code: def test_step(images, labels):
      # training=False is only needed if there are layers with different
      # behavior during training versus inference (e.g. Dropout).
      predictions = model(images)
      t_loss = loss_object(labels, predictions)
  
      test_loss(t_loss)
      test_accuracy(labels, predictions)
  
file_path: BentoML/examples/tensorflow2_native/train.py
imports: import tensorflow
  from tensorflow.keras.layers import Conv2D
  from tensorflow.keras.layers import Dense
  from tensorflow.keras.layers import Flatten
  import bentoml
label_desc: Use image node_id 2 for calling a global function with example usage: test_step(images, labels) without return types