LogSoftmax#

classtorch.nn.LogSoftmax(dim=None)[source]#

Applies the$\log (\text{Softmax}(x))$log(Softmax(x)) function to an n-dimensional input Tensor.

The LogSoftmax formulation can be simplified as:

$$\text{LogSoftmax}(x_i)=\log \left(\frac{\exp (x_i)}{\sum _j\exp (x_j)}\right)$$LogSoftmax(xi​)=log(∑j​exp(xj​)exp(xi​)​)

Shape:

• Input:$(\ast )$(∗) where* means, any number of additionaldimensions

• Output:$(\ast )$(∗), 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 withvalues 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