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https://github.com/pytorch/hydra-torch
Configuration classes enabling type-safe PyTorch configuration for Hydra apps
https://github.com/pytorch/hydra-torch
Last synced: about 1 month ago
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Configuration classes enabling type-safe PyTorch configuration for Hydra apps
- Host: GitHub
- URL: https://github.com/pytorch/hydra-torch
- Owner: pytorch
- License: mit
- Created: 2020-09-25T22:05:47.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2022-09-27T16:43:58.000Z (about 2 years ago)
- Last Synced: 2024-09-30T15:23:13.770Z (about 1 month ago)
- Language: Python
- Homepage:
- Size: 10.9 MB
- Stars: 199
- Watchers: 18
- Forks: 16
- Open Issues: 29
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
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README
# hydra-torch
Configuration classes enabling type-safe PyTorch configuration for Hydra apps.
**This repo is work in progress.**
The config dataclasses are generated using [configen](https://github.com/facebookresearch/hydra/tree/main/tools/configen), check it out if you want to generate config dataclasses for your own project.
### Install:
```
# For now, please obtain through github. Soon, versioned (per-project) dists will be on PyPI.
pip install git+https://github.com/pytorch/hydra-torch
```
### Example config:
Here is one of many configs available. Notice it uses the defaults defined in the torch function signatures:
```python
@dataclass
class TripletMarginLossConf:
_target_: str = "torch.nn.modules.loss.TripletMarginLoss"
margin: float = 1.0
p: float = 2.0
eps: float = 1e-06
swap: bool = False
size_average: Any = None
reduce: Any = None
reduction: str = "mean"
```
### Importing Convention:
```python
from hydra_configs..path.to.module import Conf
```
where `` is the package being configured and `path.to.module` is the path in the original package.
Inferring where the package is located is as simple as prepending `hydra_configs.` and postpending `Conf` to the original class import:
e.g.
```python
#module to be configured
from torch.optim.adam import Adam
#config for the module
from hydra_configs.torch.optim.adam import AdamConf
```
### Getting Started:
Take a look at our tutorial series:
1. [Basic Tutorial](examples/mnist_00.md)
2. Intermediate Tutorial (coming soon)
3. Advanced Tutorial (coming soon)
### Other Config Projects:
A list of projects following the `hydra_configs` convention (please notify us if you have one!):
[Pytorch Lightning](https://github.com/romesco/hydra-lightning)
### License
hydra-torch is licensed under [MIT License](LICENSE).