keras/src/layers/rnn/dropout_rnn_cell.py/DropoutRNNCell/reset_dropout_mask
class DropoutRNNCell:    def reset_dropout_mask(self):
        """Reset the cached dropout mask if any.

        The RNN layer invokes this in the `call()` method
        so that the cached mask is cleared after calling `cell.call()`. The
        mask should be cached across all timestep within the same batch, but
        shouldn't be cached between batches.
        """
        self._dropout_mask = None