  We present Self Meta Pseudo Labels, a novel semi-supervised learning method
similar to Meta Pseudo Labels but without the teacher model. We introduce a
novel way to use a single model for both generating pseudo labels and
classification, allowing us to store only one model in memory instead of two.
Our method attains similar performance to the Meta Pseudo Labels method while
drastically reducing memory usage.
