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, 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:

@dataclass
class AdadeltaConf:
    _target_: str = "torch.optim.adadelta.Adadelta"
    params: Any = MISSING
    lr: Any = 1.0
    rho: Any = 0.9
    eps: Any = 1e-06
    weight_decay: Any = 0

(once pytorch updates type annotations, these will automatically change from Any -> Int/Float)

Getting Started:

Take a look at our tutorial series:

1. Basic Tutorial
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

License

hydra-torch is licensed under MIT License.