In tf.keras.layers.RNN 1, the documentation states:

Note on using statefulness in RNNs: You can set RNN layers to be ‘stateful’, which means that the states computed for the samples in one batch will be reused as initial states for the samples in the next batch. This assumes a one-to-one mapping between samples in different successive batches.



Does this mean that if stateful = True, then states are not reset between epochs as well?


If stateful = False, is the layer’s state being reset each time the layer is called?