窗口多维 Tensorflow 数据集 [英] Window Multidimensional Tensorflow Dataset
本文介绍了窗口多维 Tensorflow 数据集的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我有形状为 m
by n
的二维数据,我想将其大小为 w
沿第一个轴窗口化为数据集mw
个二维数组,每个数组的大小为 w
乘 n
.例如,如果数据是:
I have 2-dimensional data with shape m
by n
that I want to window with size w
along the first axis into a dataset of m-w
many two-dimensional arrays each of size w
by n
. For instance if the data is:
[[0, 1, 2 ],
[3, 4, 5 ],
[6, 7, 8 ],
[9, 10, 11]]
然后我想把它窗口化
[[[0, 1 , 2 ],
[3, 4 , 5 ],
[6, 7 , 8 ]],
[[3, 4 , 5 ],
[6, 7 , 8 ],
[9, 10, 11]]]
我可以将数据组合成正确的集合:
I can window the data together into the right sets:
dataset = tf.data.Dataset.from_tensor_slices(np.arange(5*3).reshape(5,3))
dataset = dataset.window(size=3,shift=1,drop_remainder=True)
for window in dataset : print(list(window.as_numpy_iterator()))
>>>[array([0, 1, 2]), array([3, 4, 5]), array([6, 7, 8])]
>>>[array([3, 4, 5]), array([6, 7, 8]), array([ 9, 10, 11])]
>>>[array([6, 7, 8]), array([ 9, 10, 11]), array([12, 13, 14])]
但我不知道如何将数据重新恢复为堆叠形状.我想也许是 tf.stack,但没有骰子.有人知道如何完成吗?
but I can't figure out how to get the data back into the stacked shape again. I thought maybe tf.stack, but no dice on that. Does anybody know how to finish this?
推荐答案
I found the answer here actually. I don't know why it works, but it does:
dataset = tf.data.Dataset.from_tensor_slices(np.arange(5*3).reshape(5,3))
dataset = dataset.window(size=3,shift=1)
dataset = dataset.flat_map(lambda x : x.batch(3))
for d in dataset : print(d)
使
tf.Tensor(
[[0 1 2]
[3 4 5]
[6 7 8]], shape=(3, 3), dtype=int64)
tf.Tensor(
[[ 3 4 5]
[ 6 7 8]
[ 9 10 11]], shape=(3, 3), dtype=int64)
tf.Tensor(
[[ 6 7 8]
[ 9 10 11]
[12 13 14]], shape=(3, 3), dtype=int64)
tf.Tensor(
[[ 9 10 11]
[12 13 14]], shape=(2, 3), dtype=int64)
tf.Tensor([[12 13 14]], shape=(1, 3), dtype=int64)
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