import tensorflow as tf

            out_blocks = tf.transpose(out_blocks, (1, 2, 3, 0, 4))

        # Combine to constant channels
        with tf.variable_scope('combine'):
            W = self._make_var('W', (ni, block_ch * block_ch))
            W = tf.gather(W, unused_indices, axis=0)
            W = tf.reshape(W, (1, 1, num_out_blocks * block_ch, block_ch))
            X = tf.reshape(out_blocks, (-1, w, h, num_out_blocks * block_ch))
            X = tf.nn.relu(X)
            X = tf.nn.conv2d(X, W, (1, 1, 1, 1), padding='SAME')
