and decided instead to port their code to PyTorch. TensorFlow also lost steam in the research community, which started preferring the flexibility PyTorch offered a few years ago, resulting in a ...

PyTorch recreates the graph on the fly at each iteration step. In contrast, TensorFlow by default creates a single data flow graph, optimizes the graph code for performance, and then trains the model.

Therefore one can expect that PyTorch’s ecosystem might outgrow TensorFlow’s in due time. As cumbersome as TensorFlow might be to code, once it’s written is a lot easier to deploy than PyTorch.

In the dynamic world of machine learning, two heavyweight frameworks often dominate the conversation: PyTorch and TensorFlow. These frameworks are more than just a means to create sophisticated ...