metadata
title: YAML
description: VESSL Run is configured through a single YAML file.
version: EN
Field types
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.
| Name |
Type |
Required |
Description |
name |
string |
Required |
The name of the run. |
description |
string |
Optional |
The description of the run. |
tags |
list |
Optional |
The tags of the run. |
name: stable-diffusion
description: This is the inference example of stable diffusion.
tags:
- "best"
- "A100-80g"
- "20epochs"
Resources
resources specifies the resource specs to use for run. Use preset provided by VESSL or request the desired resource with requests.
- Common fields
| Name |
Type |
Required |
Description |
cluster |
string |
Optional |
The cluster to be used for the run. (default: VESSL-managed cluster) |
node_names |
list |
Optional |
Specify candidate nodes for workload assignment. If it's not set, we'll find any available node. |
- Using
preset with common fields
| Name |
Type |
Required |
Description |
preset |
string |
Required without requests |
The 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. |
```yaml Run resource specs with preset
resources:
cluster: vessl-gcp-oregon
preset: v1.l4-1.mem-42
```
resources:
cluster: my-on-premise-cluster
preset: v100-1
node_names:
- "n01"
- "n03"
- "n04"
- Using
requests with common fields (Upcomming feature)
| Name |
Type |
Required |
Description |
requests |
map |
Required without preset |
The desired resource specs. |
cpu |
string |
Optional |
The number of cpu cores. |
memory |
string |
Optional |
The memory size in GB. |
nvidia.com/gpu |
map |
Optional |
The device_type and quanity of the NVIDIA GPU to be used for the run. |
```yaml Run resource specs with requests
resources:
cluster: vessl-gcp-oregon
requests:
cpu: "4"
memory: 12Gi
nvidia.com/gpu:
device_type: V100
quantity: "2"
```
resources:
cluster: my-on-premise-cluster
requests:
cpu: "4"
memory: 12Gi
nvidia.com/gpu:
device_type: V100
quantity: "2"
node_names:
- "n01"
- "n03"
- "n04"
You can list available clusters or resource specs with the CLI command: vessl cluster list or vessl resource list.
```bash List VESSL clusters
pip install vessl
vessl cluster list
```
pip install vessl
vessl resource list
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.
| Name |
Type |
Required |
Description |
image |
string or map |
Requried |
Container image url or map of url and credential_name. |
url |
string |
Optional |
Container image url. |
credential_name |
string |
Optional |
Registered credential name at VESSL for private image usage. |
```yaml Use a VESSL-managed image
image: quay.io/vessl-ai/ngc-pytorch-kernel:22.10-py3-202306140422
```
image: my-docker-account/public-repo-name:tag-name
image:
url: my-docker-account/private-repo-name:tag-name
credential_name: docker_hub_cred
You can list available VESSL-managed images with the CLI command: vessl image list.
pip install vessl
vessl image list
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.
- Import
The
import type signifies that the data will be downloaded from the source to a target path in the running container.
| Prefix |
Type |
Required |
Description |
git:// |
string |
Optional |
Import a git repository. The repository will be cloned into the specified target path when container starts. |
vessl-dataset:// |
string |
Optional |
Import a dataset stored in VESSL Dataset. |
vessl-model:// |
string |
Optional |
Import a model stored in VESSL Model Registry. |
vessl-artifact:// |
string |
Optional |
Import an artifact stored in VESSL Artifact. |
s3:// |
string |
Optional |
Import an AWS S3 bucket. |
gs:// |
string |
Optional |
Import a Google Cloud Storage. |
```yaml String import value with prefix
import:
/import/code: git://github.com/{accountName}/{repoName}
/import/dataset: vessl-dataset://{organizationName}/{datasetName}
/import/model: vessl-model://{organizationName}/{modelRepositoryName}/{modelNumber}
/import/artifact: vessl-artifact://{organiztionName}/{projectName}/{artifactName}
/import/s3: s3://{bucketName}/{path}
/import/gs: gs://{buckeName}/{path}
```
import:
/import/code:
git:
url: https://github.com/{accountName}/{repoName}
ref: c0ffee
credential_name: my-git-cred-name
/import/dataset:
dataset:
organization_name: {organizationName}
dataset_name: {datasetName}
/import/model:
model:
organization_name: {organizationName}
model_repository_name: {modelRepositoryName}
model_number: {modelNumber}
/import/artifact:
artifact:
organization_name: {organizationName}
project_name: {projectName}
name: {artifactName}
/import/artifact-same-project:
artifact:
name: {artifactName}
/import/s3:
s3:
bucket: {bucketName}
prefix: {prefix}
credential_name: my-s3-cred-name
/import/gs:
gs:
bucket: {bucketName}
prefix: {prefix}
credential_name: my-gs-cred-name
- 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.
