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: Transforms each individual image of the batch independently. 
docstr_tok: ["Transforms","each","individual","image","of","the","batch","independently","."]
code: def _transform_batch(self, batch, transforms):
      """Transforms each individual image of the batch independently."""
  
      t_batch = np.array(
          [
              self._apply_transform(img, transforms[i])
              for i, img in enumerate(batch)
          ]
      )
      return t_batch
  
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 8 for calling the DataHandler obj's underlying member method code with example usage: obj._transform_batch(batch, transforms) and returns: t_batch