nn.RNN expects an input tensor in the shape [seq_len, batch_size, features] in the default setup as described in the docs 2.
The convolution arguments are generally independent from this shape as long as you know, how you would like to reshape the last conv output.
Note that a conv layer will output an activation in the shape [batch_size, nb_filters, height, width], which you would have to reshape to the expected input shape of the RNN.