Jetson Nano Torch 1.6.0 PyTorch Vision v0.7.0-rc2 Runtime Error

I am getting following error message, i am not able to find out the cause. Could you please help me?

$ sudo python3 train.py --help
[sudo] password for suresh:
Traceback (most recent call last):
File “train.py”, line 7, in
import torch
File “/usr/local/lib/python3.6/dist-packages/torch/init.py”, line 136, in
from torch._C import *
ImportError: /usr/local/lib/python3.6/dist-packages/torch/lib/libtorch_cuda.so: symbol cudnnGetConvolutionBackwardDataAlgorithm version libcudnn.so.8 not defined in file libcudnn.so.8 with link time reference

Hi,

Do you have libcudnn.so.8 installed on your environment?
Please noticed that you will need to use JetPack4.4 for the cuDNN version 8.0 package.

Thanks.

Please below outputs of terminal. Both JetPack4.4 & cuDNN 8.0 is present in the system.

Could you check and advise me how to solve the issue?

  1. print('cuDNN version: ’ + str(torch.backends.cudnn.version()))
    cuDNN version: 8000

$ sudo apt-cache show nvidia-jetpack

Package: nvidia-jetpack
Version: 4.4-b186
Architecture: arm64
Maintainer: NVIDIA Corporation
Installed-Size: 194
Depends: nvidia-cuda (= 4.4-b186), nvidia-opencv (= 4.4-b186), nvidia-cudnn8 (= 4.4-b186), nvidia-tensorrt (= 4.4-b186), nvidia-visionworks (= 4.4-b186), nvidia-container (= 4.4-b186), nvidia-vpi (= 4.4-b186), nvidia-l4t-jetson-multimedia-api (>> 32.4-0), nvidia-l4t-jetson-multimedia-api (<< 32.5-0)
Homepage: http://developer.nvidia.com/jetson
Priority: standard
Section: metapackages
Filename: pool/main/n/nvidia-jetpack/nvidia-jetpack_4.4-b186_arm64.deb
Size: 29346
SHA256: 64f791ddc010f5769b838e7bc28225bb1cc836888c2b7c1989efc396b6b8a7e0
SHA1: 12532999c9fa4688cad2d8506174f77ec696e98a
MD5sum: 4412e36f9dba41a27013b8193c918870
Description: NVIDIA Jetpack Meta Package
Description-md5: ad1462289bdbc54909ae109d1d32c0a8

