From the linked article, to help others like me who mostly scan the comments > PyTorch LSTM network is faster because, by default, it uses cuRNN’s LSTM impleme

From the linked article, to help others like me who mostly scan the comments > PyTorch LSTM network is faster because, by default, it uses cuRNN’s LSTM implementation which fuses layers, steps and point-wise operations. See blog-post on this here. > Tensorflow’s RNNs (in r1.2), by default, do not use cuDNN’s RNN, and their ‘call’ function describes only one time-step of computation, hence a lot of optimization opportunities are lost. On the flip side, though, this gives user much more flexibility, provided that the user knows what he is doing.