logsoftmaxix
Logsoftmaxix is a term used to describe the log-softmax operation applied along a designated axis of a tensor, where ix indicates the axis index. It is the log-probability version of the softmax function, computed separately for each slice of the tensor along that axis.
Mathematically, for a tensor X and a chosen axis dim = ix, the output Y has the same
Numerical stability is a key consideration. The common and stable implementation uses the log-sum-exp trick: log_softmax(x)
Applications and usage include computing log-probabilities for classification tasks, sequence models, and attention mechanisms where normalization
Relation to related concepts: logsoftmaxix is closely aligned with softmax and log_softmax, differing mainly by the