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LogSoftmax

class torch.nn.LogSoftmax(dim=None)[source]

Applies the log(Softmax(x))\log(\text{Softmax}(x)) function to an n-dimensional input Tensor. The LogSoftmax formulation can be simplified as:

LogSoftmax(xi)=log(exp(xi)jexp(xj))\text{LogSoftmax}(x_{i}) = \log\left(\frac{\exp(x_i) }{ \sum_j \exp(x_j)} \right)
Shape:
  • Input: ()(*) where * means, any number of additional dimensions

  • Output: ()(*) , same shape as the input

Parameters

dim (int) – A dimension along which LogSoftmax will be computed.

Returns

a Tensor of the same dimension and shape as the input with values in the range [-inf, 0)

Examples:

>>> m = nn.LogSoftmax()
>>> input = torch.randn(2, 3)
>>> output = m(input)

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