Package: nvidia-jetpack
Version: 4.4-b144
Architecture: arm64
Maintainer: NVIDIA Corporation
Installed-Size: 195
Depends: nvidia-container-csv-cuda (= 10.2.89-1), libopencv-python (= 4.1.1-2-gd5a58aa75), libvisionworks-sfm-dev (= 0.90.4.501), libvisionworks-dev (= 1.6.0.501), libnvparsers7 (= 7.1.0-1+cuda10.2), libnvinfer-plugin-dev (= 7.1.0-1+cuda10.2), libnvonnxparsers7 (= 7.1.0-1+cuda10.2), libnvinfer-samples (= 7.1.0-1+cuda10.2), libnvinfer-bin (= 7.1.0-1+cuda10.2), libvisionworks-samples (= 1.6.0.501), libvisionworks-tracking-dev (= 0.88.2.501), vpi-samples (= 0.2.0), tensorrt (= 7.1.0.16-1+cuda10.2), libopencv (= 4.1.1-2-gd5a58aa75), libnvinfer-doc (= 7.1.0-1+cuda10.2), libnvparsers-dev (= 7.1.0-1+cuda10.2), libnvidia-container0 (= 0.9.0~beta.1), nvidia-container-csv-visionworks (= 1.6.0.501), cuda-toolkit-10-2 (= 10.2.89-1), graphsurgeon-tf (= 7.1.0-1+cuda10.2), libcudnn8 (= 8.0.0.145-1+cuda10.2), libopencv-samples (= 4.1.1-2-gd5a58aa75), nvidia-container-csv-cudnn (= 8.0.0.145-1+cuda10.2), python-libnvinfer-dev (= 7.1.0-1+cuda10.2), libnvinfer-plugin7 (= 7.1.0-1+cuda10.2), libvisionworks (= 1.6.0.501), libcudnn8-doc (= 8.0.0.145-1+cuda10.2), nvidia-container-toolkit (= 1.0.1-1), libnvinfer-dev (= 7.1.0-1+cuda10.2), nvidia-l4t-jetson-multimedia-api (>> 32.4-0), nvidia-l4t-jetson-multimedia-api (<< 32.5-0), libopencv-dev (= 4.1.1-2-gd5a58aa75), vpi-dev (= 0.2.0), vpi (= 0.2.0), libcudnn8-dev (= 8.0.0.145-1+cuda10.2), python3-libnvinfer (= 7.1.0-1+cuda10.2), python3-libnvinfer-dev (= 7.1.0-1+cuda10.2), opencv-licenses (= 4.1.1-2-gd5a58aa75), nvidia-container-csv-tensorrt (= 7.1.0.16-1+cuda10.2), libnvinfer7 (= 7.1.0-1+cuda10.2), libnvonnxparsers-dev (= 7.1.0-1+cuda10.2), uff-converter-tf (= 7.1.0-1+cuda10.2), nvidia-docker2 (= 2.2.0-1), libvisionworks-sfm (= 0.90.4.501), libnvidia-container-tools (= 0.9.0~beta.1), nvidia-container-runtime (= 3.1.0-1), python-libnvinfer (= 7.1.0-1+cuda10.2), libvisionworks-tracking (= 0.88.2.501)
Conflicts: cuda-command-line-tools-10-0, cuda-compiler-10-0, cuda-cublas-10-0, cuda-cublas-dev-10-0, cuda-cudart-10-0, cuda-cudart-dev-10-0, cuda-cufft-10-0, cuda-cufft-dev-10-0, cuda-cuobjdump-10-0, cuda-cupti-10-0, cuda-curand-10-0, cuda-curand-dev-10-0, cuda-cusolver-10-0, cuda-cusolver-dev-10-0, cuda-cusparse-10-0, cuda-cusparse-dev-10-0, cuda-documentation-10-0, cuda-driver-dev-10-0, cuda-gdb-10-0, cuda-gpu-library-advisor-10-0, cuda-libraries-10-0, cuda-libraries-dev-10-0, cuda-license-10-0, cuda-memcheck-10-0, cuda-misc-headers-10-0, cuda-npp-10-0, cuda-npp-dev-10-0, cuda-nsight-compute-addon-l4t-10-0, cuda-nvcc-10-0, cuda-nvdisasm-10-0, cuda-nvgraph-10-0, cuda-nvgraph-dev-10-0, cuda-nvml-dev-10-0, cuda-nvprof-10-0, cuda-nvprune-10-0, cuda-nvrtc-10-0, cuda-nvrtc-dev-10-0, cuda-nvtx-10-0, cuda-samples-10-0, cuda-toolkit-10-0, cuda-tools-10-0, libcudnn7, libcudnn7-dev, libcudnn7-doc, libnvinfer-plugin6, libnvinfer6, libnvonnxparsers6, libnvparsers6
Homepage: http://developer.nvidia.com/jetson
Priority: standard
Section: metapackages
Filename: pool/main/n/nvidia-jetpack/nvidia-jetpack_4.4-b144_arm64.deb
Size: 30394
SHA256: 1d9d4937623862e4990d25df9a0dd09c78ddbbc4919d1f4c9bf4cd8df09b8869
SHA1: 0608076bbb7ee28f2c388532594ff1951f99e61b
MD5sum: 2c12a5042171a8caa2dd3e4a32246cd2
Description: NVIDIA Jetpack Meta Package
Description-md5: ad1462289bdbc54909ae109d1d32c0a8

I had the same problem and was able to solve it by (re-)installing PyTorch v1.6.0 and torchvision v0.7.0 as explained here: