IBM/pytorchpipe

# Load config defining tasks for training, validation and testing.
default_configs: vqa_med_2019/default_vqa_med_2019.yml

training:
  task:
    categories: all
    export_sample_weights: ~/data/vqa-med/answers.all.weights.csv
    # Do not load and stream images!
    stream_images: False
    batch_size:  256
  sampler:
    weights: ~/data/vqa-med/answers.all.weights.csv
  terminal_conditions:
    loss_stop_threshold: 1.0e-3

validation:
  task:
    categories: all
    # Do not load and stream images!
    stream_images: False
    batch_size:  256


pipeline:

  # Predictions decoder.
  prediction_decoder:
    type: WordDecoder
    priority: 10.1
    # Use the same word mappings as label indexer.
    import_word_mappings_from_globals: True
    streams:
      inputs: predictions
      outputs: predicted_category_names
    globals:
      vocabulary_size: num_categories
      word_mappings: category_word_mappings

  # Loss
  nllloss:
    type: NLLLoss
    priority: 10.2
    targets_dim: 1
    streams:
      targets: category_ids
      loss: loss

  # Statistics.
  batch_size:
    type: BatchSizeStatistics
    priority: 100.1

  #accuracy:
  #  type: AccuracyStatistics
  #  priority: 100.2
  #  streams:
  #    targets: category_ids

  precision_recall:
    type: PrecisionRecallStatistics
    priority: 100.3
    use_word_mappings: True
    show_class_scores: True
    streams:
      targets: category_ids
    globals:
      num_classes: num_categories
      word_mappings: category_word_mappings
      

  # Viewers.
  viewer:
    type: StreamViewer
    priority: 100.4
    input_streams: questions,category_names,predicted_category_names

#: pipeline