code: def on_train_batch_start(self, trainer, pl_module, batch, batch_idx):
      if self.log_before_first_step and pl_module.global_step == 0:
          print(f"{self.__class__.__name__}: logging before training")
          self.log_img(pl_module, batch, batch_idx, split="train")
  
imports: import argparse
  import datetime
  import glob
  import inspect
  import os
  import sys
  from inspect import Parameter
  from typing import Union
  import numpy
  import pytorch_lightning
  import torch
  import torchvision
  import wandb
  from matplotlib import pyplot
  from natsort import natsorted
  from omegaconf import OmegaConf
  from packaging import version
  from PIL import Image
  from pytorch_lightning import seed_everything
  from pytorch_lightning.callbacks import Callback
  from pytorch_lightning.loggers import WandbLogger
  from pytorch_lightning.trainer import Trainer
  from pytorch_lightning.utilities import rank_zero_only
  from sgm.util import exists, instantiate_from_config, isheatmap
label_desc: Use image node_id 6 for calling the ImageLogger obj's underlying member method code with example usage: obj.on_train_batch_start(trainer, pl_module, batch, batch_idx) without return types