019-10-04 13:25:21.924564: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3600000000 Hz
2019-10-04 13:25:21.925428: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x508dc70 executing computations on platform Host. Devices:
2019-10-04 13:25:21.925439: I tensorflow/compiler/xla/service/service.cc:175] StreamExecutor device (0): <undefined>, <undefined>
2019-10-04 13:25:21.925590: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1005] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-10-04 13:25:21.925831: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1640] Found device 0 with properties:
name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.607
pciBusID: 0000:01:00.0
This really makes me crazy. Why that trtexec wants to link against cudart.so.10.1?