CLI Examples

This article provides examples of popular use cases illustrating how to use the Command Line Interface (CLI)

Logging in¶

You can log in from the UI, if you are using SSO or credentials

runai login

Logging in via terminal (credentials)¶

runai login user -u [email protected] -p "password"

Configuration¶

Setting a default project¶

runai project set "project-name"

Submitting a workload¶

Naming a workload¶

Use the commands below to provide a name for a workload.

Setting a the workload name ( my_workload_name)¶

runai workspace submit my-workload-name -p test -i ubuntu

Setting a random name with prefix (prefix=workload type)¶

    runai workspace submit -p test -i ubuntu

Setting a random name with specific prefix (prefix determined by flag)¶

runai workspace submit --prefix-name my-prefix-workload-name -p test -i ubuntu

Labels and annotations¶

Labels¶

runai workspace submit -p test -i ubuntu --label name=value --label name2=value2

Annotations¶

runai workspace submit -p test -i ubuntu --annotation name=value --annotation name2=value2

Container's environment variables¶

runai workspace submit -p test -i ubuntu -e name=value -e name2=value2

Requests and limits¶

runai workspace submit  -p "project-name" -i runai.jfrog.io/demo/quickstart-demo   --cpu-core-request 0.3 --cpu-core-limit 1 --cpu-memory-request 50M --cpu-memory-limit 1G  --gpu-devices-request 1 --gpu-memory-request 1G

Submitting and attaching to process¶

runai workspace submit  -p "project-name" -i python  --attach -- python3

Submitting a jupyter notebook¶

runai workspace submit --image jupyter/scipy-notebook -p "project-name" --gpu-devices-request 1 --external-url container=8888 --name-prefix jupyter --command -- start-notebook.sh --NotebookApp.base_url='/${RUNAI_PROJECT}/${RUNAI_JOB_NAME}' --NotebookApp.token=''

Submitting distributed training workload with TensorFlow¶

runai distributed submit -f TF --workers=5 --no-master -g 1 -i kubeflow/tf-mnist-with-summaries:latest -p "project-name" --command -- python /var/tf_mnist/mnist_with_summaries.py --max_steps 1000000

Submitting a multi-pod workload¶

runai training submit  -i alpine -p test --parallelism 2 --completions 2  -- sleep 100000

Submit and bash¶

Submitting a workload with bash command¶

runai training pytorch submit  -p "project-name" -i nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu20.04 -g 1 --workers 3 --command -- bash -c 'trap : TERM INT; sleep infinity & wait'

Bashing into the workload¶

runai training pytorch bash pytorch-06027b585626 -p "project-name"

Submitting distributed training workload with MPI¶

runai  mpi submit dist1 --workers=2 -g 1 \
    -i runai.jfrog.io/demo/quickstart-distributed:v0.3.0 -e RUNAI_SLEEP_SECS=60 -p "project-name"

Submitting with PVC¶

New PVC bounded to the workspace¶

New PVCs will be deleted when the workload is deleted

runai workspace submit -i ubuntu --new-pvc claimname=yuval-3,size=10M,path=/tmp/test

New ephemeral PVC¶

New ephemeral PVCs will be deleted when the workload is deleted or paused

runai workspace submit -i ubuntu --new-pvc claimname=yuval2,size=10M,path=/tmp/test,ephemeral

Existing PVC¶

Existing PVCs will not be deleted when the workload is deleted

runai workspace submit -i ubuntu --existing-pvc claimname=test-pvc-2-project-mn2xs,path=/home/test

Master/Worker configuration¶

--command flag and -- are set both leader (master) and workers command/arguments

--master-args flag sets the master arguments

--master-command flag sets the master commands with arguments

--master-args and --master-command flags can be set together

Overriding both the leader (master) and worker image's arguments¶

runai pytorch submit -i ubuntu -- -a argument_a -b argument_b -c

Overriding both the leader (master) and worker image's commands with arguments¶

runai pytorch submit -i ubuntu --command -- python -m pip install

Overriding arguments of the leader (master) and worker image's arguments with different values¶

runai pytorch submit -i ubuntu --master-args "-a master_arg_a -b master-arg_b'" -- '-a worker_arg_a'

Overriding command with arguments of the leader (master) and worker image's arguments¶

runai pytorch submit -i ubuntu --master-command "python_master -m pip install'" --command -- 'python_worker -m pip install'

Listing objects¶

Listing all workloads in the user's scope¶

runai workload list -A

Listing projects in a YAML format¶

runai project list --yaml

Listing nodes in a JSON format¶

runai node list --json

CLI reference¶

For the full guide of the CLI syntax, see the CLI reference