What is the difference between torch and PyTorch?

Torch and PyTorch are two distinct deep learning frameworks.

Torch is an open-source scientific computing framework originally designed for the Lua language, but later expanded to include interfaces for other languages. It offers a wide range of numerical computing tools and deep learning modules, supporting efficient matrix operations and automatic differentiation. The main features of Torch are its speed, flexibility, ease of use, and active community.

PyTorch is a Python deep learning framework that is based on Torch. It inherits the advantages of Torch and makes it more user-friendly by providing an interface in Python. PyTorch supports dynamic computational graphs, allowing for the use of conditional statements, loops, and other control flow operations when defining models, instead of just static computational graphs. This flexibility makes PyTorch more adaptable when handling complex models and dynamic data.

In summary, Torch is a scientific computing framework primarily using Lua language, while PyTorch is a Python interface for Torch, offering more advanced features like dynamic computation graphs.