code: def keras_model_interf(model_file):
      import tensorflow as tf
      from tensorflow_addons.layers import StochasticDepth
  
      for gpu in tf.config.experimental.list_physical_devices("GPU"):
          tf.config.experimental.set_memory_growth(gpu, True)
  
      mm = tf.keras.models.load_model(model_file, compile=False)
      return lambda imgs: mm(
          (tf.cast(imgs, "float32") - 127.5) * 0.0078125
      ).numpy()
  
imports: import os
  import cv2
  import numpy
  import pandas
  from tqdm import tqdm
  from skimage import transform
  from sklearn.preprocessing import normalize
  from sklearn.metrics import roc_curve, auc
label_desc: Use image node_id 1 for calling a global function with example usage: keras_model_interf(model_file) and returns: function