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[WIP][example] Extending SC Schema for Experiments #71

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[WIP][example] Extending SC Schema for Experiments #71

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1c38ac4
starter code for best practices example on extending configs
romesco Apr 16, 2021
148bdc6
caught me vimmin
romesco Apr 22, 2021
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5 changes: 5 additions & 0 deletions examples/extend_via_sc_schema/conf/config.yaml
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defaults:
- base_config
- optim: adam_exp_1.yaml

debug: true
4 changes: 4 additions & 0 deletions examples/extend_via_sc_schema/conf/optim/adam_exp_1.yaml
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defaults:
- base_adam

lr: 0.89
7 changes: 7 additions & 0 deletions examples/extend_via_sc_schema/conf/optim/adam_exp_2.yaml
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defaults:
- base_adam

lr: 0.89
betas:
- 0.5
- 0.9
27 changes: 27 additions & 0 deletions examples/extend_via_sc_schema/extend_via_schema.py
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# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from dataclasses import dataclass
from omegaconf import OmegaConf

import hydra
from hydra.core.config_store import ConfigStore
from hydra_configs.torch.optim import AdamConf


@dataclass
class Config:
optim: AdamConf
debug: bool = False


cs = ConfigStore.instance()
cs.store(name="base_config", node=Config)
cs.store(group="optim", name="base_adam", node=AdamConf)
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We don't have a way for the user to get the config registered? (something like hydra_configs.torch.register_configs()?`
Why are you registering it here?

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Are you implying we consolidate lines 10-18 into a single call:
hydra_configs.torch.register_configs()?

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Not exactly.
Registering a schema for your own config is one thing (line 17), but registering AdamConf (and the rest of the configs hydra-torch is providing) is something we can provide a function (or functions as we have discussed) to do.

This app:

  • defines its own Config class.
  • registers it
  • registers a config class defined by the library.
    I am suggesting that registering config classes defined by the library will be done by the library and will be triggered with a function call.

This will enforce a consistent naming convention for the registered classes and will reduce the boilerplate required to use the configs package.

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Great, I agree. I'll make a quick PR for the registration. Then we can use that in this example.



@hydra.main(config_path="conf", config_name="config")
def my_app(cfg: Config) -> None:
print(OmegaConf.to_yaml(cfg))


if __name__ == "__main__":
my_app()