recurrent neural networks as previously mentionedrnns can deal with arbitrarily long inputscorrespondinglythey need to be trained on arbitrarily long inputs figures - through - illustrate how an rnn is unrolled for different sizes of inputs note that once the rnn is unrolledthe process of training the rnn is identical to training regular neural networkas covered in earlier in the figure the rnn described in figure - is unrolled for input sizes of and figure - unrolling the rnn corresponding to figure - (step and step figure - demonstrates step and step -- unrolling for input sequences ( and ( )sequentially in step given that we have no previous hidden statewe pass ( to the current hidden state in figure - we limit the time sequences to unroll thereforethe network is unrolled to steps figure - and figure - demonstrate the incremental unrolling steps sequentially