I am trying to pull the gen_trt_engine:
!tao deploy faster_rcnn gen_trt_engine --gpu_index $GPU_INDEX \
-m $USER_EXPERIMENT_DIR/modelx.onnx \
-e $SPECS_DIR/default_spec_resnet50-birds_updated.txt \
--data_type fp32 \
--batch_size 8 \
--max_batch_size 4 \
--engine_file $USER_EXPERIMENT_DIR/trt.fp32.engine \
--results_dir $USER_EXPERIMENT_DIR/
But I am getting this error:
2024-03-07 15:07:03,968 [TAO Toolkit] [INFO] root 160: Registry: ['nvcr.io']
2024-03-07 15:07:04,043 [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-deploy
2024-03-07 15:07:06,714 [TAO Toolkit] [INFO] nvidia_tao_cli.components.docker_handler.docker_handler 296: The required docker doesn't exist locally/the manifest has changed. Pulling a new docker.
2024-03-07 15:07:06,714 [TAO Toolkit] [INFO] nvidia_tao_cli.components.docker_handler.docker_handler 155: Pulling the required container. This may take several minutes if you're doing this for the first time. Please wait here.
...
Pulling from repository: nvcr.io/nvidia/tao/tao-toolkit
Docker pull failed. 500 Server Error: Internal Server Error ("Head "https://nvcr.io/v2/nvidia/tao/tao-toolkit/manifests/5.0.0-deploy": unauthorized: authentication required")
What I tried so far:
- Upgraded the TAO toolkit version:
bash setup/quickstart_launcher.sh --upgrade - Restared my machine.
docker login nvcr.ioseems to work.docker pull nvcr.io/nvidia/tao/tao-toolkit-tf:v3.22.05-tf1.15.5-py3gives this error:
Error response from daemon: Head "https://nvcr.io/v2/nvidia/tao/tao-toolkit-tf/manifests/v3.22.05-tf1.15.5-py3": unauthorized: authentication required
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
5.2.0-pyt2.1.0:
docker_registry: nvcr.io
tasks:
1. action_recognition
2. centerpose
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. visual_changenet
5.2.0.1-pyt1.14.0:
docker_registry: nvcr.io
tasks:
1. classification_pyt
2. segformer
dataset:
dockers:
nvidia/tao/tao-toolkit:
5.2.0-data-services:
docker_registry: nvcr.io
tasks:
1. augmentation
2. auto_label
3. annotations
4. analytics
deploy:
dockers:
nvidia/tao/tao-toolkit:
5.2.0-deploy:
docker_registry: nvcr.io
tasks:
1. visual_changenet
2. centerpose
3. classification_pyt
4. classification_tf1
5. classification_tf2
6. deformable_detr
7. detectnet_v2
8. dino
9. dssd
10. efficientdet_tf1
11. efficientdet_tf2
12. faster_rcnn
13. lprnet
14. mask_rcnn
15. ml_recog
16. multitask_classification
17. ocdnet
18. ocrnet
19. optical_inspection
20. retinanet
21. segformer
22. ssd
23. trtexec
24. unet
25. yolo_v3
26. yolo_v4
27. yolo_v4_tiny
format_version: 3.0
toolkit_version: 5.2.0.1
published_date: 01/16/2024
2 posts - 1 participant