Agon Shabi04/28/2021, 3:32 PM
@pipeline def my_pipeline(): features = ... untrained_models = generate_models() trained_models = untrained_models.map( train_model # I want to also pass in "features" here ) best_model = pick_best(trained_models.collect()) ...
solid yields a variable number of untrained model instances, driven by config. Is there another obvious way to do this that I'm missing, besides feeding the
alex04/28/2021, 3:38 PM
should do the trick
trained_models = untrained_models.map( lambda model: train_model(model=model, features=features) )
Agon Shabi04/28/2021, 4:25 PM