import tensorflow as tf

                                 data_format='channels_last', padding= "same",
                                strides=(2, 1), 
                                activation=tf.nn.relu)
        pool5 = conv5        
        pool5 = tf.transpose(pool5, [0, 3, 1, 2])
        size = pool5.shape[-1] * pool5.shape[-2] * pool5.shape[-3]

        logits = tf.layers.dense(tf.reshape(pool5,(-1, size)), units=256*amp_factor)
