问题
var = [[0, 1, -4, 8],
[2, -3, 2, 1],
[5, -8, 7, 1]]
var = torch.Tensor(var)
Here, var
is a 3 x 4 (2d) tensor. How the first and second row can be swapped to get the following 2d tensor?
2, -3, 2, 1
0, 1, -4, 8
5, -8, 7, 1
回答1:
The other answer does not work, as some dimensions get overwritten before they are copied:
>>> var = [[0, 1, -4, 8],
[2, -3, 2, 1],
[5, -8, 7, 1]]
>>> x = torch.tensor(var)
>>> index = torch.LongTensor([1, 0, 2])
>>> x[index] = x
>>> x
tensor([[ 0, 1, -4, 8],
[ 0, 1, -4, 8],
[ 5, -8, 7, 1]])
For me, it suffices to create a new tensor (with separate underlying storage) to hold the result:
>>> x = torch.tensor(var)
>>> index = torch.LongTensor([1, 0, 2])
>>> y = torch.zeros_like(x)
>>> y[index] = x
Alternatively, you can use (index_copy_)[https://pytorch.org/docs/stable/tensors.html#torch.Tensor.index_copy_] (following the explanation in discuss.pytorch.org), although I don't see an advantage for either way at the moment.
回答2:
Generate the permutation index you desire:
index = torch.LongTensor([1,0,2])
Apply the permutation:
var[index] = var
回答3:
As other answers suggested that your permutation index should be a tensor itself, but it is not necessary. You can swap 1st and 2nd row like this:
>>> var
tensor([[ 0, 1, -4, 8],
[ 2, -3, 2, 1],
[ 5, -8, 7, 1]])
>>> var[[0, 1]] = var[[1, 0]]
>>> var
tensor([[ 2, -3, 2, 1],
[ 0, 1, -4, 8],
[ 5, -8, 7, 1]])
var
can be a NumPy array or PyTorch tensor.
来源:https://stackoverflow.com/questions/44935176/how-two-rows-can-be-swapped-in-a-torch-tensor