Finally, it has a JIT (Just-In-Time) component that takes your code and optimizes it for the XLA compiler, resulting in significant performance improvements over TensorFlow and PyTorch.

Is PyTorch better ... TF construction. TensorFlow has very wide support for parallel and distributed training. If you have 100 GPU… well, if you have 100 GPU, stop wasting time here and go ...

For these cases, PyTorch and TensorFlow can be quite effective ... Training a deep neural network from scratch is time-consuming and requires a lot of tagged data. Transfer learning takes less ...

Similar wars seem to be flaring up around PyTorch ... user growth over the past few years. Therefore one can expect that PyTorch’s ecosystem might outgrow TensorFlow’s in due time.