I am trying to construct a ML pipeline DAG using Argo. And I am running into an issue where I need a value from one node in the DAG to be sent as a parameter to its subsequent node. Say the ARGO DAG structure looks like the following:
{
"apiVersion": "argoproj.io/v1alpha1",
"kind": "Workflow",
"metadata": {
"generateName": "workflow01-"
},
"spec": {
"entrypoint": "workflow01",
"arguments": {
"parameters": [
{
"name": "log-level",
"value": "INFO"
}
]
},
"templates": [
{
"name": "workflow01",
"dag": {
"tasks": [
{
"name": "A",
"template": "task-container",
"arguments": {
"parameters": [
{
"name": "model-type",
"value": "INTENT-TRAIN"
}
]
}
},
{
"name": "B",
"template": "task-container",
"dependencies": ["A"],
"arguments": {
"parameters": [
{
"name": "model-type",
"value": "INTENT-EVALUATE"
}
]
}
}
]
}
},
{
"name": "task-container",
"inputs": {
"parameters": [
{
"name": "model-type",
"value": "NIL"
}
]
},
"container": {
"env": [
{
"name": "LOG_LEVEL",
"value": "{{workflow.parameters.log-level}}"
},
{
"name": "MODEL_TYPE",
"value": "{{inputs.parameters.model-type}}"
}
]
}
}
]
}
}
A -> B
The computation happening in B depends on the value that has been computed in A.
How will I be able to pass the value computed in A into B?
You can use Argo's "artifacts" for this - see the examples at https://github.com/argoproj/argo-workflows/tree/master/examples#artifacts
Another way is to set up a shared volume: https://github.com/argoproj/argo-workflows/tree/master/examples#volumes