docstr: Return default logging levels for given hook.
docstr_tok: ["Return","default","logging","levels","for","given","hook","."]
code: def get_default_logging_levels(
      cls,
      fx_name: str,
      on_step: Optional[bool],
      on_epoch: Optional[bool],
  ) -> Tuple[bool, bool]:
      """Return default logging levels for given hook."""
      fx_config = cls.functions[fx_name]
      assert fx_config is not None
      on_step = (
          fx_config["default_on_step"] if on_step is None else on_step
      )
      on_epoch = (
          fx_config["default_on_epoch"]
          if on_epoch is None
          else on_epoch
      )
      return on_step, on_epoch
  
file_path: pytorch-lightning/src/lightning/pytorch/trainer/connectors/logger_connector/fx_validator.py
imports: from typing import Optional, Tuple, Union
  from typing_extensions import TypedDict
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
label_desc: Use image node_id 2 for calling the _FxValidator obj's underlying member method code with example usage: obj.get_default_logging_levels(cls, fx_name, on_step, on_epoch) and returns: on_step,  on_epoch