pipeline.yml

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

display_name: rai_pipeline_adult_analyse
experiment_name: rai_pipeline_adult_analyse
description: Sample rai pipeline
type: pipeline

inputs:
  target_column_name: income
  my_test_data:
    type: uri_file
    path: azureml:adult_test_pq:1
    mode: download

settings:
  default_datastore: azureml:workspaceblobstore
  default_compute: azureml:cpu-cluster
  continue_on_step_failure: false

jobs:
  train_model_job:
    type: command
    component: ./components/component_train_logreg.yaml
    inputs:
      training_data: 
        type: uri_file
        path: azureml:adult_train_pq:1
        mode: download      
      target_column_name: ${{parent.inputs.target_column_name}}


  register_model_job:
    type: command
    component: ./components/component_register_model.yaml
    inputs:
      model_input_path: ${{parent.jobs.train_model_job.outputs.model_output}}
      model_base_name: component_registered_lr_01

  create_rai_job:
    type: command
    component: ./components/component_rai_insights.yaml
    inputs:
      title: With just the OSS
      task_type: classification
      model_info_path: ${{parent.jobs.register_model_job.outputs.model_info_output_path}}
      train_dataset: 
        type: uri_file
        path: azureml:adult_train_pq:1
        mode: download      
      test_dataset: ${{parent.inputs.my_test_data}}
      target_column_name: ${{parent.inputs.target_column_name}}
      categorical_column_names: '["Race", "Sex", "Workclass", "Marital Status", "Country", "Occupation"]'

  explain_01:
    type: command
    component: ./components/component_explain.yaml  #azureml:rai_insights_explanation:1
    inputs:
      comment: Some random string
      rai_insights_dashboard: ${{parent.jobs.create_rai_job.outputs.rai_insights_dashboard}}

  causal_01:
    type: command
    component: ./components/component_causal.yaml
    inputs:
      rai_insights_dashboard: ${{parent.jobs.create_rai_job.outputs.rai_insights_dashboard}}
      treatment_features: '["Age", "Sex"]'
      heterogeneity_features: '["Marital Status"]'

  counterfactual_01:
    type: command
    component: ./components/component_counterfactual.yaml # azureml:rai_insights_counterfactual:1
    inputs:
      rai_insights_dashboard: ${{parent.jobs.create_rai_job.outputs.rai_insights_dashboard}}
      total_CFs: 10
      desired_class: opposite

  error_analysis_01:
    type: command
    component: ./components/component_error_analysis.yaml  # azureml:rai_insights_erroranalysis:1
    inputs:
      rai_insights_dashboard: ${{parent.jobs.create_rai_job.outputs.rai_insights_dashboard}}
      filter_features: '["Race", "Sex", "Workclass", "Marital Status", "Country", "Occupation"]'

  gather_01:
    type: command
    component: ./components/component_gather_rai_insights.yaml # azureml:rai_insights_gather:1
    inputs:
      constructor: ${{parent.jobs.create_rai_job.outputs.rai_insights_dashboard}}
      insight_1: ${{parent.jobs.causal_01.outputs.causal}}
      insight_2: ${{parent.jobs.counterfactual_01.outputs.counterfactual}}
      insight_3: ${{parent.jobs.error_analysis_01.outputs.error_analysis}}
      insight_4: ${{parent.jobs.explain_01.outputs.explanation}}