Variables

You can use expressions to programmatically access contexts or set variables in pipeline files and action-datatorch.yaml files. An expression can be any combination of literal values, references to a context, or functions. You can combine literals, context references, and functions using operators.

Context

Contexts are a way to access information about workflow runs, runner environments, jobs, and steps. Contexts use the following syntax.

${{ <context> }}

Variable	Type	Description
agent	object	Information about the agent.
agent.id	object	ID of the agent.
machine	object	Information about the machine the agent is running on.
machine.name	string	The computer’s network name. An empty string is returned if the value cannot be determined.
machine.os	string	The system/OS name, e.g. Linux, Windows, or Java. An empty string is returned if the value cannot be determined.
machine.version	string	The system’s release version, e.g. #3 on degas. An empty string is returned if the value cannot be determined.
python	string	Information about the python instance the agent is running on.
python.version	string	Python version of the current agent.
python.implementation	string	Python implementation of the current agent.
pipeline	object	Information about the pipeline
pipeline.id	string	Id of the current pipeline
pipeline.name	string	Name of the current pipeline
pipeline.creatorId	string	Id of the user who created this pipeline
pipeline.projectId	string	Id of the project this pipeline belongs to
pipeline.lastRunNumber	int	Last number used for running
run	object	Information about the run
run.id	string	ID of the pipeline run.
run.name	string	Name of the pipeline run.
run.config	object	Parse JSON version of the runs YAML.
run.runNumber	int	Number of the pipeline run.
step	object	Information about the current running step.
step.id	string	ID of the step.
step.name	string	name of the step.
action	object	Information about the current (or previous if no action is active) action being executed.
action.name	string	Name of the action.
action.version	string	Version of the action.
action.directory	string	Directory where the actions files are.
variable	object	Contains inputs and outputs from previous steps
variable.<key>	any	Input and output from previous steps. All inputs and outputs are added to this variable object.

Examples

A Datatorch pipeline file using context for a custom annotator tool:

# DataTorch Pipeline file
# This is NOT an action-datatorch.yaml file

name: DEXTR

triggers:
  # Adds a button to the annotator.
  annotatorButton:
    name: "DEXTR"
    icon: brain
    # Annotator will prompt the user for 4 points before triggering the pipeline
    flow: 4-points

jobs:
  predict:
    # Properties about the trigger event can be accessed at 'event' property
    steps:
      - name: Download File
        action: datatorch/download-file@v1
        inputs:
          # Get the file id for the event that triggered this.
          fileId: ${{ event.fileId }}

      - name: Predict Segmentation
        action: datatorch/dextr@latest
        inputs:
          # Download file path from the previous action.
          imagePath: ${{ variable.path }}
          # Get the 4 points the user clicked
          points: ${{ event.flowData.points }}
          # Annotation created by the four points. We will insert the
          # segmentation into this annotation
          annotationId: ${{ event.annotationId }}

An action-datatorch.yaml file in an action repository for inporting COCO annotations:

# action-datatorch.yaml

name: Import COCO
description: Imports annotation in COCO format into a DataTorch Project. Files are are matched by name.
inputs:
  path:
    type: string
    required: true
    description: Absolute path to the coco file
  bbox:
    type: boolean
    default: false
    description: Create a bbox annotation.
  segmentation:
    type: boolean
    default: true
    description: Create segmentation annotations.
  project:
    type: string
    default: ${{ pipeline.projectId }}
    description: >
      Id or namespace and slug of the project to import the annotations into. This
      will default to the flows project if not set.
  maxIou:
    type: float
    default: 0.99
    description: >
      If an annotation exists on the file with an union over intersection of the
      annotation about to be imported, the annotation will not be imported. Set
      to 0 to disable. Disabling can significantly increase performance.
  simplify:
    type: float
    default: 0.5
    description: >
      Simplification tolerance applied to coco segmentations before importing.
      Set to 0 to disable. Disabling can significantly increase performance.
  ignoreAnnotationsWithIds:
    type: boolean
    default: true
    description: Annotations with the property 'datatorch_id' will be ignored.
runs:
  using: python
  main: import_coco.py