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.

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

Tensor

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