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Field types

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Metadata

name, description, and tags fields are the metadata of Run. They should be ideally represent the specific characteristics or purposes of your run for better identification.

NameTypeRequiredDescription
namestringRequiredThe name of the run.
descriptionstringOptionalThe description of the run.
tagslistOptionalThe tags of the run.
Specify run metadata
name: stable-diffusion
description: This is the inference example of stable diffusion.
tags:
- "best"
- "A100-80g"
- "20epochs"

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Resources

resources specifies the resource specs to use for run. Use preset provided by VESSL or request the desired resource with requests.

  1. Common fields
NameTypeRequiredDescription
clusterstringOptionalThe cluster to be used for the run. (default: VESSL-managed cluster)
node_nameslistOptionalSpecify candidate nodes for workload assignment. If it’s not set, we’ll find any available node.
  1. Using preset with common fields
NameTypeRequiredDescription
presetstringRequired without requestsThe name of resource spec preset that specified in VESSL. If the preset is not specified, we will offer the best option for you based on reqeusts.
  1. Using requests with common fields (Upcomming feature)
NameTypeRequiredDescription
requestsmapRequired without presetThe desired resource specs.
cpustringOptionalThe number of cpu cores.
memorystringOptionalThe memory size in GB.
nvidia.com/gpumapOptionalThe device_type and quanity of the NVIDIA GPU to be used for the run.
You can list available clusters or resource specs with the CLI command: vessl cluster list or vessl resource list.

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Container Image

The image field is a string that specifies the container image to be used in the run. This is typically a Docker image that includes all the necessary dependencies and environment for your machine learning model.

NameTypeRequiredDescription
imagestring or mapRequriedContainer image url or map of url and credential_name.
urlstringOptionalContainer image url.
credential_namestringOptionalRegistered credential name at VESSL for private image usage.
You can list available VESSL-managed images with the CLI command: vessl image list.
List VESSL-manged images with the VESSL CLI
pip install vessl
vessl image list

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Volumes

There are three type of volumes: import, mount, and export. Each field is a map that specifies a target path as a key and a source information as a value. The value is either a simple string with prefix or another map that holds more detailed information.

  1. Import The import type signifies that the data will be downloaded from the source to a target path in the running container.
PrefixTypeRequiredDescription
git://stringOptionalImport a git repository. The repository will be cloned into the specified target path when container starts.
vessl-dataset://stringOptionalImport a dataset stored in VESSL Dataset.
vessl-model://stringOptionalImport a model stored in VESSL Model Registry.
vessl-artifact://stringOptionalImport an artifact stored in VESSL Artifact.
s3://stringOptionalImport an AWS S3 bucket.
gs://stringOptionalImport a Google Cloud Storage.
  1. Mount The mount type means that the data will be directly mounted to a target path in the run container, providing direct access to the user.
PrefixTypeRequiredDescription
vessl-dataset://stringOptionalMount a dataset stored in VESSL Dataset.
hostpath://stringOptionalMount a file or directory from the host node’s filesystem.
nfs://stringOptionalMount a Network File System(NFS).
readonlybooleanOptionalTrue if readonly mode. (default: True)
  1. Export The export type is desgined for uploading data from a path in the run container to a target path after run execution.
PrefixTypeRequiredDescription
vessl-artifact://stringOptionalExport to VESSL Artifact.
vessl-dataset://stringOptionalExport to VESSL Dataset.
vessl-model://stringOptionalExport to VESSL Model.
s3://stringOptionalExport to Amazon S3 bucket.
gs://stringOptionalExport to Google Cloud Storage.

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Run Command

The run field is a list that contains commands to be run in the container. Each item in the list is a map with the following keys. run could be empty if it’s an interactive run.

NameTypeRequiredDescription
workdirstringOptionalThe working directory for the command.
commandstringRequiredThe command to be run.
waitstringOptionalHow long to wait after a command.

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Interactive

The interactive field is used to specify if the run allows interactive communication with the user. It provides multiple ways to interact with the container during the run, such as JupyterLab, SSH, or a custom service via specified ports.

NameTypeRequiredDescription
interactivemapOptionalMark run as an interactive type that includes max_runtime, jupyter, and idle_timeout
max_runtimestringRequiredThe amount of time to run. Set 0 for infintie use.
jupytermapRequiredJupyter configurations that includes idle_timeout
idle_timeoutstringRequiredThe amount of time a server can be inactive before it will be culled.
Maximum runtime 24h and idle_timeout 120m
interactive:
  max_runtime: 24h
  jupyter:
    idle_timeout: 120m

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Ports

The ports field is a list of map that specifies the port information to expose.

NameTypeRequiredDescription
portslistOptionalList of port numbers or port information that includes name, type, and port to expose.
namestringOptionalThe port name.
typestringOptionalThe protocol of port. (http or tcp)
portintOptionalThe port number.

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Environment Variables

The env field is a map that specifies the environment variables for the run. Each key-value pair in this map represents an environment variable and its value.

NameTypeRequiredDescription
envmapOptionalKey-value pairs for environment variables in the run container.
valuestringOptionalValue of environment variables.
secretbooleanOptionalTrue if the variable is secret.
Set multiple environment variables
env:
  learning_rate: 0.001
  postgres_password:
    value: OUR_DB_PW
    secret: true
Serve YAML