I have been reading about RNNs and I have some confusion between the number of timesteps and number of units in an RNN layer (which after searching for an answer) seems to be a common thing.
I understand that the idea behind using a RNN is to capture the relationship between every element in the sequence with other elements. In an example of text classification with tweets padded to a length of 20 words, the number of units in a layer -which I understand is the same as the number of timesteps- should be equal to the length of the input sequence which is 20.
I also saw some examples that deals with the number of units as a hyperparameter to be tuned.
Which of these is correct?
This picture is from a course on coursera by Andrew Ng. The super script Tx indicates the number of timesteps which is the same as the number of units in the network.