Welcome to gobbli’s documentation

gobbli is a library designed to make experimentation and analysis using deep learning easier. It provides a simple, uniform interface to deep learning models that abstracts away most of the complexity in terms of different input/output formats, library versions, etc. It attempts to implement a set of common use cases with an emphasis on usability rather than performance.

gobbli is not designed to provide deep learning models in a production context. Each task generally involves running a Docker container in the background and transferring a large amount of data to and from disk, which creates significant overhead. Additionally, gobbli does not support fine-grained model-specific tuning, such as custom loss functions. Our goal is to take the user 80% of the way to their deep learning solution as quickly as possible so they can decide whether it’s worth the effort to resolve the remaining 20%.