runtime:
  distribution_strategy: 'mirrored'
  mixed_precision_dtype: 'float16'
  loss_scale: 'dynamic'
  num_gpus: 2
task:
  model:
    num_classes: 1001
    input_size: [256, 256, 3]
    backbone:
      type: 'darknet'
      darknet:
        model_id: 'darknet53'
    norm_activation:
      activation: 'mish'
  losses:
    l2_weight_decay: 0.0005
    one_hot: true
  train_data:
    tfds_name: 'imagenet2012'
    tfds_split: 'train'
    tfds_data_dir: '~/tensorflow_datasets/'
    tfds_download: true
    is_training: true
    global_batch_size: 16  # default = 128
    dtype: 'float16'
    shuffle_buffer_size: 100
  validation_data:
    tfds_name: 'imagenet2012'
    tfds_split: 'validation'
    tfds_data_dir: '~/tensorflow_datasets/'
    tfds_download: true
    is_training: true
    global_batch_size: 16  # default = 128
    dtype: 'float16'
    drop_remainder: false
    shuffle_buffer_size: 100
trainer:
  train_steps: 6400000  # epochs: 80, 800000 * 128/batchsize
  validation_steps: 3200  # size of validation data, 400 * 128/batchsize
  validation_interval: 10000  # 10000
  steps_per_loop: 10000
  summary_interval: 10000
  checkpoint_interval: 10000
  optimizer_config:
    optimizer:
      type: 'sgd'
      sgd:
        momentum: 0.9
    learning_rate:
      type: 'polynomial'
      polynomial:
        initial_learning_rate: 0.0125  # 0.1 * batchsize/128, default = 0.1
        end_learning_rate: 0.0000125  # 0.0001 * batchsize/128, default = 0.0001
        power: 4.0
        decay_steps: 6392000  # 790000 * 128/batchsize,   default =  800000 - 1000 = 799000
    warmup:
      type: 'linear'
      linear:
        warmup_steps: 8000  # 0 to 0.1 over 1000 * 128/batchsize, default = 128
