code: import Controller
  import tensorflow as tf
  import time
  import efficientnet.tfkeras
  
  # Run pre-loaded pipelines
  start_time= time.time()
  
  #E0 - G
  model = tf.keras.models.load_model("..\\models\\200324_EfficientNetB0NoisyStudent_001.h5", compile=False)
  
  image_tags = ["C:\\Users\\finnt\\OneDrive\\Documents\\Uni\\Year 4\\Honours\\Project\\Lesions\\", ".jpg", "ISIC_", "_downsampled", 0]
  seg_tags = ["C:\\Users\\finnt\\OneDrive\\Documents\\Uni\\Year 4\\Honours\\Project\\Segmentations\\", ".png", "ISIC_", "_segmentation", 0]
  numpy_tags = ["C:\\Users\\finnt\\Documents\\Honours Results\\200324_EfficientNetB0NoisyStudent_001\\grad_cam\\", "_sorted.npy", "ISIC_", "_downsampled", 0]
  label_tag = ["C:\\Users\\finnt\\OneDrive\\Documents\\Uni\\Year 4\\Honours\\Project\\Dual Classifier\\", ".csv", "ISIC_", "_downsampled", 0]
  
  input_tags = [image_tags, numpy_tags, seg_tags, label_tag]
  
  output_dir = "C:\\Users\\finnt\\Documents\\Honours Results\\200324_EfficientNetB0NoisyStudent_001\\grad_cam\\"
  
  Controller.pre_loaded_shap(model, input_tags, output=output_dir, save_csv=True)
  
  #E0 - S
  model = tf.keras.models.load_model("..\\models\\200324_EfficientNetB0NoisyStudent_001.h5", compile=False)
  
  image_tags = ["C:\\Users\\finnt\\OneDrive\\Documents\\Uni\\Year 4\\Honours\\Project\\Lesions\\", ".jpg", "ISIC_", "_downsampled", 0]
  seg_tags = ["C:\\Users\\finnt\\OneDrive\\Documents\\Uni\\Year 4\\Honours\\Project\\Segmentations\\", ".png", "ISIC_", "_segmentation", 0]
  numpy_tags = ["C:\\Users\\finnt\\Documents\\Honours Results\\200324_EfficientNetB0NoisyStudent_001\\shap\\", "_sorted.npy", "ISIC_", "_downsampled", 0]
  label_tag = ["C:\\Users\\finnt\\OneDrive\\Documents\\Uni\\Year 4\\Honours\\Project\\Dual Classifier\\", ".csv", "ISIC_", "_downsampled", 0]
  
  input_tags = [image_tags, numpy_tags, seg_tags, label_tag]
  
  output_dir = "C:\\Users\\finnt\\Documents\\Honours Results\\200324_EfficientNetB0NoisyStudent_001\\shap\\"
  
  Controller.pre_loaded_shap(model, input_tags, output=output_dir, save_csv=True)
  
  #E7 - G
  model = tf.keras.models.load_model("..\\models\\200411_EfficientNetB7NoisyStudent_001.h5", compile=False)
  
  image_tags = ["C:\\Users\\finnt\\OneDrive\\Documents\\Uni\\Year 4\\Honours\\Project\\Lesions\\", ".jpg", "ISIC_", "_downsampled", 0]
  seg_tags = ["C:\\Users\\finnt\\OneDrive\\Documents\\Uni\\Year 4\\Honours\\Project\\Segmentations\\", ".png", "ISIC_", "_segmentation", 0]
  numpy_tags = ["C:\\Users\\finnt\\Documents\\Honours Results\\200411_EfficientNetB7NoisyStudent_001\\grad_cam\\", "_sorted.npy", "ISIC_", "_downsampled", 0]
  label_tag = ["C:\\Users\\finnt\\OneDrive\\Documents\\Uni\\Year 4\\Honours\\Project\\Dual Classifier\\", ".csv", "ISIC_", "_downsampled", 0]
  
  input_tags = [image_tags, numpy_tags, seg_tags, label_tag]
  
  output_dir = "C:\\Users\\finnt\\Documents\\Honours Results\\200411_EfficientNetB7NoisyStudent_001\\grad_cam\\"
  
  Controller.pre_loaded_shap(model, input_tags, output=output_dir, save_csv=True)
  
  print("Finished: " + str((time.time()-start_time)/60) + " mins")
apis: tensorflow.keras.models.load_model