LogSoftmax

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

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)

Return type

None

Examples:

>>> m = nn.LogSoftmax(dim=1)
>>> input = torch.randn(2, 3)
>>> output = m(input)

extra_repr() [source]

Return the extra representation of the module.

Return type

str

forward(input) [source]

Runs the forward pass.

Return type

Tensor