data:
    batch_size: 32
    dataset_params:
        iq_key: iq_data
        label_key: labels
    drop_last: false
    kind: iq_h5
    num_workers: 0
    persistent_workers: false
    pin_memory: false
    test_path: /opt/qmb/riahub/dataset/qoherent/icc-28/main/datasets/icc28-test_v1.0.0.h5
    test_split: 0
    train_path: /opt/qmb/riahub/dataset/qoherent/icc-28/main/datasets/icc28-train_v1.0.0.h5
    validation_path: /opt/qmb/riahub/dataset/qoherent/icc-28/main/datasets/icc28-test_v1.0.0.h5
    validation_split: 0
evaluation:
    capture_predictions: true
    enabled: true
    params:
        save_confusion: true
    split: test
export:
    dynamic_batch: true
    dynamic_width: false
    enabled: true
    file_name: model.onnx
    opset_version: 17
    strict: false
    use_dynamo: true
    use_onnxsim: false
model:
    name: iq_vtcnn2
    params:
        dropout_p: 0.6
optimization:
    loss:
        name: cross_entropy
        params: {}
    optimizer:
        name: adam
        params:
            amsgrad: false
            eps: 1e-08
            lr: 0.001
            weight_decay: 0
runtime:
    amp_enabled: false
    autocast_dtype: float32
    checkpoint_every_n_epochs: 1
    component_modules: []
    device: auto
    epochs: 1
    progress_bar: false
    seed: 42
task:
    name: classification
    params:
        save_artifacts: true
        selection_metric: accuracy
        selection_mode: max