import tensorflow as tf


        with tf.variable_scope("Model_Encoder_Layer"):
            inputs = tf.concat(attention_outputs, axis = -1)
            self.enc = [conv(inputs, d, name = "input_projection")]
            for i in range(3):
                if i % 2 == 0: # dropout every 2 blocks
                    self.enc[i] = tf.nn.dropout(self.enc[i], 1.0 - self.dropout)
                self.enc.append(
                    residual_block(self.enc[i],
                        num_blocks = 7,
                        num_conv_layers = 2,
                        kernel_size = 5,
