Std
torch_std(self, dim, unbiased = TRUE, keepdim = FALSE)
self | (Tensor) the input tensor. |
---|---|
dim | (int or tuple of ints) the dimension or dimensions to reduce. |
unbiased | (bool) whether to use the unbiased estimation or not |
keepdim | (bool) whether the output tensor has |
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.
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.
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 #> 1.2264 #> 1.0589 #> 0.5738 #> 1.4700 #> [ CPUFloatType{4} ]