如何使用 torch.roll 移动张量的特定元素?
How do I shift specific elements of a tensor with torch.roll?
我有一个张量 x
,它看起来像这样:
x = tensor([ 1, 2, 3, 4, 5],
[ 6, 7, 8, 9, 10]
[ 11, 12, 13, 14, 15])
我正在尝试切换每个张量的前两个和最后两个数字,如下所示:
x = tensor([ 4, 5, 3, 1, 2],
[ 9, 10, 8, 6, 7],
[ 14, 15, 13, 11, 12])
如何使用 torch.roll()
执行此操作?我如何切换 3 而不是 1?
不确定单独使用 torch.roll
是否可以完成...但是,您可以通过使用临时张量和配对赋值来获得所需的结果:
>>> x = torch.arange(1, 16).reshape(3,-1)
tensor([[ 1, 2, 3, 4, 5],
[ 6, 7, 8, 9, 10],
[11, 12, 13, 14, 15]])
>>> tmp = x.clone()
# swap the two sets of columns
>>> x[:,:2], x[:,-2:] = tmp[:,-2:], tmp[:,:2]
这样张量 x
已经变异为:
>>> x
tensor([[ 4, 5, 3, 1, 2],
[ 9, 10, 8, 6, 7],
[14, 15, 13, 11, 12]])
您可以使用 torch.roll
和一些索引来完成此操作:
>>> x = torch.arange(1, 21).reshape(4,-1)
tensor([[ 1, 2, 3, 4, 5],
[ 6, 7, 8, 9, 10],
[11, 12, 13, 14, 15],
[16, 17, 18, 19, 20]])
>>> rolled = x.roll(-2,0)
tensor([[11, 12, 13, 14, 15],
[16, 17, 18, 19, 20],
[ 1, 2, 3, 4, 5],
[ 6, 7, 8, 9, 10]])
# overwrite columns [1,-1[ from rolled with those from x
>>> rolled[:, 1:-1] = x[:, 1:-1]
在这一端你得到:
>>> rolled
tensor([[11, 2, 3, 4, 15],
[16, 7, 8, 9, 20],
[ 1, 12, 13, 14, 5],
[ 6, 17, 18, 19, 10]])
我有一个张量 x
,它看起来像这样:
x = tensor([ 1, 2, 3, 4, 5],
[ 6, 7, 8, 9, 10]
[ 11, 12, 13, 14, 15])
我正在尝试切换每个张量的前两个和最后两个数字,如下所示:
x = tensor([ 4, 5, 3, 1, 2],
[ 9, 10, 8, 6, 7],
[ 14, 15, 13, 11, 12])
如何使用 torch.roll()
执行此操作?我如何切换 3 而不是 1?
不确定单独使用 torch.roll
是否可以完成...但是,您可以通过使用临时张量和配对赋值来获得所需的结果:
>>> x = torch.arange(1, 16).reshape(3,-1)
tensor([[ 1, 2, 3, 4, 5],
[ 6, 7, 8, 9, 10],
[11, 12, 13, 14, 15]])
>>> tmp = x.clone()
# swap the two sets of columns
>>> x[:,:2], x[:,-2:] = tmp[:,-2:], tmp[:,:2]
这样张量 x
已经变异为:
>>> x
tensor([[ 4, 5, 3, 1, 2],
[ 9, 10, 8, 6, 7],
[14, 15, 13, 11, 12]])
您可以使用 torch.roll
和一些索引来完成此操作:
>>> x = torch.arange(1, 21).reshape(4,-1)
tensor([[ 1, 2, 3, 4, 5],
[ 6, 7, 8, 9, 10],
[11, 12, 13, 14, 15],
[16, 17, 18, 19, 20]])
>>> rolled = x.roll(-2,0)
tensor([[11, 12, 13, 14, 15],
[16, 17, 18, 19, 20],
[ 1, 2, 3, 4, 5],
[ 6, 7, 8, 9, 10]])
# overwrite columns [1,-1[ from rolled with those from x
>>> rolled[:, 1:-1] = x[:, 1:-1]
在这一端你得到:
>>> rolled
tensor([[11, 2, 3, 4, 15],
[16, 7, 8, 9, 20],
[ 1, 12, 13, 14, 5],
[ 6, 17, 18, 19, 10]])