Training RNNs in batches

Hi All, I’ve been watching the CS224N NLP lectures from Stanford on YouTube. In Lecture 9, the instructor says that RNNs suffer from being unparallelizable, which makes intuitive sense to me. However, it is clearly possible to batch process inputs to an RNN during training as evidenced by the support for this on libraries such as PyTorch and TensorFlow. What am I missing here? Is there a distinction between parallelization and batching that I’m not understanding?

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