class_docstr: PyTorch Lightening logger integration.
  Pass an instance of this class to ``pytorch_lightning.Training`` as argument ``logger``.
  PyTorch Lightening will call relavent mehtods of this class to log hyper-parameters and metrics.
class_docstr_tok: ["PyTorch","Lightening","logger","integration",".","Pass","an","instance","of","this","class","to","``","pytorch_lightning.Training","``","as","argument","``","logger","``",".","PyTorch","Lightening","will","call","relavent","mehtods","of","this","class","to","log","hyper-parameters","and","metrics","."]
code: def save_dir(self) -> Optional[str]:
      return str(lab.get_experiments_path())
  
file_path: labml/client/labml/utils/lightning.py
imports: from argparse import Namespace
  from typing import Any, Dict, Optional, Union
  import torch
  from pytorch_lightning.loggers.base import LightningLoggerBase, rank_zero_experiment
  from pytorch_lightning.utilities import rank_zero_only
  from labml import experiment, tracker, lab
  from labml.internal.experiment import experiment_singleton
label_desc: Use image node_id 6 for calling the LabMLLightningLogger obj's underlying member method code with example usage: obj.save_dir() and returns: str