variables-template.yml

# Variables in this file determine _how_ the project runs.
# When this file is placed before a variable group in Azure DevOps pipeline yml,
# the values defined in the variable group overwrite the value defined here.
variables:
  # The directory containing the scripts for training, evaluating, and registering the model
  - name: SOURCES_DIR_TRAIN
    value: ml_model
    
  # Azure ML Variables
  - name: EXPERIMENT_NAME
    value: flower_classification
  - name: DATASET_NAME
    value: flower_dataset
  # Uncomment DATASTORE_NAME if you have configured non default datastore to point to your data
  # - name: DATASTORE_NAME
  #   value: datablobstore
  # which data folder do we want to train on
  - name: RAW_DATAFILE_PATH
    value: flower_dataset
  - name: PREPROCESSING_PIPELINE_NAME
    value: "flower-preprocessing-pipeline"
  - name: TRAINING_PIPELINE_NAME
    value: "flower-training-Pipeline"
  - name: MODEL_NAME
    value: flower_classifier
  # Flag to allow rebuilding the AML Environment after it was built for the first time. This enables dependency updates from conda_dependencies.yaml.
  # - name: AML_REBUILD_ENVIRONMENT
  #  value: "false"

  # AML Environment Config
  - name: AML_ENV_NAME
    value: flower_classifier_training_env

  # AML Compute Cluster Config
  - name: AML_COMPUTE_CLUSTER_CPU_SKU
    value: STANDARD_DS2_V2
  - name: AML_COMPUTE_CLUSTER_NAME
    value: train-cluster
  - name: AML_CLUSTER_PRIORITY
    value: lowpriority
  - name: AML_CLUSTER_MIN_NODES
    value: 0
  - name: AML_CLUSTER_MAX_NODES
    value: 4

  # Data used for smoke testing deployed service, comma separated
  # - name: TEST_IMAGE_URLS
  #   value: url_to_sunflower_jpg,url_to_daisy_jpg
  # - name: TEST_IMAGE_CLASSES
  #   value: sunflowers,daisy