Exploring the PyTorch library in contrast to TensorFlow

PyTorch is a machine learning library for Python based on the Torch library. PyTorch is extensively used as a deep learning tool both for research as well as building industrial applications. It is primarily developed by Meta. PyTorch is competition for the other well-known deep learning library – TensorFlow, which is developed by Google. The initial difference between these two was that PyTorch was based on eager execution whereas TensorFlow was built on graph-based deferred execution. Although, TensorFlow now also provides an eager execution mode.

Eager execution is basically an imperative programming mode where mathematical operations are computed immediately. A deferred execution mode would have all the operations stored in a computational graph without immediate calculations and then the entire graph would be evaluated later. Eager execution is considered advantageous for reasons such as intuitive flow, easy debugging...