When running:
(launcher) root@TAO-NVIDIA-INFERENCE-1GPU:~# tao model faster_rcnn train
I am getting this error:
2024-12-03 13:01:27,261 [TAO Toolkit] [INFO] root 160: Registry: ['nvcr.io']
2024-12-03 13:01:27,322 [TAO Toolkit] [INFO] nvidia_tao_cli.components.instance_handler.local_instance 360: Running command in container: nvcr.io/nvidia/tao/tao-toolkit:5.0.0-tf1.15.5
2024-12-03 13:01:27,354 [TAO Toolkit] [INFO] nvidia_tao_cli.components.docker_handler.docker_handler 275: Printing tty value True
Docker instantiation failed with error: 500 Server Error: Internal Server Error ("could not select device driver "" with capabilities: [[gpu]]")
Any clue what’s wrong?
Here are few housekeeping checks if any:
(launcher) root@TAO-NVIDIA-INFERENCE-1GPU:~# nvidia-smi
Command 'nvidia-smi' not found, but can be installed with:
apt install nvidia-340 # version 340.108-0ubuntu5.20.04.2, or
apt install nvidia-utils-390 # version 390.157-0ubuntu0.20.04.1
apt install nvidia-utils-450-server # version 450.248.02-0ubuntu0.20.04.1
apt install nvidia-utils-470 # version 470.223.02-0ubuntu0.20.04.1
apt install nvidia-utils-470-server # version 470.223.02-0ubuntu0.20.04.1
apt install nvidia-utils-525 # version 525.147.05-0ubuntu0.20.04.1
apt install nvidia-utils-525-server # version 525.147.05-0ubuntu0.20.04.1
apt install nvidia-utils-535 # version 535.129.03-0ubuntu0.20.04.1
apt install nvidia-utils-535-server # version 535.129.03-0ubuntu0.20.04.1
apt install nvidia-utils-435 # version 435.21-0ubuntu7
apt install nvidia-utils-440 # version 440.82+really.440.64-0ubuntu6
apt install nvidia-utils-418-server # version 418.226.00-0ubuntu0.20.04.2
(launcher) root@TAO-NVIDIA-INFERENCE-1GPU:~# nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Sun_Jul_28_19:07:16_PDT_2019
Cuda compilation tools, release 10.1, V10.1.243
(launcher) root@TAO-NVIDIA-INFERENCE-1GPU:~# more /etc/os-release
NAME="Ubuntu"
VERSION="20.04.4 LTS (Focal Fossa)"
ID=ubuntu
ID_LIKE=debian
PRETTY_NAME="Ubuntu 20.04.4 LTS"
VERSION_ID="20.04"
HOME_URL="https://www.ubuntu.com/"
SUPPORT_URL="https://help.ubuntu.com/"
BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/"
PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy"
VERSION_CODENAME=focal
UBUNTU_CODENAME=focal
(launcher) root@TAO-NVIDIA-INFERENCE-1GPU:~# tao info --verbose
Configuration of the TAO Toolkit Instance
task_group:
model:
dockers:
nvidia/tao/tao-toolkit:
5.0.0-tf2.11.0:
docker_registry: nvcr.io
tasks:
1. classification_tf2
2. efficientdet_tf2
5.0.0-tf1.15.5:
docker_registry: nvcr.io
tasks:
1. bpnet
2. classification_tf1
3. converter
4. detectnet_v2
5. dssd
6. efficientdet_tf1
7. faster_rcnn
8. fpenet
9. lprnet
10. mask_rcnn
11. multitask_classification
12. retinanet
13. ssd
14. unet
15. yolo_v3
16. yolo_v4
17. yolo_v4_tiny
5.0.0-pyt:
docker_registry: nvcr.io
tasks:
1. action_recognition
2. classification_pyt
3. deformable_detr
4. dino
5. mal
6. ml_recog
7. ocdnet
8. ocrnet
9. optical_inspection
10. pointpillars
11. pose_classification
12. re_identification
13. segformer
dataset:
dockers:
nvidia/tao/tao-toolkit:
5.0.0-data-services:
docker_registry: nvcr.io
tasks:
1. augmentation
2. auto_label
3. annotations
4. analytics
deploy:
dockers:
nvidia/tao/tao-toolkit:
5.0.0-deploy:
docker_registry: nvcr.io
tasks:
1. classification_pyt
2. classification_tf1
3. classification_tf2
4. deformable_detr
5. detectnet_v2
6. dino
7. dssd
8. efficientdet_tf1
9. efficientdet_tf2
10. faster_rcnn
11. lprnet
12. mask_rcnn
13. ml_recog
14. multitask_classification
15. ocdnet
16. ocrnet
17. optical_inspection
18. retinanet
19. segformer
20. ssd
21. trtexec
22. unet
23. yolo_v3
24. yolo_v4
25. yolo_v4_tiny
format_version: 3.0
toolkit_version: 5.0.0
published_date: 07/14/2023
PS: nvcr logged in
2 posts - 2 participants