import tensorflow as tf

            _debug(self.conv2)

        with tf.variable_scope('conv3_x'):
            self.conv3 = self._residual_block('conv3_1', self.conv2, 128, pool_first=True, strides=2)
            _debug(self.conv3)
            self.conv3 = self._residual_block('conv3_2', self.conv3, 128)
            _debug(self.conv3)

        with tf.variable_scope('conv4_x'):
            self.conv4 = self._residual_block('conv4_1', self.conv3, 256, pool_first=True, strides=2)
            _debug(self.conv4)
            self.conv4 = self._residual_block('conv4_2', self.conv4, 256)
            _debug(self.conv4)

        with tf.variable_scope('conv5_x'):
            self.conv5 = self._residual_block('conv5_1', self.conv4, 512, pool_first=True, strides=2)
            _debug(self.conv5)
            self.conv5 = self._residual_block('conv5_2', self.conv5, 512)
            _debug(self.conv5)

        if self.test_classification:
            with tf.variable_scope('logits'):
                print('Building unit: logits')
                self.score = tf.reduce_mean(self.conv5, axis=[1, 2])
                self.score = self._fc('logits_dense', self.score, output_dim=self.num_classes, l2_strength=self.wd)
                print('logits-shape: ' + str(self.score.shape.as_list()))

        self.feed1 = self.conv4