| Prefix |
Type |
Required |
Description |
vessl-dataset:// |
string |
Optional |
Mount a dataset stored in VESSL Dataset. |
hostpath:// |
string |
Optional |
Mount a file or directory from the host node's filesystem. |
nfs:// |
string |
Optional |
Mount a Network File System(NFS). |
readonly |
boolean |
Optional |
True if readonly mode. (default: True) |
```yaml String mount value with prefix
mount:
/mount/dataset: vessl-dataset://{organizationName}/{datasetName}
/mount/hostpath: hostpath://{path}
/mount/nfs: nfs://{server}/{path}
```
mount:
/mount/dataset:
dataset:
organization_name: {organizationName}
dataset_name: {datasetName}
/mount/hostpath:
hostpath:
path: {path}
readonly: true
/mount/nfs:
nfs:
server: {server}
path: {path}
readonly: false
- Export
The
export type is desgined for uploading data from a path in the run container to a target path after run execution.
| Prefix |
Type |
Required |
Description |
vessl-artifact:// |
string |
Optional |
Export to VESSL Artifact. |
vessl-dataset:// |
string |
Optional |
Export to VESSL Dataset. |
vessl-model:// |
string |
Optional |
Export to VESSL Model. |
s3:// |
string |
Optional |
Export to Amazon S3 bucket. |
gs:// |
string |
Optional |
Export to Google Cloud Storage. |
```yaml String export value with prefix
export:
/export/output-artifact: vessl-artifact://
/export/backup-artifact: vessl-artifact://{organizationName}/{projectName}/{artifactName}
/export/dataset: vessl-dataset://{organizationName}/{datasetName}
/export/model: vessl-model://{organizationName}/{modelRepositoryName}
/export/s3: s3://{buckeName}/{prefix}
/export/gs: gs://{bucketName}/{prefix}
```
export:
/export/output-artifact:
artifact:
/export/backup-artifact:
artifact:
organization_name: {organizationName}
project_name: {projectName}
artifact_name: {artifactName}
/export/dataset:
dataset:
organization_name: {organizationName}
dataset_name: {datasetName}
/export/model:
model:
organization_name: {organizationName}
model_repository_name: {modelRepositoryName}
/export/s3:
s3:
bucket: {bucketName}
prefix: {prefix}
endpoint: in-house.endpoint.co.kr
credential_name: my-s3-cred-name
/export/gs:
gs:
bucket: {bucketName}
prefix: {prefix}
credential_name: my-gs-cred-name
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.
| Name |
Type |
Required |
Description |
workdir |
string |
Optional |
The working directory for the command. |
command |
string |
Required |
The command to be run. |
wait |
string |
Optional |
How long to wait after a command. |
```yaml Run a single command
run:
- command: |
python train.py --learning_rate=$learning_rate --batch_size=$batch_size
```
run:
- workdir: /input/data1
command: |
python data_preprocessing.py
- wait: 10s
- workdir: /root/git-examples
command: |
python train.py --learning_rate=$learning_rate --batch_size=$batch_size
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.
| Name |
Type |
Required |
Description |
interactive |
map |
Optional |
Mark run as an interactive type that includes max_runtime, jupyter, and idle_timeout |
max_runtime |
string |
Required |
The amount of time to run. Set 0 for infintie use. |
jupyter |
map |
Required |
Jupyter configurations that includes idle_timeout |
idle_timeout |
string |
Required |
The amount of time a server can be inactive before it will be culled. |
interactive:
max_runtime: 24h
jupyter:
idle_timeout: 120m
Ports
The ports field is a list of map that specifies the port information to expose.
| Name |
Type |
Required |
Description |
ports |
list |
Optional |
List of port numbers or port information that includes name, type, and port to expose. |
name |
string |
Optional |
The port name. |
type |
string |
Optional |
The protocol of port. (http or tcp) |
port |
int |
Optional |
The port number. |
```yaml Expose port by number
ports:
- 3000
```
ports:
- name: streamlit
type: http
port: 8501
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.
| Name |
Type |
Required |
Description |
env |
map |
Optional |
Key-value pairs for environment variables in the run container. |
value |
string |
Optional |
Value of environment variables. |
secret |
boolean |
Optional |
True if the variable is secret. |
env:
learning_rate: 0.001
postgres_password:
value: OUR_DB_PW
secret: true
