PADL: portable PyTorch pipelines facilitating deep-learning model use

Programs are read more often than they are written. Models are used more often than they are trained. The PyTorch, and the deep-learning ecosystem in general, abounds with tools for training models, and squeezing the best performance out of computational resources in doing this. In the life cycle of a model this is only the beginning of the journey. Once a model has been trained, it will be shared, and used in a multitude of contexts, often on a daily basis, in operations, evaluation, comparision and experimentation by data scientists.