code: def testPruneTrainingLoopRaisesError_PruningStepCallbackMissing_CustomTrainingLoop(
      self,
  ):
      pruned_model, _, _, x_train, _ = self._pruned_model_setup(
          custom_training_loop=True
      )
  
      # Throws an error since UpdatePruningStep is missing.
      with self.assertRaises(errors_impl.InvalidArgumentError):
          inp = np.reshape(
              x_train, [self._BATCH_SIZE, 10]
          )  # original shape: [10].
          with tf.GradientTape():
              pruned_model(inp, training=True)
  
file_path: model-optimization/tensorflow_model_optimization/python/core/sparsity/keras/pruning_callbacks_test.py
imports: import os
  import tempfile
  import numpy
  import tensorflow
  from tensorflow_model_optimization.python.core.keras import test_utils
  from tensorflow_model_optimization.python.core.sparsity.keras import prune
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_callbacks
label_desc: Use image node_id 7 for calling the PruneCallbacksTest obj's underlying member method code with example usage: obj.testPruneTrainingLoopRaisesError_PruningStepCallbackMissing_CustomTrainingLoop() without return types