Network Type (Detectnet_v2/Faster_rcnn/Yolo_v4/LPRnet/Mask_rcnn/Classification/etc)

Hardware I am using is Jetson AGX ORIN and I am running TAO tool kit/notebook. Getting following error:

Any pointer to the problem is appreciated.

print(“To run with multigpu, please change --gpus based on the number of available GPUs in your machine.”)
!tao model yolo_v4 train -e $SPECS_DIR/yolo_v4_train_resnet18_kitti_seq.txt
-r $USER_EXPERIMENT_DIR/experiment_dir_unpruned
–gpus 1

To run with multigpu, please change --gpus based on the number of available GPUs in your machine. 2024-04-28 12:49:27,421 [TAO Toolkit] [INFO] root 160: Registry: [‘’] 2024-04-28 12:49:27,550 [TAO Toolkit] [INFO] nvidia_tao_cli.components.instance_handler.local_instance 361: Running command in container: 2024-04-28 12:49:27,692 [TAO Toolkit] [WARNING] nvidia_tao_cli.components.docker_handler.docker_handler 293: Docker will run the commands as root. If you would like to retain your local host permissions, please add the “user”:“UID:GID” in the DockerOptions portion of the “/home/datasigns/.tao_mounts.json” file. You can obtain your users UID and GID by using the “id -u” and “id -g” commands on the terminal. 2024-04-28 12:49:27,692 [TAO Toolkit] [INFO] nvidia_tao_cli.components.docker_handler.docker_handler 301: Printing tty value True Docker instantiation failed with error: 500 Server Error: Internal Server Error (“failed to create task for container: failed to create shim task: OCI runtime create failed: runc create failed: unable to start container process: error during container init: error running hook #0: error running hook: exit status 1, stdout: , stderr: Auto-detected mode as ‘csv’ invoking the NVIDIA Container Runtime Hook directly (e.g. specifying the docker --gpus flag) is not supported. Please use the NVIDIA Container Runtime (e.g. specify the --runtime=nvidia flag) instead.: unknown”)

It is expected to run in dgpu machines instead of Jetson devices.

I’m am sorry . What are Dhrupad machines. I am under the impression that AGX ORIN are edge devices should be able to cater edge solutions.


It was typo I mean what are dGPU machines? Also I need to know what version of TOA has AGX support?

The dGPU machine has discrete GPU. For example, A100, V100, T4, etc. Refer to TAO Toolkit Quick Start Guide - NVIDIA Docs.

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