utilities.py 文件源码

def unpool(pool, ind, shape, ksize=[1, 2, 2, 1], scope=None):
    with tf.name_scope(scope):
        input_shape =  tf.shape(pool)
        output_shape = [input_shape[0], input_shape[1] * ksize[1], input_shape[2] * ksize[2], input_shape[3]]
        flat_input_size = tf.cumprod(input_shape)[-1]
        flat_output_shape = tf.stack([output_shape[0], output_shape[1] * output_shape[2] * output_shape[3]])
        pool_ = tf.reshape(pool, tf.stack([flat_input_size]))
        batch_range = tf.reshape(tf.range(tf.cast(output_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([flat_input_size, 1]))
        ind_ = tf.reshape(ind, tf.stack([flat_input_size, 1]))
        ind_ = tf.concat([b, ind_], 1)
        ret = tf.scatter_nd(ind_, pool_, shape=tf.cast(flat_output_shape, tf.int64))
        ret = tf.reshape(ret, tf.stack(output_shape))
        ret = tf.reshape(ret, shape=shape)
        return ret