semiring-torch 0.0.1

Semiring programming in PyTorch

semiring_torch

Run your pytorch code on any semiring with a single line of code! Semiring_torch is built on top of autoray.

Warning: this is a proof of concept. Expect bugs and missing features.

Example

By using the logarithmic semiring, you can easily write numerically stable code. In the following example, we compute a matrix product in log-space.

Regular torch	semiring_torch
import torch x1 = torch.tensor([[0.1, 0.6], [0.1, 0.4]]) x2 = torch.tensor([[0.5, 0.3], [0.2, 0.1]]) x1 = x1.log() x2 = x2.log() result = x1[:, :, None] + x2[None, :, :] result = torch.logsumexp(result, dim=1) result = result.exp()	from autoray import numpy as torch from semiring_torch import logarithmic_semiring with logarithmic_semiring: x1 = torch.tensor([[0.1, 0.6], [0.1, 0.4]]) x2 = torch.tensor([[0.5, 0.3], [0.2, 0.1]]) result = x1 @ x2

Supported semirings

Currently only the logarithmic semiring is supported, but more semirings can be added easily.