Introducing Retiarii: A deep learning exploratory-training framework on NNI

Traditional deep learning frameworks such as TensorFlow and PyTorch support training on a single deep neural network (DNN) model, which involves computing the weights iteratively for the DNN model. Designing a DNN model for a task remains an experimental science and is typically a practice of deep learning model exploration. Retrofitting such exploratory-training into the training process of a single DNN model, as supported by current deep learning frameworks, is unintuitive, cumbersome, and inefficient. In this webinar, Microsoft Research Asia Senior Researcher Quanlu Zhang and Principal Program Manager Scarlett Li will analyze these challenges within the context of Neural Architecture Search (NAS). The first part of the webinar will focus on Retiarii, a deep learning exploratory-training framework for DNN models. Retiarii also offers a just-in-time (JIT) engine that instantiates models and manages their training, gathers information for the exploration strategy to consume, and executes the decisions accor