Std
Arguments
- self
(Tensor) the input tensor.
- dim
(int or tuple of ints) the dimension or dimensions to reduce.
- correction
The type of correction.
- unbiased
(bool) whether to use the unbiased estimation or not
- keepdim
(bool) whether the output tensor has
dimretained or not.
std(input, unbiased=TRUE) -> Tensor
Returns the standard-deviation of all elements in the input tensor.
If unbiased is FALSE, then the standard-deviation will be calculated
via the biased estimator. Otherwise, Bessel's correction will be used.
std(input, dim, unbiased=TRUE, keepdim=False, out=NULL) -> Tensor
Returns the standard-deviation of each row of the input tensor in the
dimension dim. If dim is a list of dimensions,
reduce over all of them.
If keepdim is TRUE, the output tensor is of the same size
as input except in the dimension(s) dim where it is of size 1.
Otherwise, dim is squeezed (see torch_squeeze), resulting in the
output tensor having 1 (or len(dim)) fewer dimension(s).
If unbiased is FALSE, then the standard-deviation will be calculated
via the biased estimator. Otherwise, Bessel's correction will be used.
Examples
if (torch_is_installed()) {
a = torch_randn(c(1, 3))
a
torch_std(a)
a = torch_randn(c(4, 4))
a
torch_std(a, dim=1)
}
#> torch_tensor
#> 0.7483
#> 1.7592
#> 0.7803
#> 0.5091
#> [ CPUFloatType{4} ]