Extracting the top-k value-indices from a 1-D Tensor

As of pull request #496 Torch now includes a built-in API named torch.topk. Example:

> t = torch.Tensor{9, 1, 8, 2, 7, 3, 6, 4, 5}

-- obtain the 3 smallest elements
> res = t:topk(3)
> print(res)
 1
 2
 3
[torch.DoubleTensor of size 3]

-- you can also get the indices in addition
> res, ind = t:topk(3)
> print(ind)
 2
 4
 6
[torch.LongTensor of size 3]

-- alternatively you can obtain the k largest elements as follow
-- (see the API documentation for more details)
> res = t:topk(3, true)
> print(res)
 9
 8
 7
[torch.DoubleTensor of size 3]

At the time of writing the CPU implementation follows a sort and narrow approach (there are plans to improve it in the future). That being said an optimized GPU implementation for cutorch is currently being reviewed.

You can use topk function.

for example:

import torch

t = torch.tensor([5.7, 1.4, 9.5, 1.6, 6.1, 4.3])

values,indices = t.topk(2)

print(values)
print(indices)

the result:

tensor([9.5000, 6.1000])
tensor([2, 4])