I have a question about types of RNN. Ian Goodfellow in his book Deep Learning writes:
Some examples of important design patterns for recurrent neural networks include the following:
• Recurrent networks that produce an output at each time step and have recurrent connections between hidden units, illustrated in figure 10.3.
• Recurrent networks that produce an output at each time step and have recurrent connections only from the output at one time step to the hidden units at the next time step, illustrated in figure 10.4
• Recurrent networks with recurrent connections between hidden units, that read an entire sequence and then produce a single output, illustrated in figure 10.5.
CHAPTER 10. SEQUENCE MODELING: RECURRENT AND RECURSIVE NETS
Next I read about RNN article by Andrej Karpathy http://karpathy.github.io/2015/05/21/rnn-effectiveness/ and his describe rnn architecture like relation model. My question is: description of types RNN by Ian Goodfellow are equal to Andrej Karpathy? If not what it the diffrence beetween this descriptions?