pipeline.nodes is an array of objects, each object having the following properties:
name: name of the node, used in edge definitions
type: type of the node, accepts “execution”, “task”, or “deployment”
step: name of the step to be executed, defined in the same file
override: (optional) override values defined in the original step
Other than that, pipeline execution nodes behave like you would expect:
- it will use the defaults from the original step
- you can customize the parameters and inputs before starting the pipeline
- you can override values when defining the pipeline using the
Note that separate nodes in a pipeline can implement the same step multiple times.
# define "gather-dataset" and "train-model" steps above... - pipeline: name: gatherer-pipeline nodes: - name: gather-node type: execution step: gather-dataset - name: train-node type: execution step: train-model override: image: tensorflow/tensorflow:1.13.1-py3 - name: deploy-node type: deployment deployment: predict-digit endpoints: - predict-digit edges: - [gather-node.output.images*, train-node.input.dataset-images] - [gather-node.output.labels*, train-node.input.dataset-labels] - [train-node.output.model*, deploy-node.file.predict-digit.model]
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