TL;DR

Implementing the Frechet distribution in torch.distributions or finding a PyTorch-compatible library that supports it could resolve the issue.

Guidance

• Review the PyTorch documentation and existing libraries to determine if the Frechet distribution is already available or if there are plans to add it.
• Consider implementing the Frechet distribution as a transformation of the Weibull distribution, using the affine transformation for the location parameter as described in the Wikipedia article.
• Look into existing PyTorch-compatible libraries that may already support the Frechet distribution, such as those mentioned in the alternatives section.
• If implementation is necessary, start by creating a prototype using PyTorch tensors to ensure compatibility.

Example

No code example is provided due to the lack of specific implementation details in the issue.

Notes

The solution may depend on the specific requirements of the project, such as performance or accuracy constraints. Additionally, the implementation details may vary depending on the chosen approach.

Recommendation

Apply workaround: Implement the Frechet distribution using a transformation of the Weibull distribution or find a PyTorch-compatible library that supports it, as this approach allows for a flexible and compatible solution.