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from typing import List
import hydra
from omegaconf import DictConfig
from pytorch_lightning import Callback
from pytorch_lightning.loggers import Logger
from .logger import RankedLogger
log = RankedLogger(__name__, rank_zero_only=True)
def instantiate_callbacks(callbacks_cfg: DictConfig) -> List[Callback]:
"""Instantiates callbacks from config."""
callbacks: List[Callback] = []
if not callbacks_cfg:
log.warning("No callback configs found! Skipping..")
return callbacks
if not isinstance(callbacks_cfg, DictConfig):
raise TypeError("Callbacks config must be a DictConfig!")
for _, cb_conf in callbacks_cfg.items():
if isinstance(cb_conf, DictConfig) and "_target_" in cb_conf:
log.info(f"Instantiating callback <{cb_conf._target_}>")
callbacks.append(hydra.utils.instantiate(cb_conf))
return callbacks
def instantiate_loggers(logger_cfg: DictConfig) -> List[Logger]:
"""Instantiates loggers from config."""
logger: List[Logger] = []
if not logger_cfg:
log.warning("No logger configs found! Skipping...")
return logger
if not isinstance(logger_cfg, DictConfig):
raise TypeError("Logger config must be a DictConfig!")
for _, lg_conf in logger_cfg.items():
if isinstance(lg_conf, DictConfig) and "_target_" in lg_conf:
log.info(f"Instantiating logger <{lg_conf._target_}>")
logger.append(hydra.utils.instantiate(lg_conf))
return logger
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