R/gen-namespace-docs.R
, R/gen-namespace-examples.R
, R/gen-namespace.R
torch_nonzero.Rd
Nonzero
torch_nonzero(self)
self | (Tensor) the input tensor. |
---|
[`torch_nonzero(..., as_tuple=False) <torch.nonzero>`] (default) returns a 2-D tensor where each row is the index for a nonzero value. [`torch_nonzero(..., as_tuple=TRUE) <torch.nonzero>`] returns a tuple of 1-D index tensors, allowing for advanced indexing, so `x[x.nonzero(as_tuple=TRUE)]` gives all nonzero values of tensor `x`. Of the returned tuple, each index tensor contains nonzero indices for a certain dimension. See below for more details on the two behaviors.
When as_tuple
is FALSE
(default):
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 \(n\) dimensions, then the resulting indices tensor
out
is of size \((z \times n)\), where \(z\) is the total number of
non-zero elements in the input
tensor.
When as_tuple
is TRUE
:
Returns a tuple of 1-D tensors, one for each dimension in input
,
each containing the indices (in that dimension) of all non-zero elements of
input
.
If input
has \(n\) dimensions, then the resulting tuple contains \(n\)
tensors of size \(z\), where \(z\) is the total number of
non-zero elements in the input
tensor.
As a special case, when input
has zero dimensions and a nonzero scalar
value, it is treated as a one-dimensional tensor with one element.
#> torch_tensor #> 0 #> 1 #> 2 #> 4 #> [ CPULongType{4,1} ]