Error while training classification model with TAO

Please provide the following information when requesting support.

• Hardware (T4/V100/Xavier/Nano/etc)
V100
• Network Type (Detectnet_v2/Faster_rcnn/Yolo_v4/LPRnet/Mask_rcnn/Classification/etc)
Classification
• TLT Version (Please run “tlt info --verbose” and share “docker_tag” here)
dockers: [‘nvidia/tao/tao-toolkit-tf’, ‘nvidia/tao/tao-toolkit-pyt’, ‘nvidia/tao/tao-toolkit-lm’]
format_version: 2.0
toolkit_version: 3.22.05
published_date: 05/25/2022
• Training spec file(If have, please share here)
• How to reproduce the issue ? (This is for errors. Please share the command line and the detailed log here.)
When I use TAO to train a classification model, I get the following error:

Traceback (most recent call last):
  File "/usr/local/bin/classification", line 8, in <module>
    sys.exit(main())
  File "/root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/makenet/entrypoint/makenet.py", line 12, in main
  File "/root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/common/entrypoint/entrypoint.py", line 263, in launch_job
  File "/root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/common/entrypoint/entrypoint.py", line 47, in get_modules
  File "/usr/lib/python3.6/importlib/__init__.py", line 126, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "<frozen importlib._bootstrap>", line 994, in _gcd_import
  File "<frozen importlib._bootstrap>", line 971, in _find_and_load
  File "<frozen importlib._bootstrap>", line 955, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 665, in _load_unlocked
  File "<frozen importlib._bootstrap_external>", line 678, in exec_module
  File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
  File "/root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/makenet/scripts/evaluate.py", line 34, in <module>
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1585, in __init__
    super(Session, self).__init__(target, graph, config=config)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 699, in __init__
    self._session = tf_session.TF_NewSessionRef(self._graph._c_graph, opts)
tensorflow.python.framework.errors_impl.InternalError: cudaGetDevice() failed. Status: CUDA driver version is insufficient for CUDA runtime version
2022-09-09 15:06:34,933 [INFO] tlt.components.docker_handler.docker_handler: Stopping container.

I am going to delete the old version of the driver

./NVIDIA-Linux-x86_64-515.65.01.run --uninstall


So I am going to upgrade the driver, but the following error occurred:

./NVIDIA-Linux-x86_64-515.65.01.run


Still not working after restart.

There is no update from you for a period, assuming this is not an issue anymore.
Hence we are closing this topic. If need further support, please open a new one.
Thanks

Usually you can update nvidia-driver via below way.
$ apt-cache search nvidia | grep driver
For example, for 510 driver,
$ sudo apt install nvidia-driver-510