builder.py 文件源码

def Unpool_layer(self, pool, ind, k_size=[1, 2, 2, 1]):
        # https://github.com/tensorflow/tensorflow/issues/2169
        """
           Unpooling layer after max_pool_with_argmax.
           Args:
               pool:   max pooled output tensor
               ind:      argmax indices
               k_size:     k_size is the same as for the pool
           Return:
               unpool:    unpooling tensor
        """
        with tf.name_scope('Unpool'):
            input_shape =  tf.shape(pool)
            input_shape_aslist = pool.get_shape().as_list()
            output_shape = tf.stack([input_shape[0], input_shape[1] * k_size[1], input_shape[2] * k_size[2], input_shape[3]])
            output_shapeaslist = [-1,  input_shape_aslist[1]* k_size[1] ,  input_shape_aslist[2]  * k_size[2], input_shape_aslist[3]]

            pool_ = tf.reshape(pool, [input_shape_aslist[1] * input_shape_aslist[2] * input_shape_aslist[3]])
            batch_range = tf.reshape(tf.range(tf.cast(input_shape[0], tf.int64), dtype=ind.dtype), 
                                              shape=tf.stack([input_shape[0], 1, 1, 1]))
            b = tf.ones_like(ind) * batch_range
            b = tf.reshape(b, tf.stack([ input_shape_aslist[1] * input_shape_aslist[2] * input_shape_aslist[3], 1]))
            ind_ = tf.reshape(ind, tf.stack( [input_shape_aslist[1] * input_shape_aslist[2] * input_shape_aslist[3], 1]))
            ind_ = tf.concat([b, ind_], 1)
            ret = tf.scatter_nd(ind_, pool_, shape=tf.cast([input_shape[0], output_shapeaslist[1] * output_shapeaslist[2] * output_shapeaslist[3] ], tf.int64))
            ret = tf.reshape(ret, [-1, output_shapeaslist[1], output_shapeaslist[2], output_shapeaslist[3]])
            return ret