settings:
  name: tf-mnist-hyperparameter-optimization-experiment
  description: Simple MNIST model implemented in TF using Hyperparameter Optimization
training_references: 
- name: model1
  training_definition_url: https://ibm-watson-ml.mybluemix.net/v3/ml_assets/training_definitions/<REPLACE WITH UUID>
  command: python3 convolutional_network.py --trainImagesFile ${DATA_DIR}/train-images-idx3-ubyte.gz
    --trainLabelsFile ${DATA_DIR}/train-labels-idx1-ubyte.gz --testImagesFile ${DATA_DIR}/t10k-images-idx3-ubyte.gz
    --testLabelsFile ${DATA_DIR}/t10k-labels-idx1-ubyte.gz --trainingIters 200000
  compute_configuration:
      name: k80
  hyper_parameters_optimization:
    method:
      name: random
      parameters:
      - name: objective
        string_value: accuracy
      - name: maximize_or_minimize
        string_value: maximize
      - name: num_optimizer_steps
        int_value: 4
    hyper_parameters:
    - name: learning_rate
      double_range:
        min_value: 0.005
        max_value: 0.01
        step: 0.001
    - name: conv_filter_size1
      int_range:
        min_value: 5
        max_value: 6
    - name: conv_filter_size2
      int_range:
        min_value: 5
        max_value: 6
    - name: fc
      int_range: 
        min_value: 9
        max_value: 10
        power: 2
training_results_reference:
  name: training-results-reference_name
  connection: 
    endpoint_url: <INSERT endpoint_url found in your cloud storage endpoint>
    access_key_id: <INSERT access_key_id found in your cloud storage credentials>
    secret_access_key: <INSERT secret_access_key found in your cloud storage credentials>
  target:
    bucket: <INSERT name of training_results bucket found in your cloud storage>
  type: s3