Tensorlayer 3.0: A Deep Learning Library Compatible With Multiple Backends

TensorLayer 3.0 is a deep learning library refactored based on TensorLayer 2.0. It is compatible with multiple deep learning frameworks, designed for researchers and engineers. The library provides an extensive collection of customised neural layers enabling users to build advanced AI models quickly. TensorLayer 3.0 designed backend layers to unify the low-level APIs operators of multiple frameworks, and model abstraction layers to be compatible with model building using different frameworks. Therefore, the library has the combined advantage of low coupling, easy to extend and great compatibility with other frameworks. The TensorLayer community has accumulated a large number of users, and there are many open-source examples to help users get started quickly.