torch.std_mean¶
-
torch.
std_mean
(input, dim, unbiased, keepdim=False, *, out=None)¶ If
unbiased
isTrue
, Bessel’s correction will be used to calculate the standard deviation. Otherwise, the sample deviation is calculated, without any correction.- Parameters
- Keyword Arguments
- Returns
A tuple (std, mean) containing the standard deviation and mean.
-
torch.
std_mean
(input, unbiased)
Calculates the standard deviation and mean of all elements in the
input
tensor.If
unbiased
isTrue
, Bessel’s correction will be used. Otherwise, the sample deviation is calculated, without any correction.- Parameters
- Returns
A tuple (std, mean) containing the standard deviation and mean.
Example:
>>> a = torch.tensor([[-0.8166, -1.3802, -0.3560]]) >>> torch.std_mean(a, unbiased=False) (tensor(0.4188), tensor(-0.8509))