task:
  model:
    num_classes: 1001
    input_size: [128, 128, 3]
  train_data:
    input_path: 'gs://mlcompass-data/imagenet/imagenet-2012-tfrecord/train*'
    is_training: true
    global_batch_size: 64
    dtype: 'bfloat16'
  validation_data:
    input_path: 'gs://mlcompass-data/imagenet/imagenet-2012-tfrecord/valid*'
    is_training: false
    global_batch_size: 64
    dtype: 'bfloat16'
    drop_remainder: false
trainer:
  train_steps: 62400
  validation_steps: 13
  validation_interval: 312
  steps_per_loop: 312
  summary_interval: 312
  checkpoint_interval: 312
  optimizer_config:
    optimizer:
      type: 'sgd'
      sgd:
        momentum: 0.9
    learning_rate:
      type: 'stepwise'
      stepwise:
        boundaries: [18750, 37500, 50000]
        values: [0.1, 0.01, 0.001, 0.0001]
