- torch.nn.functional.kl_div(input, target, size_average=None, reduce=None, reduction='mean', log_target=False)¶
input (Tensor) – Tensor of arbitrary shape in log-probabilities.
target (Tensor) – Tensor of the same shape as input. See
log_targetfor the target’s interpretation.
size_average (bool, optional) – Deprecated (see
reduction). By default, the losses are averaged over each loss element in the batch. Note that for some losses, there multiple elements per sample. If the field
size_averageis set to
False, the losses are instead summed for each minibatch. Ignored when reduce is
reduce (bool, optional) – Deprecated (see
reduction). By default, the losses are averaged or summed over observations for each minibatch depending on
False, returns a loss per batch element instead and ignores
reduction (str, optional) – Specifies the reduction to apply to the output:
'none': no reduction will be applied
'batchmean': the sum of the output will be divided by the batchsize
'sum': the output will be summed
'mean': the output will be divided by the number of elements in the output Default:
log_target (bool) – A flag indicating whether
targetis passed in the log space. It is recommended to pass certain distributions (like
softmax) in the log space to avoid numerical issues caused by explicit
- Return type
reduceare in the process of being deprecated, and in the meantime, specifying either of those two args will override
'mean'doesn’t return the true kl divergence value, please use
'batchmean'which aligns with KL math definition.