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"""Util functions for training hydra configs and pytorch lightning."""
import warnings
from omegaconf import DictConfig, OmegaConf
import loguru.logger as log
from pytorch_lightning.loggers.wandb import WandbLogger
from pytorch_lightning.utilities import rank_zero_only
from tqdm import tqdm
@rank_zero_only
def configure_logging(level: str) -> None:
"""Configure the loguru logger for output to terminal and disk."""
# Remove default logger to get tqdm to work properly.
log.remove()
log.add(lambda msg: tqdm.write(msg, end=""), colorize=True, level=level)
def extras(config: DictConfig) -> None:
"""Sets optional utilities."""
# Enable adding new keys.
OmegaConf.set_struct(config, False)
if config.get("ignore_warnings"):
log.info("Disabling python warnings! <config.ignore_warnings=True>")
warnings.filterwarnings("ignore")
if config.get("debug"):
log.info("Running in debug mode! <config.debug=True>")
config.trainer.fast_dev_run = True
if config.trainer.get("fast_dev_run"):
log.info(
"Forcing debugger friendly configuration! <config.trainer.fast_dev_run=True>"
)
# Debuggers do not like GPUs and multiprocessing.
if config.trainer.get("gpus"):
config.trainer.gpus = 0
if config.datamodule.get("pin_memory"):
config.datamodule.pin_memory = False
if config.datamodule.get("num_workers"):
config.datamodule.num_workers = 0
# Force multi-gpu friendly config.
accelerator = config.trainer.get("accelerator")
if accelerator in ["ddp", "ddp_spawn", "dp", "ddp2"]:
log.info(
f"Forcing ddp friendly configuration! <config.trainer.accelerator={accelerator}>"
)
if config.datamodule.get("pin_memory"):
config.datamodule.pin_memory = False
if config.datamodule.get("num_workers"):
config.datamodule.num_workers = 0
# Disable adding new keys to config
OmegaConf.set_struct(config, True)
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