class_docstr: DataHandler generate augmented batches used for training or validation.
  
  Args:
      lr_dir: directory containing the Low Res images.
      hr_dir: directory containing the High Res images.
      patch_size: integer, size of the patches extracted from LR images.
      scale: integer, upscaling factor.
      n_validation_samples: integer, size of the validation set. Only provided if the
          DataHandler is used to generate validation sets.
docstr: Sanity check for dataset. 
docstr_tok: ["Sanity","check","for","dataset","."]
code: def _check_dataset(self):
      """Sanity check for dataset."""
  
      # the order of these asserts is important for testing
      assert (
          len(self.img_list["hr"]) == self.img_list["hr"].shape[0]
      ), "UnevenDatasets"
      assert self._matching_datasets(), "Input/LabelsMismatch"
  
file_path: image-super-resolution/ISR/utils/datahandler.py
imports: import os
  import imageio
  import numpy
  from ISR.utils.logger import get_logger
label_desc: Use image node_id 3 for calling the DataHandler obj's underlying member method code with example usage: obj._check_dataset() without return types