TRFL is a reinforcement learning library built on top of TensorFlow, developed by Google DeepMind. It exposes reusable algorithmic building blocks for implementing RL agents, including loss functions such as Q-learning that compute TD errors and targets. The library returns both loss tensors and auxiliary information that can be differentiated to derive RL updates, allowing integration into standard TensorFlow training pipelines.