name: tf-mnist-hyperparameter-optimization
description: Simple MNIST model implemented in TF using Hyperparameter Optimization
framework:
  name: tensorflow
  version: '1.5'
  runtimes:
    name: python
    version: '3.5'
execution:
  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
training_data_reference:
- name: MNIST Training Data
  connection:
    endpoint_url: s3.private.us-south.cloud-object-storage.appdomain.cloud
    access_key_id: "3b6e39780fd34466b02417a920e2bf25"
    secret_access_key: "4028a1ae4459e851a13a428f65bd7f05a5cd3f84f308713f"
  source:
    bucket: tutorial-train-data
    type: s3
training_results_reference:
  name: Training Results
  connection:
    endpoint_url: s3.private.us-south.cloud-object-storage.appdomain.cloud
    access_key_id: "3b6e39780fd34466b02417a920e2bf25"
    secret_access_key: "4028a1ae4459e851a13a428f65bd7f05a5cd3f84f308713f"
  target:
    bucket: tutorial-train-results
  type: s3