Returns a tensor containing the indices of all non-zero elements of input. Each row in the result contains the indices of a non-zero element in input. The result is sorted lexicographically, with the last index changing the fastest (C-style).
If input has n n n dimensions, then the resulting indices tensor out is of size ( z × n ) (z \times n) (z×n), where z z z is the total number of non-zero elements in the input tensor.
Note
This function is similar to NumPy’s argwhere.
When input is on CUDA, this function causes host-device synchronization.
>>> t = torch.tensor([1, 0, 1])
>>> torch.argwhere(t)
tensor([[0],
[2]])
>>> t = torch.tensor([[1, 0, 1], [0, 1, 1]])
>>> torch.argwhere(t)
tensor([[0, 0],
[0, 2],
[1, 1],
[1, 2]])
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