code: def get_loss(self, preds):
      if self.learner.NUM_CLASSES == 2:
          ret = preds[0]
      else:
          index = tf.argmax(tf.math.softmax(preds), axis=1)[0]
          ret = preds[0, index]
          print(f"index: {index}")
      return ret
  
imports: import inspect
  from functools import partial
  from typing import Any, List, Optional, Union
  import matplotlib.cm
  import matplotlib.pyplot
  import numpy
  import tensorflow
  import tensorflow_addons
  from PIL import Image
  from tensorflow import keras
  from tensorflow.keras.models import Model
  from tf_keras_vis.gradcam import Gradcam, GradcamPlusPlus
  from tf_keras_vis.utils import normalize
  from typeguard import check_argument_types, typechecked
  from chitra.import_utils import is_installed
  from .datagenerator import Dataset
label_desc: Use image node_id 4 for calling the InterpretModel obj's underlying member method code with example usage: obj.get_loss(preds) and returns: ret