import tensorflow as tf

                         + self.b_out

        else:
            new_output = tf.matmul(tf.nn.relu(new_state), self.W_out * self.output_Connectivity,
                                   transpose_b=True, name="3") + self.b_out

        return new_output

    def compute_predictions(self):

        rnn_inputs = tf.unstack(self.x, axis=1)
        state = self.init_state
        rnn_outputs = []
        rnn_states = []
        for rnn_input in rnn_inputs:
            state = self.rnn_step(rnn_input, state)
            output = self.rnn_output(state)
            rnn_outputs.append(output)
            rnn_states.append(state)
        return tf.transpose(rnn_outputs, [1, 0, 2]), rnn_states
