LogSoftmax

class torch.nn.LogSoftmax(dim: Optional[int] = None)

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

$\text{LogSoftmax}(x_{i}) = \log\left(\frac{\exp(x_i) }{ \sum_j \exp(x_j)} \right)$

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)