Table of Contents
Shortcuts

# torch.logaddexp

torch.logaddexp(input, other, *, out=None) → Tensor

  Logarithm of the sum of exponentiations of the inputs.

  Calculates pointwise log⁡(e x+e y)\log\left(e^x + e^y\right)log(e x+e y). This function is useful in statistics where the calculated probabilities of events may be so small as to exceed the range of normal floating point numbers. In such cases the logarithm of the calculated probability is stored. This function allows adding probabilities stored in such a fashion.

  This op should be disambiguated with `torch.logsumexp()` which performs a reduction on a single tensor.

  Parameters:

    - input (Tensor) – the input tensor.

    - other (Tensor) – the second input tensor

  Keyword Arguments:

    out (Tensor, optional) – the output tensor.

  Example:

      >>> torch.logaddexp(torch.tensor([-1.0]), torch.tensor([-1.0, -2, -3]))
      tensor([-0.3069, -0.6867, -0.8731])
      >>> torch.logaddexp(torch.tensor([-100.0, -200, -300]), torch.tensor([-1.0, -2, -3]))
      tensor([-1., -2., -3.])
      >>> torch.logaddexp(torch.tensor([1.0, 2000, 30000]), torch.tensor([-1.0, -2, -3]))
      tensor([1.1269e+00, 2.0000e+03, 3.0000e+04])

## 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.