import tensorflow as tf

                cell_drop=tf.contrib.rnn.DropoutWrapper(lstm,variational_recurrent=True,dtype=tf.float32, input_size=num_input,input_keep_prob=input_prob,state_keep_prob=state_prob)


        elif cell_type == 'GRU':
            
            if activation == 'linear':
                gru=tf.nn.rnn_cell.GRUCell(state_size, activation = tf.identity)
                cell_drop=tf.contrib.rnn.DropoutWrapper(gru,variational_recurrent=True,dtype=tf.float32, input_size=num_input,input_keep_prob=input_prob,state_keep_prob=state_prob)
            elif activation == 'relu':
                gru=tf.nn.rnn_cell.GRUCell(state_size, activation = tf.nn.relu)
                cell_drop=tf.contrib.rnn.DropoutWrapper(gru,variational_recurrent=True,dtype=tf.float32, input_size=num_input,input_keep_prob=input_prob,state_keep_prob=state_prob)
            else:
                gru=tf.nn.rnn_cell.GRUCell(state_size)
                cell_drop=tf.contrib.rnn.DropoutWrapper(gru,variational_recurrent=True,dtype=tf.float32, input_size=num_input,input_keep_prob=input_prob,state_keep_prob=state_prob)
