code: def _predict_and_assert(predictor):
      batch_size = 100
      data = numpy.zeros((batch_size, 784), dtype="float32")
      output = predictor.predict(data)
      assert len(output) == batch_size
  
imports: from __future__ import absolute_import
  import os
  import time
  import pytest
  import numpy
  from sagemaker.serverless import ServerlessInferenceConfig
  from sagemaker.sklearn import SKLearn, SKLearnModel, SKLearnProcessor
  from sagemaker.utils import unique_name_from_base
  from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES
  from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name
label_desc: Use image node_id 11 for calling a global function with example usage: _predict_and_assert(predictor) without return types