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run.py
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run.py
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# template: https://github.com/ashleve/lightning-hydra-template/blob/main/run.py
import dotenv
import hydra
from omegaconf import DictConfig
import os
import sys
import socket
#import multiprocessing as mp
sys.setrecursionlimit(2000)
# load environment variables from `.env` file if it exists
# recursively searches for `.env` in all folders starting from work dir
dir_path = os.path.dirname(os.path.realpath(__file__))
dotenv.load_dotenv(dir_path+'/pc_environment.env',override=True)
# dotenv.dotenv_values("pc_environment.env")
@hydra.main(config_path="configs/", config_name="config.yaml")
def main(config: DictConfig):
# import torch
# torch.multiprocessing.set_sharing_strategy('file_system')
# Imports should be nested inside @hydra.main to optimize tab completion
# Read more here: https://github.com/facebookresearch/hydra/issues/934
from src.train import train
from src.utils import utils
# A couple of optional utilities:
# - disabling python warnings
# - easier access to debug mode
# - forcing debug friendly configuration
# You can safely get rid of this line if you don't want those
utils.extras(config)
# Pretty print config using Rich library
if config.get("print_config"):
utils.print_config(config, resolve=True)
# Train model
return train(config)
if __name__ == "__main__":
main()