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train.py
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import dotenv
import hydra
from omegaconf import DictConfig
import time
# load environment variables from `.env` file if it exists
# recursively searches for `.env` in all folders starting from work dir
dotenv.load_dotenv(override=True)
@hydra.main(config_path="configs/", config_name="train.yaml")
def main(config: DictConfig):
# Imports can be nested inside @hydra.main to optimize tab completion
# https://github.com/facebookresearch/hydra/issues/934
from src import utils
from src.training_pipeline import train
# Applies optional utilities
utils.extras(config)
# Train model
return train(config)
if __name__ == "__main__":
start = time.time()
main()
print(f"Execution time: {time.time() - start} secs")