Created by: dingsiyu

• 版本、环境信息：    1）PaddlePaddle版本：1.5    2）CPU/GPU：cuda 10, cudnn 7.4    3）系统环境：centos 6    4）Python版本号 3

这是官方代码：

LoD-Tensor 转 Tensor

import paddle.fluid as fluid import numpy as np

创建一个 LoD-Tensor

a = fluid.create_lod_tensor(np.array([[1.1], [2.2],[3.3],[4.4]]).astype('float32'), [[1,3]], fluid.CPUPlace()) def LodTensor_to_Tensor(lod_tensor):

获取 LoD-Tensor 的 lod 信息

lod = lod_tensor.lod()

转换成 array

array = np.array(lod_tensor) new_array = []

依照原LoD-Tensor的层级信息，转换成Tensor

for i in range(len(lod[0]) - 1): new_array.append(array[lod[0][i]:lod[0][i + 1]]) return new_array new_array = LodTensor_to_Tensor(a)

输出结果

print(new_array)

Tensor 转 LoD-Tensor import paddle.fluid as fluid import numpy as np

def to_lodtensor(data, place):

存储Tensor的长度作为LoD信息

seq_lens = [len(seq) for seq in data] cur_len = 0 lod = [cur_len] for l in seq_lens: cur_len += l lod.append(cur_len)

对待转换的 Tensor 降维

flattened_data = np.concatenate(data, axis=0).astype("int64") flattened_data = flattened_data.reshape([len(flattened_data), 1])

为 Tensor 数据添加lod信息

res = fluid.LoDTensor() res.set(flattened_data, place) res.set_lod([lod]) return res

new_array 为上段代码中转换的Tensor

lod_tensor = to_lodtensor(new_array,fluid.CPUPlace())

输出 LoD 信息

print("The LoD of the result: {}.".format(lod_tensor.lod()))

检验与原Tensor数据是否一致

print("The array : {}.".format(np.array(lod_tensor)))

问题：为什么new_array是个list，按照标题，不是应该是tensor吗？ 而且，我直接向to_lodtensor输入一个tensor后，报错。具体如下：

代码： a = np.array([[1,2,3],[4,5,6],[7,8,9]], dtype="float32") b = fluid.layers.create_tensor(dtype="float32") fluid.layers.assign(a,b) lodtensor = to_lodtensor(b, fluid.CPUPlace)

报错信息： Traceback (most recent call last): File "b.py", line 56, in lodtensor = to_lodtensor(b, fluid.CPUPlace) File "b.py", line 35, in to_lodtensor seq_lens = [len(seq) for seq in data] File "b.py", line 35, in seq_lens = [len(seq) for seq in data] TypeError: object of type 'Variable' has no len()