OSError: libcurand.so.10: cannot open shared object file: No such file or directory

I have just flashed the new JetPack 5.0 on my Jetson AGX Xavier. And I try to follow those instructions NVIDIA L4T PyTorch | NVIDIA NGC to run PyTorch docker container.

I run docker:

sudo docker run -it --rm --runtime nvidia --network host nvcr.io/nvidia/l4t-pytorch:r32.6.1-pth1.9-py3

And when I run python3 and import torch i get:

>>> import torch
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python3.6/dist-packages/torch/__init__.py", line 195, in <module>
    _load_global_deps()
  File "/usr/local/lib/python3.6/dist-packages/torch/__init__.py", line 148, in _load_global_deps
    ctypes.CDLL(lib_path, mode=ctypes.RTLD_GLOBAL)
  File "/usr/lib/python3.6/ctypes/__init__.py", line 348, in __init__
    self._handle = _dlopen(self._name, mode)
OSError: libcurand.so.10: cannot open shared object file: No such file or directory

my nvidia-jetpack specification:

Package: nvidia-jetpack
Version: 5.0.1-b118
Architecture: arm64
Maintainer: NVIDIA Corporation
Installed-Size: 194
Depends: nvidia-cuda (= 5.0.1-b118), nvidia-opencv (= 5.0.1-b118), nvidia-cudnn8 (= 5.0.1-b118), nvidia-tensorrt (= 5.0.1-b118), nvidia-container (= 5.0.1-b118), nvidia-vpi (= 5.0.1-b118), nvidia-nsight-sys (= 5.0.1-b118), nvidia-l4t-jetson-multimedia-api (>> 34.1-0), nvidia-l4t-jetson-multimedia-api (<< 34.2-0)
Homepage: http://developer.nvidia.com/jetson
Priority: standard
Section: metapackages
Filename: pool/main/n/nvidia-jetpack/nvidia-jetpack_5.0.1-b118_arm64.deb
Size: 29376
SHA256: d7ff0e4a95cc11c7a5d0b9e347923e8233ab544431d5db49d18c24944902e7a2
SHA1: fcab6ba9d6dca4a8b3e758d6fb1584baed34f7ed
MD5sum: f168d009bf5e3ee36ab14e646ad4b7dc
Description: NVIDIA Jetpack Meta Package
Description-md5: ad1462289bdbc54909ae109d1d32c0a8

Package: nvidia-jetpack
Version: 5.0-b114
Architecture: arm64
Maintainer: NVIDIA Corporation
Installed-Size: 194
Depends: nvidia-cuda (= 5.0-b114), nvidia-opencv (= 5.0-b114), nvidia-cudnn8 (= 5.0-b114), nvidia-tensorrt (= 5.0-b114), nvidia-container (= 5.0-b114), nvidia-vpi (= 5.0-b114), nvidia-nsight-sys (= 5.0-b114), nvidia-l4t-jetson-multimedia-api (>> 34.1-0), nvidia-l4t-jetson-multimedia-api (<< 34.2-0)
Homepage: http://developer.nvidia.com/jetson
Priority: standard
Section: metapackages
Filename: pool/main/n/nvidia-jetpack/nvidia-jetpack_5.0-b114_arm64.deb
Size: 29370
SHA256: 3b5c14e3ed53cd2517d1a318d056aad3d8b44ff660a489a9b62825d518cf7c5b
SHA1: 608d1f78791a2bdda8bf88443796dfe99f19b199
MD5sum: dbcb9ff116c50b66d5270acd95e05f9a
Description: NVIDIA Jetpack Meta Package
Description-md5: ad1462289bdbc54909ae109d1d32c0a8

additional information

/usr/local/cuda/lib64/ inside docker only contain:

libcudadevrt.a  libcudart_static.a  stubs

/usr/local/cuda/lib64/ on host contain a lot more files

nefault runtime is set to nvidia

ubuntu@ubuntu:~$ docker info
Client:
 Context:    default
 Debug Mode: false

Server:
 Containers: 0
  Running: 0
  Paused: 0
  Stopped: 0
 Images: 53
 Server Version: 20.10.12
 Storage Driver: overlay2
  Backing Filesystem: extfs
  Supports d_type: true
  Native Overlay Diff: true
  userxattr: false
 Logging Driver: json-file
 Cgroup Driver: cgroupfs
 Cgroup Version: 1
 Plugins:
  Volume: local
  Network: bridge host ipvlan macvlan null overlay
  Log: awslogs fluentd gcplogs gelf journald json-file local logentries splunk syslog
 Swarm: inactive
 Runtimes: io.containerd.runc.v2 io.containerd.runtime.v1.linux nvidia runc
 Default Runtime: nvidia
 Init Binary: docker-init
 containerd version: 
 runc version: 7cfd3bd
 init version: 
 Security Options:
  seccomp
   Profile: default
 Kernel Version: 5.10.65-tegra
 Operating System: Ubuntu 20.04.4 LTS
 OSType: linux
 Architecture: aarch64
 CPUs: 4
 Total Memory: 14.56GiB
 Name: ubuntu
 ID: TSUV:CCRX:H2ZP:OR7L:E4SU:KG5S:RTJS:63BA:6UJB:DPKB:7EMK:CBV6
 Docker Root Dir: /mnt/docker
 Debug Mode: false
 Registry: https://index.docker.io/v1/
 Labels:
 Experimental: false
 Insecure Registries:
  127.0.0.0/8
 Live Restore Enabled: false

Hi @uzytkownik786, that r32.6.1 container image was built for JetPack 4.6 (L4T R32.6.1). Since you are running JetPack 5.0.1, please use one of these tags instead:

docker pull nvcr.io/nvidia/l4t-pytorch:r34.1.1-pth1.12-py3
docker pull nvcr.io/nvidia/l4t-pytorch:r34.1.1-pth1.11-py3