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: training_data_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>
  source:
    bucket: <INSERT name of training_data bucket found in your cloud storage>
    type: s3