test_config_lazy.yml

# Download test data from: https://osf.io/8jz7e/
model_path: PATH_TO_BEST_CHECKPOINT
model:
  name: UNet3D
  # number of input channels to the model
  in_channels: 1
  # number of output channels
  out_channels: 1
  # determines the order of operators in a single layer (crg - Conv3d+ReLU+GroupNorm)
  layer_order: gcr
  # initial number of feature maps
  f_maps: 32
  # number of groups in the groupnorm
  num_groups: 8
  # apply element-wise nn.Sigmoid after the final 1x1x1 convolution, otherwise apply nn.Softmax
  final_sigmoid: true
predictor:
  # use LazyPredictor for large datasets
  name: 'LazyPredictor'
loaders:
  # use LazyHDF5Dataset for large datasets
  dataset: LazyHDF5Dataset
  # save predictions to output_dir
  output_dir: PATH_TO_OUTPUT_DIR
  # batch dimension; if number of GPUs is N > 1, then a batch_size of N * batch_size will automatically be taken for DataParallel
  batch_size: 1
  # how many subprocesses to use for data loading
  num_workers: 8
  # test loaders configuration
  test:
    file_paths:
      - PATH_TO_TEST_DIR

    slice_builder:
      name: SliceBuilder
      patch_shape: [ 80, 170, 170 ]
      stride_shape: [ 80, 170, 170 ]
      # halo around each patch
      halo_shape: [ 16, 32, 32 ]


    transformer:
      raw:
        - name: Standardize
        - name: ToTensor
          expand_dims: true