def predict_fn()

in src/inference.py [0:0]

• 11 lines of code
• 2 McCabe index (conditional complexity)

def predict_fn(input_data, model):
    """
    SageMaker XGBoost model server invokes `predict_fn` on the return value of `input_fn`.
    Return a two-dimensional NumPy array where the first columns are predictions
    and the remaining columns are the feature contributions (SHAP values) for that prediction.
    """
    is_feature_importance = False
    prediction = model.predict(input_data)
    if is_feature_importance:
        feature_contribs = model.predict(input_data, 
                                         pred_contribs=True, 
                                         validate_features=False)
        output = np.hstack((prediction[:, np.newaxis], feature_contribs))
    else:
        output = prediction
    return output