AssertionError: Config path must be a valid unix path. No file found at: /root/.docker/config.json. Did you run docker login?

Accelerated Computing Intelligent Video Analytics TAO Toolkit
1

tensorrt-8.0.1.6
Quadro RTX 5000 dual GPU
Driver Version: 470.82.00
CUDA Version: 11.4
Ubuntu 18.04
python 3.6
Yolo_v4

nvidia/tao/tao-toolkit-tf:
docker_registry: nvcr.io
docker_tag: v3.21.08-py3

Current dependency
Ubuntu 18.04 LTS
18.04
python

when i run inside the jupyter notebook i get his error

/usr/local/lib/python3.6/dist-packages/tlt/init.py:20: DeprecationWarning:
The nvidia-tlt package will be deprecated soon. Going forward please migrate to using the nvidia-tao package.

warnings.warn(message, DeprecationWarning)
~/.tao_mounts.json wasn’t found. Falling back to obtain mount points and docker configs from ~/.tlt_mounts.json.
Please note that this will be deprecated going forward.
Traceback (most recent call last):
File “/usr/local/bin/tlt”, line 8, in
sys.exit(main())
File “/usr/local/lib/python3.6/dist-packages/tlt/entrypoint/entrypoint.py”, line 115, in main
args[1:]
File “/usr/local/lib/python3.6/dist-packages/tlt/components/instance_handler/local_instance.py”, line 296, in launch_command
docker_logged_in(required_registry=self.task_map[task].docker_registry)
File “/usr/local/lib/python3.6/dist-packages/tlt/components/instance_handler/utils.py”, line 129, in docker_logged_in
data = load_config_file(docker_config)
File “/usr/local/lib/python3.6/dist-packages/tlt/components/instance_handler/utils.py”, line 66, in load_config_file
“No file found at: {}. Did you run docker login?”.format(config_path)
AssertionError: Config path must be a valid unix path. No file found at: /root/.docker/config.json. Did you run docker login?

when i run

docker login nvcr.io
Authenticating with existing credentials…
WARNING! Your password will be stored unencrypted in /home/vaaan/.docker/config.json.
Configure a credential helper to remove this warning. See
docker login | Docker Documentation

Login Succeeded

and the file is present in this path …what am i doing wrong

2

Refer to Is there some spacial things about bpnet? A question about "tlt bpnet dataset_convert " for bpnet - #7 by Morganh

3

I also meet this

4

i didn’t get it

5

Are you running A docker in B docker? If yes, please add -v /var/run/docker.sock:/var/run/docker.sock when you trigger B docker.

6

-v /var/run/docker.sock:/var/run/docker.sock

it gives
-v: command not found

7

What command did you run? Can you share the full command?

8

i just ran it as it is

9

i tried few things now i get this error when starting training

To run with multigpu, please change --gpus based on the number of available GPUs in your machine.
~/.tao_mounts.json wasn’t found. Falling back to obtain mount points and docker configs from ~/.tlt_mounts.json.
Please note that this will be deprecated going forward.
2022-05-16 14:46:06,581 [INFO] root: Registry: [‘nvcr.io’]
2022-05-16 14:46:06,695 [INFO] tlt.components.instance_handler.local_instance: Running command in container: nvcr.io/nvidia/tao/tao-toolkit-tf:v3.21.11-tf1.15.5-py3
2022-05-16 14:46:06,753 [WARNING] tlt.components.docker_handler.docker_handler:
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/vaaan/.tlt_mounts.json” file. You can obtain your
users UID and GID by using the “id -u” and “id -g” commands on the
terminal.
Using TensorFlow backend.
Using TensorFlow backend.
WARNING:tensorflow:Deprecation warnings have been disabled. Set TF_ENABLE_DEPRECATION_WARNINGS=1 to re-enable them.
WARNING:tensorflow:From /root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v4/scripts/train.py:40: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.

2022-05-16 09:16:13,601 [WARNING] tensorflow: From /root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v4/scripts/train.py:40: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.

WARNING:tensorflow:From /root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v4/scripts/train.py:43: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.

2022-05-16 09:16:13,602 [WARNING] tensorflow: From /root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v4/scripts/train.py:43: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.

WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:153: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.

2022-05-16 09:16:14,007 [WARNING] tensorflow: From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:153: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.

Traceback (most recent call last):
File “/root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v4/scripts/train.py”, line 110, in
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/utils.py”, line 528, in return_func
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/utils.py”, line 516, in return_func
File “/root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v4/scripts/train.py”, line 106, 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/yolo_v4/scripts/train.py”, line 49, in run_experiment
File “/root/.cache/bazel/_bazel_root/ed34e6d125608f91724fda23656f1726/execroot/ai_infra/bazel-out/k8-fastbuild/bin/magnet/packages/iva/build_wheel.runfiles/ai_infra/iva/yolo_v4/utils/spec_loader.py”, line 63, in load_experiment_spec
AssertionError: output_channel must be either 1 or 3.
2022-05-16 14:46:14,926 [INFO] tlt.components.docker_handler.docker_handler: Stopping container.

does this mean i overcame the docker problem

10

Yes.

11

Will close this topic. For your latest error, please set “output_channel” in config file.

You can also use latest 3.21.11 docker.