pipeline.yml

$schema: https://azuremlschemas.azureedge.net/latest/pipelineJob.schema.json
type: pipeline

description: "Dummy train-score-eval pipeline with local components"

inputs:
  pipeline_job_training_input: 
    dataset: 
      local_path: ./data
#  pipeline_job_test_input: 
#    dataset: 
#      local_path: ./data
  pipeline_job_training_max_epocs: 20
  pipeline_job_training_learning_rate: 1.8
  pipeline_job_learning_rate_schedule: 'time-based'

outputs: 
  pipeline_job_trained_model:
    mode: upload
#  pipeline_job_scored_data:
#    mode: upload
  pipeline_job_evaluation_report:
    mode: upload

#settings: 
#  datastore: azureml:workspaceblobstore

compute: azureml:cpu-cluster

jobs:
  train-job:
    type: component
    compute: azureml:cpu-cluster
    component: file:./train.yml
    inputs:
      training_data: ${{inputs.pipeline_job_training_input}}
      max_epocs: ${{inputs.pipeline_job_training_max_epocs}}
      learning_rate: ${{inputs.pipeline_job_training_learning_rate}}
      learning_rate_schedule: ${{inputs.pipeline_job_learning_rate_schedule}}
    outputs:
      model_output: ${{outputs.pipeline_job_trained_model}}
  
  score-job:
    type: component
    component: file:./score.yml
    compute: azureml:cpu-cluster
    inputs:
      model_input: ${{jobs.train-job.outputs.model_output}}
      test_data: 
        dataset:
          local_path: ./data
    outputs:
      score_output: 
        mode: upload

  evaluate-job:
    type: component
    component: file:./eval.yml
    compute: azureml:cpu-cluster
    inputs:
      scoring_result: ${{jobs.score-job.outputs.score_output}}
    outputs:
      eval_output: ${{outputs.pipeline_job_evaluation_report}}