Table of Contents
Shortcuts

# torch.nn.functional.softmin

torch.nn.functional.softmin(input, dim=None, _stacklevel=3, dtype=None)

  Applies a softmin function.

  Note that Softmin(x)=Softmax(−x)\text{Softmin}(x) = \text{Softmax}(-x)Softmin(x)=Softmax(−x). See softmax definition for mathematical formula.

  See `Softmin` for more details.

  Parameters:

    - input (Tensor) – input

    - dim (int) – A dimension along which softmin will be computed (so every slice along dim will sum to 1).

    - dtype (`torch.dtype`, optional) – the desired data type of returned tensor. If specified, the input tensor is casted to `dtype` before the operation is performed. This is useful for preventing data type overflows. Default: None.

  Return type:

    Tensor

## Docs

Access comprehensive developer documentation for PyTorch

View Docs

## Tutorials

Get in-depth tutorials for beginners and advanced developers

View Tutorials

## Resources

Find development resources and get your questions answered

View Resources

To analyze traffic and optimize your experience, we serve cookies on this site. By clicking or navigating, you agree to allow our usage of cookies. As the current maintainers of this site, Facebook’s Cookies Policy applies. Learn more, including about available controls: Cookies Policy.