文件列表:

semiring_torch/
tests/
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# semiring_torch Run your pytorch code on any semiring with a single line of code! Semiring_torch is built on top of [autoray](https://github.com/jcmgray/autoray). ### 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
```python 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() result2 = x1[:, :, None] + x2[None, :, :] result2 = torch.logsumexp(result2, dim=1) result2 = result2.exp() ```	```python import autoray as ar from autoray import numpy as np from semiring_torch import * with ar.backend_like('log_torch'): x1 = np.array([[0.1, 0.6], [0.1, 0.4]]) x2 = np.array([[0.5, 0.3], [0.2, 0.1]]) result = x1 @ x2 ```

### Supported semirings Currently only the logarithmic semiring is supported. More semirings will be added soon.

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