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Applies the \(\log(\mbox{Softmax}(x))\) function to an n-dimensional input Tensor. The LogSoftmax formulation can be simplified as:
nn_log_softmax(dim)
a Tensor of the same dimension and shape as the input with values in the range [-inf, 0)
(int): A dimension along which LogSoftmax will be computed.
Input: \((*)\) where * means, any number of additional dimensions
*
Output: \((*)\), same shape as the input
$$ \mbox{LogSoftmax}(x_{i}) = \log\left(\frac{\exp(x_i) }{ \sum_j \exp(x_j)} \right) $$
if (torch_is_installed()) { m <- nn_log_softmax(1) input <- torch_randn(2, 3) output <- m(input) }
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