torch.nn.functional.gaussian_nll_loss#
- torch.nn.functional.gaussian_nll_loss(input, target, var, full=False, eps=1e-06, reduction='mean')[source]#
Compute the Gaussian negative log likelihood loss.
See
GaussianNLLLossfor details.- Parameters
input (Tensor) – Expectation of the Gaussian distribution.
target (Tensor) – Sample from the Gaussian distribution.
var (Union[Tensor, float]) – Tensor of positive variance(s), one for each of the expectations in the input (heteroscedastic), or a single one (homoscedastic), or a positive scalar value to be used for all expectations.
full (bool, optional) – Whether to include the constant term in the loss calculation. Default:
False.eps (float, optional) – Value added to var, for stability. Default: 1e-6.
reduction (str, optional) – Specifies the reduction to apply to the output:
'none'|'mean'|'sum'.'none': no reduction will be applied,'mean': the output is the average of all batch member losses,'sum': the output is the sum of all batch member losses. Default:'mean'.
- Return type
