Solved – How to set the dimension of hidden states for Recurrent Neural Network (RNN)

I'm learning RNN and know that a basic RNN maps an input sequence to a sequence of hidden states, and then maps the sequence of hidden states to the output sequence. I'm confused about the dimension of the 3 sequences. The dimension of the input and output sequence can be found from data, but what about the dimension of the hidden states? Is it set by people in advance, or set to be the dimension of the output or input sequence?

The dimension of the RNN hidden state can be chosen in advance. It is independent of the dimension of the input or output sequences.

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