code: def check_frequency(self, check_idx):
      if (
          (check_idx % self.batch_freq) == 0
          or (check_idx in self.log_steps)
      ) and (check_idx > 0 or self.log_first_step):
          try:
              self.log_steps.pop(0)
          except IndexError as e:
              print(e)
              pass
          return True
      return False
  
imports: import argparse, os, sys, datetime, glob, importlib, csv
  import numpy
  import time
  import torch
  import torchvision
  import pytorch_lightning
  from packaging import version
  from omegaconf import OmegaConf
  from torch.utils.data import random_split, DataLoader, Dataset, Subset
  from functools import partial
  from PIL import Image
  from pytorch_lightning import seed_everything
  from pytorch_lightning.trainer import Trainer
  from pytorch_lightning.callbacks import ModelCheckpoint, Callback, LearningRateMonitor
  from pytorch_lightning.utilities.distributed import rank_zero_only
  from pytorch_lightning.utilities import rank_zero_info
  from ldm.data.base import Txt2ImgIterableBaseDataset
  from ldm.util import instantiate_from_config
label_desc: Use image node_id 5 for calling the ImageLogger obj's underlying member method code with example usage: obj.check_frequency(check_idx) and returns: False, True