runai training submit
submit a standard training workload
runai training submit [flags]Examples
# Submit a workload
runai training standard submit <name> -p <project_name> -i runai.jfrog.io/demo/quickstart-demo
# Submit a workload with arguments
runai training standard submit <name> -p <project_name> -i ubuntu -- ls -la
# Submit a workload with a custom command
runai training standard submit <name> -p <project_name> -i ubuntu --command -- echo "Hello, World"
# Submit a workload with a field reference
runai training standard submit <name> -p <project_name> -i ubuntu --env-pod-field-ref "PROJECT=metadata.labels['project']"
# Submit the workload jupyter notebook
runai training standard submit <name> -p <project_name> -i jupyter/scipy-notebook --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='Options
--allow-privilege-escalation Allow the job to gain additional privileges after starting
--annotation stringArray Set of annotations to populate into the container running the workload
--attach If true, wait for the pod to start running, and then attach to the pod as if 'runai attach' was called. Attach makes tty and stdin true by default. Defaults to false
--auto-deletion-time-after-completion duration The length of time (like 5s, 2m, or 3h, higher than zero) after which a completed job is automatically deleted (default 0s)
--backoff-limit int32 The number of times the job will be retried before failing
--capability stringArray The POSIX capabilities to add when running containers. Defaults to the default set of capabilities granted by the container runtime.
-c, --command If true, override the image's entrypoint with the command supplied after '--'
--configmap-map-volume stringArray Mount ConfigMap as a volume. Use the fhe format name=CONFIGMAP_NAME,path=PATH
--cpu-core-limit float CPU core limit (e.g. 0.5, 1)
--cpu-core-request float CPU core request (e.g. 0.5, 1)
--cpu-memory-limit string CPU memory limit to allocate for the job (e.g. 1G, 500M)
--cpu-memory-request string CPU memory to allocate for the job (e.g. 1G, 500M)
--create-home-dir Create a temporary home directory. Defaults to true when --run-as-user is set, false otherwise
--env-pod-field-ref stringArray Set an environment variable in the container with a field reference as value. Format: "ENV_VARIABLE=FIELD_REFERENCE"
-e, --environment stringArray Set environment variables in the container
--existing-pvc stringArray Mount an existing persistent volume. Use the format: claimname=CLAIM_NAME,path=PATH <auto-complete supported>
--extended-resource stringArray Request access to an extended resource. Use the format: resource_name=quantity
--external-url stringArray Expose URL from the job container. Use the format: container=9443,url=https://external.runai.com,authusers=user1,authgroups=group1
--git-sync stringArray Specifies git repositories to mount into the container. Use the format: name=NAME,repository=REPO,path=PATH,secret=SECRET,rev=REVISION
-g, --gpu-devices-request int32 GPU units to allocate for the job (e.g. 1, 2)
--gpu-memory-limit string GPU memory limit to allocate for the job (e.g. 1G, 500M)
--gpu-memory-request string GPU memory to allocate for the job (e.g. 1G, 500M)
--gpu-portion-limit float GPU portion limit, must be no less than the gpu-memory-request (between 0 and 1, e.g. 0.5, 0.2)
--gpu-portion-request float GPU portion request (between 0 and 1, e.g. 0.5, 0.2)
--gpu-request-type string GPU request type (portion|memory|migProfile[Deprecated])
-h, --help help for submit
--host-ipc Whether to enable host IPC. (Default: false)
--host-network Whether to enable host networking. (Default: false)
--host-path stringArray host paths (Volumes) to mount into the container. Format: path=PATH,mount=MOUNT,mount-propagation=None|HostToContainer,readwrite
-i, --image string The image for the workload
--image-pull-policy string Set image pull policy. One of: Always, IfNotPresent, Never. Defaults to Always (default "Always")
--label stringArray Set of labels to populate into the container running the workspace
--large-shm Request large /dev/shm device to mount
--name-prefix string Set defined prefix for the workload name and add index as a suffix
--new-pvc stringArray Mount a persistent volume, create it if it does not exist. Use the format: claimname=CLAIM_NAME,storageclass=STORAGE_CLASS,size=SIZE,path=PATH,accessmode-rwo,accessmode-rom,accessmode-rwm,ro,ephemeral
--nfs stringArray NFS volumes to use in the workload. Format: path=PATH,server=SERVER,mountpath=MOUNT_PATH,readwrite
--node-pools stringArray List of node pools to use for scheduling the job, ordered by priority
--node-type string Enforce node type affinity by setting a node-type label
--parallelism int32 Specifies the maximum number of pods that should run in parallel at any given time
--pod-running-timeout duration Pod check for running state timeout.
--port stringArray Expose ports from the job container. Use the format: service-type=NodePort,container=80,external=8080
--preferred-pod-topology-key string If possible, all pods of this job will be scheduled onto nodes that have a label with this key and identical values
--priority priority-class Priority class of the workload (build|train|interactive-preemptible). The default value for workspace is 'build' and it can be changed to 'interactive-preemptible' to allow the workload to use over-quota resources. The default value for training is 'train' and it can be changed to 'build' to allow the training workload to have a higher priority for in-queue scheduling and also become non-preemptive (if it's in deserved quota)..
-p, --project string Specify the project to which the command applies. By default, commands apply to the default project. To change the default project use ‘runai config project <project name>’
--required-pod-topology-key string Enforce scheduling pods of this job onto nodes that have a label with this key and identical values
--restart-policy restart-policy defines how containers within a worker pod are restarted when they exit, with options of Always, OnFailure, or Never.
--run-as-gid int The group ID the container will run with
--run-as-uid int The user ID the container will run with
--run-as-user takes the uid, gid, and supplementary groups fields from the token, if all the fields do not exist, uses the local running terminal user credentials. if any of the fields exist take only the existing fields
--runs int32 Number of successful runs required for this workload to be considered completed
--s3 stringArray s3 buckets to use in the workload. Format: name=NAME,bucket=BUCKET,path=PATH,accesskey=ACCESS_KEY,url=URL
--seccomp-profile string Indicates which kind of seccomp profile will be applied to the container, options: RuntimeDefault|Unconfined|Localhost
--secret-volume stringArray Secret volumes to use in the workload. Format: path=PATH,name=SECRET_RESOURCE_NAME
--stdin Keep stdin open on the container(s) in the pod, even if nothing is attached
--supplemental-groups ints Comma seperated list of groups (IDs) that the user running the container belongs to
--termination-grace-period duration The length of time (like 5s or 2m, higher than zero) the workload's pod is expected to terminate gracefully upon probe failure. In case value is not specified, kubernetes default of 30 seconds applies (default 0s)
--toleration stringArray Toleration details. Use the format: operator=Equal|Exists,key=KEY,[value=VALUE],[effect=NoSchedule|NoExecute|PreferNoSchedule],[seconds=SECONDS]
-t, --tty Allocate a TTY for the container
--user-group-source string Indicate the way to determine the user and group ids of the container, options: fromTheImage|fromIdpToken|fromIdpToken
--wait-for-submit duration Waiting duration for the workload to be created in the cluster. Defaults to 1 minute (1m)
--working-dir string Set the container's working directoryOptions inherited from parent commands
--config-file string config file name; can be set by environment variable RUNAI_CLI_CONFIG_FILE (default "config.json")
--config-path string config path; can be set by environment variable RUNAI_CLI_CONFIG_PATH
-d, --debug enable debug mode
-q, --quiet enable quiet mode, suppress all output except error messages
--verbose enable verbose modeSEE ALSO
runai training - training management
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