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.

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 ...

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.