Files
Mark Aron Szulyovszky b5ddee8dce feat(HPO): added run_hpo script (#237)
* feat(HPO): added `run_hpo` script

* fix(Linter): ran

* feat(HPO): removed any reference to sweep (superseeded by optuna)

* fix(HPO): optimize for sharpe

* fix(Config): removed glassnode data, save trials from hpo

* feat(Labelling): added three-balanced method works again

* fix(BetSizing): set the correct class labels

* fix(HPO): powerset should return what's expected, added two new normalization methods

* fix(Linter): ran

* fix(DataLoader): sort the dataframe when fetching data

* fix(Config): only take z-score of other assets
2022-03-15 14:43:16 +01:00

45 lines
1.1 KiB
Python

from config.types import RawConfig
from typing import Optional
from training.types import Stats
def launch_wandb(project_name: str, default_config: RawConfig) -> Optional[object]:
from wandb_setup import get_wandb
wandb = get_wandb()
if wandb is None:
raise Exception(
"Wandb can not be initalized, the environment variable WANDB_API_KEY is missing (can also use .env file)"
)
else:
wandb.init(project=project_name, config=vars(default_config), reinit=True)
return wandb
def override_config_with_wandb_values(
wandb: Optional[object], raw_config: RawConfig
) -> RawConfig:
if wandb is None:
return raw_config
wandb_config: dict = wandb.config
config_dict = vars(raw_config)
for k in config_dict:
config_dict[k] = wandb_config[k]
return RawConfig(**config_dict)
def send_report_to_wandb(stats: Stats, wandb: Optional[object]):
if wandb is None:
return
run = wandb.run
run.save()
for key, value in stats.items():
run.log({key: value})
run.finish()